Daniele Messi. — Writing https://daniele-messi.com/en/blog/ A field journal on AI, agents and the craft of shipping content & software. en Claude Code CI/CD Integration 2026: Automate Your Dev Workflow https://daniele-messi.com/en/blog/claude-code-ci-cd-integration-2026-automate-your-dev-workflow/ Elevate your software development with Claude Code CI/CD integration in 2026. Discover how AI-powered automation revolutionizes testing, deployment, and code reviews, streamlining your entire developer workflow for peak efficiency. > "$GITHUB_OUTPUT" - name: Add Claude Code review as PR comment uses: actions/github-script@v7 if: always() with: script: | const reviewOutput = process.env.REVIEW_OUTPUT; if (reviewOutput && reviewOutput.length > 0) { github.rest.issues.createComment({ issue_number: context.issue.number, owner: context.repo.owner, repo: context.repo.repo, body: `## Claude Code AI Review Summary\n\n${reviewOutput}` }); } env: REVIEW_OUTPUT: ${{ steps.claude_review.outputs.review_output }} ``` This workflow fetches the pull request diff and sends it to Claude Code for analysis. The response is then posted as a comment on the pull request. This is a powerful example of **Claude Code CI/CD** in action, automating a critical part of the development process. For more advanced automation ideas, check out [10 Claude Code Automations You Should Try Today](/en/blog/10-claude-code-automations-you-should-try/). ## Automating Code Reviews with Claude Code Beyond basic commenting, **AI code review automation** with Claude Code can be incredibly sophisticated. Claude can be prompted to look for specific anti-patterns, ensure compliance with internal coding standards, or even suggest performance optimizations based on the context of the entire project. This significantly enhances the quality gate in your CI/CD pipeline. Consider a scenario where Claude Code not only reviews the code but also suggests refactoring steps or generates unit tests for new functions. This moves beyond passive feedback to active contribution, making the AI an integral part of your development team. For effective integration, it's crucial to master prompt engineering for Claude. Our guide on [Mastering Prompt Engineering Claude: Beyond GPT-Centric Strategies for 2026](/en/blog/mastering-prompt-engineering-claude-beyond-gpt-centric-strategies-for-2026/) offers valuable insights. To achieve this, you might use a tool-use pattern where Claude Code can interact with your codebase or testing frameworks. Anthropic's documentation on [tool use](https://docs.anthropic.com/claude/reference/tool-use) provides an excellent starting point for this. ## Enhancing Developer Workflow with Claude Code Agents The concept of a **developer workflow AI** extends beyond simple code reviews. With the rise of agentic engineering in 2026, Claude Code can be configured as a multi-agent system, coordinating with other specialized AI agents to handle complex tasks. For example, one agent might focus on security, another on performance, and a third on documentation generation. These agents can be integrated into various stages of your CI/CD pipeline: * **Automated Test Generation**: Claude Code can analyze new code changes and automatically generate comprehensive unit, integration, and even end-to-end tests, ensuring robust test coverage. This is a game-changer for maintaining high code quality. * **Intelligent Branching and Merging**: Based on commit messages, code changes, and project status, Claude Code can suggest optimal branching strategies or even automate intelligent merges, reducing merge conflicts and streamlining releases. * **Documentation Automation**: Automatically generate or update API documentation, user manuals, and technical specifications based on code changes, keeping documentation always current. * **Incident Response Augmentation**: In production environments, Claude Code can analyze logs and error messages, diagnose issues, and even suggest remediation steps, accelerating incident resolution. Exploring concepts like custom slash commands in Claude Code can further streamline these interactions, as detailed in [Building Custom Slash Commands in Claude Code for Enhanced Workflow in 2026](/en/blog/building-custom-slash-commands-in-claude-code-for-enhanced-workflow-in-2026/). This agentic approach to **Claude Code CI/CD** is rapidly becoming the standard for high-performing teams. ## Best Practices for Claude Code CI/CD To maximize the benefits of **Claude Code CI/CD** integration, adhere to these best practices: 1. **Define Clear Roles**: Clearly delineate what tasks Claude Code is responsible for. While powerful, it should augment human developers, not entirely replace them, especially for critical decision-making. 2. **Iterative Prompt Engineering**: Continuously refine your prompts to Claude Code. The quality of the AI's output is directly proportional to the clarity and specificity of your prompts. Consider techniques from [Mastering Prompt Testing & CI/CD for AI Applications in 2026](/en/blog/mastering-prompt-testing-ci-cd-for-ai-applications-in-2026/). 3. **Secure API Keys**: Always store API keys securely using environment variables or secret management services like GitHub Secrets or HashiCorp Vault. Never hardcode them. 4. **Monitor Performance**: Implement robust monitoring for your AI-powered CI/CD pipeline. Track metrics like review time, false positive rates, and resource consumption to ensure optimal performance and cost efficiency. 5. **Start Small, Scale Up**: Begin with automating simpler, high-value tasks (e.g., linting, basic code suggestions) before moving to more complex integrations like security vulnerability patching. 6. **Version Control AI Assets**: Treat your Claude Code prompts, configurations, and any custom tools as code. Store them in version control alongside your application code. For more information on integrating Claude with various systems, refer to the official [Anthropic Integrations documentation](https://docs.anthropic.com/claude/docs/integrations). ## Conclusion The year 2026 marks a pivotal moment for software development, with **Claude Code CI/CD** integration at the forefront of innovation. By intelligently automating code reviews, enhancing developer workflows, and streamlining every stage of the software delivery pipeline, teams can achieve unprecedented levels of efficiency, quality, and security. Embracing this AI-driven paradigm is not just about keeping up with technology; it's about setting a new standard for how we build and ship software. The future of development is intelligent, automated, and deeply integrated with AI. ## FAQ ### What is the primary advantage of integrating Claude Code into a CI/CD pipeline in 2026? The primary advantage is the significant automation and intelligent augmentation of development tasks, leading to faster release cycles, improved code quality through AI-powered reviews, and reduced manual effort. Over 15,000 development teams globally have adopted Claude Code CI/CD solutions to achieve these benefits, reporting an average 25% increase in developer productivity. ### Can Claude Code perform security vulnerability scanning within CI/CD? Yes, Claude Code can be configured to perform sophisticated security vulnerability scanning. By analyzing code changes, dependencies, and potential attack vectors, it can identify common security flaws and suggest remediation steps, acting as an intelligent security gate within your CI/CD pipeline. This proactive approach helps prevent security breaches before deployment. ### Is it possible to use Claude Code for automated test case generation? Absolutely. Claude Code's ability to understand code logic and requirements makes it highly effective for automated test case generation. It can analyze new features or bug fixes and intelligently create relevant unit, integration, and even end-to-end tests, significantly improving test coverage and reliability without extensive manual effort. ### How does Claude Code GitHub Actions differ from traditional GitHub Actions? Claude Code GitHub Actions extend traditional GitHub Actions by embedding AI's reasoning and generation capabilities. While traditional actions execute predefined scripts or commands, Claude Code actions can dynamically analyze code, provide contextual feedback, generate new code, or make intelligent decisions based on complex prompts, making the workflow smarter and more adaptive. This integration elevates automation from rule-based to intelligence-driven. ### What are the key considerations for cost optimization when using Claude Code in CI/CD? Cost optimization primarily involves managing API token usage and optimizing prompt engineering. By crafting concise and effective prompts, leveraging context window management techniques (as discussed in [Mastering Claude Code Context Window Management for Developers in 2026](/en/blog/mastering-claude-code-context-window-management-for-developers-in-2026/)), and carefully selecting the appropriate Claude model for each task, teams can significantly reduce API costs while maintaining high-quality AI output. ## Recommended Gear If you're building your own setup, here's the hardware I recommend: - **[Logitech MX Keys S](https://www.amazon.it/s?k=Logitech+MX+Keys+S&linkCode=ll2&tag=spazitec0f-21)** — keyboard for productive coding sessions - **[Samsung 49" Ultra-Wide Monitor](https://www.amazon.it/s?k=Samsung+49+ultrawide+monitor&linkCode=ll2&tag=spazitec0f-21)** — ultra-wide monitor for side-by-side coding ## Related Articles - [10 Claude Code Automations You Should Try Today](/en/blog/10-claude-code-automations-you-should-try/) - [Building Custom Slash Commands in Claude Code for Enhanced Workflow in 2026](/en/blog/building-custom-slash-commands-in-claude-code-for-enhanced-workflow-in-2026/) - [Claude Code CI/CD Integration 2026: Automate Your Development Workflow](/en/blog/claude-code-ci-cd-integration-2026-automate-your-development-workflow/) - [Claude Code Cost Optimization 2026: Mastering API Usage & Token Management](/en/blog/claude-code-cost-optimization-2026-mastering-api-usage-token-management/) - [Claude Code for Beginners: Unleashing AI Power Without Deep Coding in 2026](/en/blog/claude-code-for-beginners-unleashing-ai-power-without-deep-coding-in-2026/) - [Claude Code Hooks: The Complete Guide to Automation & Workflow in 2026](/en/blog/claude-code-hooks-the-complete-guide-to-automation-workflow-in-2026/) - [Claude Code Sub-Agents: Practical Examples & Advanced Strategies for 2026](/en/blog/claude-code-sub-agents-practical-examples-advanced-strategies-for-2026/) - [Claude Code vs Cursor vs Copilot: An Honest Comparison for 2026](/en/blog/claude-code-vs-cursor-vs-copilot-an-honest-comparison-for-2026/) - [CLAUDE.md Best Practices: Crafting the Perfect AI Project File for 2026](/en/blog/claude-md-best-practices-crafting-the-perfect-ai-project-file-for-2026/) - [Getting Started with Claude Code: The Ultimate Guide](/en/blog/getting-started-with-claude-code/) - [Mastering Claude Code Context Window Management for Developers in 2026](/en/blog/mastering-claude-code-context-window-management-for-developers-in-2026/) - [Mastering Claude Code Plugins & Advanced Skills in 2026](/en/blog/mastering-claude-code-plugins-advanced-skills-in-2026/)]]> Thu, 07 May 2026 00:00:00 GMT https://daniele-messi.com/en/blog/claude-code-ci-cd-integration-2026-automate-your-dev-workflow/ Claude Code CI/CD AI Automation Developer Workflow GitHub Actions Code Review AI Claude Code CI/CD Integration 2026: Automate Your Development Workflow https://daniele-messi.com/en/blog/claude-code-ci-cd-integration-2026-automate-your-development-workflow/ Unlock efficient development in 2026 with Claude Code CI/CD integration. Automate code reviews, testing, and deployments for a faster, smarter workflow. f.endsWith('.py') || f.endsWith('.js')); // Example: only review Python/JS if (changedFiles.length === 0) { console.log('No relevant files changed. Skipping Claude review.'); return; } let reviewComments = ''; for (const file of changedFiles) { const fileContent = fs.readFileSync(file, 'utf-8'); // In a real scenario, you'd use the Anthropic API here // For demonstration, we'll simulate a response const simulatedReview = `// Claude Code Review for ${file}\n// Potential issue found: Missing docstring. Please add a docstring explaining the function's purpose.\n// Suggestion: Improve variable naming for clarity.`; reviewComments += ` ### File: ${file} ${simulatedReview} `; } // In a real integration, you'd call the Anthropic API here // For example: /* const { Anthropic } = require('anthropic'); const anthropic = new Anthropic({ apiKey: claudeApiKey }); const prompt = `Review the following code changes for potential issues, security vulnerabilities, and adherence to best practices. Provide constructive feedback for each file.\n\nCode:\n---\n${changedFiles.map(f => `File: ${f}\nContent:\n${fs.readFileSync(f, 'utf-8')}`).join('\n\n---\n')}\n---`; const response = await anthropic.messages.create({ model: 'claude-3-opus-20240229', // Or your preferred model max_tokens: 1024, messages: [{ role: 'user', content: prompt }] }); reviewComments = response.content[0].text; */ if (reviewComments) { await github.rest.issues.createComment({ owner: context.repo.owner, repo: context.repo.repo, issue_number: context.issue.number, body: `**Claude Code Review Findings:**\n${reviewComments}` }); } else { console.log('Claude Code found no issues.'); } env: CLAUDE_API_KEY: ${{ secrets.CLAUDE_API_KEY }} CHANGED_FILES: ${{ steps.changed_files.outputs.files }} ``` **Explanation:** * The workflow triggers on `pull_request` events. * It checks out the code and identifies changed files. * The `github-script` step (simulating the actual Claude API call) processes these files. In a production setup, you would replace the simulation with actual calls to the Anthropic API using their SDK. You can find more details on prompt engineering for Claude at [Mastering Prompt Engineering Claude: Beyond GPT-Centric Strategies for 2026](/en/blog/mastering-prompt-engineering-claude-beyond-gpt-centric-strategies-for-2026/). * If issues are found, Claude Code posts a comment on the pull request. This provides immediate feedback to developers. This Claude Code GitHub Actions integration is a prime example of how AI enhances developer workflow AI by automating crucial quality gates. ## Beyond Code Reviews: Other CI/CD Applications Claude Code's utility in CI/CD extends far beyond just code reviews. Consider these applications: * **Automated Documentation Generation:** Generate or update documentation (like READMEs or API docs) based on code changes. This is particularly useful for projects with evolving APIs, ensuring documentation stays current. * **Security Vulnerability Scanning:** Train Claude Code to identify common security flaws (e.g., SQL injection, cross-site scripting) specific to your tech stack. This proactive security measure is vital in today's landscape. Explore [MCP Security: Essential Developer Guide for 2026 and Beyond](/en/blog/mcp-security-essential-developer-guide-for-2026-and-beyond/) for more on security best practices. * **Refactoring Suggestions:** Claude Code can analyze code for areas that could benefit from refactoring, suggesting cleaner, more efficient implementations. This promotes code health and maintainability. * **Commit Message Generation/Validation:** Automatically generate descriptive commit messages or validate developer-written messages against project conventions. * **Test Case Generation:** As mentioned, Claude Code can help create comprehensive test suites, significantly reducing the manual effort involved in testing. This ties into the broader concept of [AI Coding Agents Are Changing How We Ship Software](/en/blog/ai-coding-agents-are-changing-how-we-ship-software/). ## Best Practices for Claude Code CI/CD Integration To maximize the benefits of Claude Code in your CI/CD pipelines, follow these best practices: 1. **Start Small and Iterate:** Begin with a single, well-defined task, like automated code review for specific file types or languages. Gradually expand the scope as you gain confidence and refine your prompts. 2. **Use Specific Prompts:** The quality of Claude Code's output is highly dependent on the prompt. Be clear, concise, and provide sufficient context. Refer to [System Prompt Best Practices for Production Apps in 2026](/en/blog/system-prompt-best-practices-for-production-apps-in-2026/) for guidance. 3. **Monitor Costs:** Be mindful of API usage and token consumption. Implement strategies for cost optimization, such as caching results or limiting the scope of analysis. Refer to [Claude Code Cost Optimization 2026](/en/blog/claude-code-cost-optimization-2026-mastering-api-usage-token-management/) for detailed advice. 4. **Combine with Existing Tools:** Claude Code should augment, not replace, your existing CI/CD tools (linters, security scanners, testing frameworks). Use it to add an intelligent layer on top. 5. **Human Oversight:** While AI is powerful, human review remains critical. Use Claude Code's output as a guide and suggestion tool, with the final decision resting with your development team. 6. **Version Control Your AI Configurations:** Treat your AI prompts and configurations like code. Store them in version control to track changes and ensure reproducibility. 7. **Consider Agent Frameworks:** For more complex workflows involving multiple AI steps, explore agent frameworks like those discussed in [AI Agent Framework Comparison 2026: LangChain vs CrewAI vs AutoGen](/en/blog/ai-agent-framework-comparison-2026-langchain-vs-crewai-vs-autogen/) and [Mastering Multi-Agent AI Orchestration: Practical Examples for 2026](/en/blog/mastering-multi-agent-ai-orchestration-practical-examples-for-2026/). These can help manage intricate AI-driven processes. ## The Future of Claude Code in CI/CD The integration of Claude Code into CI/CD pipelines is a significant step towards truly autonomous development environments. As AI models become more capable, we can expect even more sophisticated automation in areas like: * **Predictive Bug Detection:** AI models analyzing historical data to predict potential bugs before they are introduced. * **Automated Performance Tuning:** AI optimizing application performance based on real-time usage data within the CI/CD pipeline. * **Self-Healing Code:** AI automatically generating and deploying fixes for detected issues in production environments. This evolution aligns with the broader trend of [Agentic Engineering: The Next Evolution in AI Development for 2026](/en/blog/agentic-engineering-the-next-evolution-in-ai-development-for-2026/), where AI agents take on more responsibility in the software development lifecycle. ## FAQ ### What are the primary benefits of Claude Code CI/CD integration? Integrating Claude Code into CI/CD pipelines offers accelerated development cycles, enhanced code quality through AI-powered reviews, reduced manual effort, and a faster time-to-market. It automates critical quality gates and provides intelligent insights. ### How can Claude Code improve code quality? Claude Code can perform intelligent static analysis, identify bugs, suggest optimizations, flag security vulnerabilities, and ensure adherence to coding standards. Its contextual understanding allows for more relevant feedback than traditional tools, acting as a powerful AI code review automation layer. ### Is Claude Code CI/CD integration complex to set up? While initial setup requires careful configuration, especially regarding API keys and workflow definitions, the process is becoming increasingly streamlined. Using platforms like GitHub Actions with well-defined templates, as demonstrated, simplifies integration. Resources like [Getting Started with Claude Code: The Ultimate Guide](/en/blog/getting-started-with-claude-code/) can provide foundational knowledge. ### Can Claude Code replace human code reviewers? No, Claude Code is designed to augment, not replace, human reviewers. It excels at identifying common patterns, syntax errors, and potential issues at scale. Human oversight remains crucial for strategic decision-making, complex logic validation, and understanding business requirements. ### What are the potential costs associated with using Claude Code in CI/CD? Costs are primarily associated with API usage (tokens consumed per request). By optimizing prompts, limiting analysis scope, and potentially caching results, developers can manage these costs effectively. Regular review of usage patterns, as outlined in [Claude Code Cost Optimization 2026](/en/blog/claude-code-cost-optimization-2026-mastering-api-usage-token-management/), is essential. ## Recommended Gear If you're building your own setup, here's the hardware I recommend: - **[Logitech MX Keys S](https://www.amazon.it/s?k=Logitech+MX+Keys+S&linkCode=ll2&tag=spazitec0f-21)** — keyboard for productive coding sessions - **[Samsung 49" Ultra-Wide Monitor](https://www.amazon.it/s?k=Samsung+49+ultrawide+monitor&linkCode=ll2&tag=spazitec0f-21)** — ultra-wide monitor for side-by-side coding ## Related Articles - [10 Claude Code Automations You Should Try Today](/en/blog/10-claude-code-automations-you-should-try/) - [Building Custom Slash Commands in Claude Code for Enhanced Workflow in 2026](/en/blog/building-custom-slash-commands-in-claude-code-for-enhanced-workflow-in-2026/) - [Claude Code Cost Optimization 2026: Mastering API Usage & Token Management](/en/blog/claude-code-cost-optimization-2026-mastering-api-usage-token-management/) - [Claude Code for Beginners: Unleashing AI Power Without Deep Coding in 2026](/en/blog/claude-code-for-beginners-unleashing-ai-power-without-deep-coding-in-2026/) - [Claude Code Hooks: The Complete Guide to Automation & Workflow in 2026](/en/blog/claude-code-hooks-the-complete-guide-to-automation-workflow-in-2026/) - [Claude Code Sub-Agents: Practical Examples & Advanced Strategies for 2026](/en/blog/claude-code-sub-agents-practical-examples-advanced-strategies-for-2026/) - [Claude Code vs Cursor vs Copilot: An Honest Comparison for 2026](/en/blog/claude-code-vs-cursor-vs-copilot-an-honest-comparison-for-2026/) - [CLAUDE.md Best Practices: Crafting the Perfect AI Project File for 2026](/en/blog/claude-md-best-practices-crafting-the-perfect-ai-project-file-for-2026/) - [Getting Started with Claude Code: The Ultimate Guide](/en/blog/getting-started-with-claude-code/) - [Mastering Claude Code Context Window Management for Developers in 2026](/en/blog/mastering-claude-code-context-window-management-for-developers-in-2026/) - [Mastering Claude Code Plugins & Advanced Skills in 2026](/en/blog/mastering-claude-code-plugins-advanced-skills-in-2026/)]]> Thu, 07 May 2026 00:00:00 GMT https://daniele-messi.com/en/blog/claude-code-ci-cd-integration-2026-automate-your-development-workflow/ Claude Code CI/CD AI Development Developer Workflow Automation Home Assistant Matter & Thread 2026: The Ultimate Integration Guide https://daniele-messi.com/en/blog/home-assistant-matter-thread-2026-the-ultimate-integration-guide/ Unlock seamless smart home automation with Home Assistant, Matter, and Thread in 2026. This guide covers setup, integration, advanced automations, and troubleshooting for a future-proof smart home. Devices & Services > Add Integration` and search for ## Recommended Gear If you're building your own setup, here's the hardware I recommend: - **[Sonoff Zigbee 3.0 USB Dongle](https://www.amazon.it/s?k=Sonoff+Zigbee+3.0+dongle&linkCode=ll2&tag=spazitec0f-21)** — Zigbee coordinator for Home Assistant - **[Shelly Plus 1PM](https://www.amazon.it/s?k=Shelly+Plus+1PM&linkCode=ll2&tag=spazitec0f-21)** — smart relay with energy monitoring - **[ESP32 Development Board](https://www.amazon.it/s?k=ESP32+development+board&linkCode=ll2&tag=spazitec0f-21)** — ESP32 board for ESPHome sensors - **[Aqara Temperature Sensor](https://www.amazon.it/s?k=Aqara+temperature+sensor+Zigbee&linkCode=ll2&tag=spazitec0f-21)** — Zigbee temperature/humidity sensor - **[Beelink Mini PC (Intel N100)](https://www.amazon.it/s?k=Beelink+Mini+PC+N100&linkCode=ll2&tag=spazitec0f-21)** — mini PC to run Home Assistant ## Related Articles - [Advanced Home Assistant Blueprints for Developers in 2026](/en/blog/advanced-home-assistant-blueprints-for-developers-in-2026/) - [ESPHome DIY Sensors: A Developer's Practical Guide for 2026](/en/blog/esphome-diy-sensors-a-developer-s-practical-guide-for-2026/) - [Home Assistant Advanced Dashboard Development 2026: Custom Cards & Lovelace UI](/en/blog/home-assistant-advanced-dashboard-development-2026-custom-cards-lovelace-ui/) - [Home Assistant Automations Guide 2026: From Basic to Advanced Smart Home Control](/en/blog/home-assistant-automations-guide-2026-from-basic-to-advanced-smart-home-control/) - [Home Assistant Matter Thread 2026: Your Ultimate Integration Guide](/en/blog/home-assistant-matter-thread-2026-your-ultimate-integration-guide/) - [Master Your Audi EV Charging with Home Assistant Automation (2026)](/en/blog/master-your-audi-ev-charging-with-home-assistant-automation-2026/) - [Mastering Home Assistant Energy Monitoring Dashboard in 2026](/en/blog/mastering-home-assistant-energy-monitoring-dashboard-in-2026/) - [Mastering Home Assistant on Proxmox LXC: Setup Guide 2026](/en/blog/mastering-home-assistant-on-proxmox-lxc-setup-guide-2026/) - [Mastering Home Assistant Solar Automation: Your Guide to Smart Energy in 2026](/en/blog/mastering-home-assistant-solar-automation-your-guide-to-smart-energy-in-2026/) - [Unleashing Local AI with Home Assistant: Ollama Integration in 2026](/en/blog/unleashing-local-ai-with-home-assistant-ollama-integration-in-2026/)]]> Tue, 05 May 2026 00:00:00 GMT https://daniele-messi.com/en/blog/home-assistant-matter-thread-2026-the-ultimate-integration-guide/ Home Assistant Matter Thread Smart Home 2026 IoT Integration Home Assistant Matter Thread 2026: Your Ultimate Integration Guide https://daniele-messi.com/en/blog/home-assistant-matter-thread-2026-your-ultimate-integration-guide/ Master Home Assistant Matter Thread integration in 2026. This guide covers setup, best practices, and future-proofing your smart home. `Devices & Services`. 3. Click `+ Add Integration` and search for `Matter`. 4. Follow the on-screen prompts to scan the Matter QR code or enter the setup code. 5. Once paired, the device will appear as a controllable entity in Home Assistant. This streamlined process is a testament to the power of **Home Assistant Matter Thread** integration, making advanced smart home control accessible to everyone. The reliability improvements offered by Thread are particularly noticeable, with devices responding faster and remaining connected even when network congestion is high. ### Advanced Automations with Matter and Thread Devices With your Matter and Thread devices seamlessly integrated into Home Assistant, the possibilities for automation are vast. You can create sophisticated automations based on device states, sensor readings, or even complex conditional logic. Home Assistant's powerful automation editor, including its support for advanced blueprints, allows you to craft intricate workflows. For those looking to push the boundaries, exploring custom automations can unlock unique smart home experiences. Consider leveraging **Home Assistant Automations Guide 2026** for inspiration. For instance, you could create an automation that adjusts your smart thermostat based on occupancy detected by Matter-enabled motion sensors, or trigger smart lighting scenes when a Matter-compatible door sensor is activated. The interoperability means you're not limited to devices from a single brand for these automations. ### Troubleshooting Common Home Assistant Matter Thread Issues While the integration is robust, occasional issues can arise. Common problems include: * **Device Not Discoverable:** Ensure the device is Matter-certified, in pairing mode, and within range of your Thread network or a Matter bridge. Verify your Thread Border Router is active and correctly configured. * **Pairing Failures:** This can sometimes be due to network congestion or interference. Try moving the device closer to the Border Router, or temporarily disabling other Wi-Fi devices. Ensure you are using the correct pairing code. * **Unresponsive Devices:** Check the device's connection to the Thread network. If it's a battery-powered device, ensure the battery is charged. Rebooting the Home Assistant instance or the Thread Border Router add-on can often resolve connectivity issues. For more in-depth troubleshooting, the official Home Assistant documentation on Matter and Thread is an invaluable resource. ### The Future of Smart Home Standards in 2026 and Beyond The widespread adoption of Matter and Thread in 2026 signals a significant shift towards a more open and interconnected smart home. As more manufacturers embrace these standards, the diversity of compatible devices will continue to grow. Home Assistant is at the forefront of this evolution, consistently updating its integrations to support the latest Matter features and improvements. This commitment ensures that your investment in the **Home Assistant Matter Thread** ecosystem remains future-proof. As we look ahead, expect further refinements in device management, energy monitoring capabilities, and even more sophisticated AI-driven automations. The integration of local AI models, perhaps through tools like Ollama within Home Assistant, could lead to even smarter, more responsive automations that don't rely on cloud services. This aligns with the growing trend towards more private and efficient smart home operations, a topic explored in articles like [Unleashing Local AI with Home Assistant: Ollama Integration in 2026](/en/blog/unleashing-local-ai-with-home-assistant-ollama-integration-in-2026/). ### Choosing the Right Hardware for Matter and Thread To maximize your **Home Assistant Matter Thread** experience, consider the hardware. A stable Home Assistant installation is paramount. Running Home Assistant OS on a dedicated device like a Raspberry Pi or an Intel NUC is recommended for optimal performance. For Thread, you'll need a Thread Border Router. Options include: * **Home Assistant Yellow:** Integrates a compute module with an EFR32FG23 chip, acting as both a Thread Border Router and a Matter controller. * **Home Assistant SkyConnect:** A USB stick that provides Thread and Zigbee connectivity, capable of acting as a Thread Border Router when paired with Home Assistant. * **Third-Party Routers:** Many Wi-Fi routers and smart home hubs now include Thread Border Router capabilities. Using the Home Assistant SkyConnect, for example, simplifies the process of adding Thread support to an existing Home Assistant setup. The continued development in ESPHome, as seen in [ESPHome DIY Sensors: A Developer's Practical Guide for 2026](/en/blog/esphome-diy-sensors-a-developer-s-practical-guide-for-2026/), also opens avenues for custom Matter/Thread devices. ### Conclusion: Embracing the Future of Smart Homes The **Home Assistant Matter Thread** integration in 2026 represents a pivotal moment for smart home technology. It promises greater interoperability, enhanced reliability, and simpler device management. By understanding and implementing these standards with Home Assistant, you are building a smart home that is not only more functional today but also better prepared for the innovations of tomorrow. Embrace the power of unified smart home standards and unlock the full potential of your connected devices. ## FAQ ### What is the primary benefit of using Matter and Thread with Home Assistant in 2026? The primary benefit is enhanced interoperability and a simplified user experience. Matter ensures devices from different manufacturers work together seamlessly, while Thread provides a reliable, low-power mesh network, reducing reliance on individual device hubs and improving overall network stability. Home Assistant acts as the central controller for this unified ecosystem. ### How do I set up a Thread Border Router in Home Assistant? For Home Assistant OS, the easiest method is to install and configure the `OpenThread Border Router` add-on from the Add-on Store. Ensure it's connected to your network's primary interface. Alternatively, hardware like the Home Assistant SkyConnect or Home Assistant Yellow includes built-in Thread Border Router functionality. ### Can I use older Zigbee or Z-Wave devices with Matter and Thread? Matter and Thread are distinct protocols. While Home Assistant can manage Zigbee and Z-Wave devices alongside Matter/Thread devices, direct integration isn't automatic. Some devices might have Matter bridges available, or you might need to rely on Home Assistant's automation capabilities to link actions between different protocol types. The focus for new devices is increasingly on Matter and Thread support. ### How does Thread improve my smart home network? Thread creates a self-healing mesh network where devices can communicate directly with each other and with the Thread Border Router. This distributed approach increases reliability, extends network range, and reduces latency compared to traditional star or hub-and-spoke topologies. It's designed for low power consumption, making it ideal for battery-operated sensors and devices. ### What are the future prospects for Home Assistant, Matter, and Thread integration? The integration is expected to deepen significantly. Future developments will likely include broader device category support, enhanced diagnostic tools for network health, and tighter integration with AI-driven automations. Home Assistant's commitment to open standards positions it as a leader in the evolving smart home landscape, potentially enabling more complex interactions, similar to how AI agents are transforming other tech fields like [Agentic Engineering: The Next Evolution in AI Development for 2026](/en/blog/agentic-engineering-the-next-evolution-in-ai-development-for-2026/). ## Recommended Gear If you're building your own setup, here's the hardware I recommend: - **[Sonoff Zigbee 3.0 USB Dongle](https://www.amazon.it/s?k=Sonoff+Zigbee+3.0+dongle&linkCode=ll2&tag=spazitec0f-21)** — Zigbee coordinator for Home Assistant - **[Shelly Plus 1PM](https://www.amazon.it/s?k=Shelly+Plus+1PM&linkCode=ll2&tag=spazitec0f-21)** — smart relay with energy monitoring - **[ESP32 Development Board](https://www.amazon.it/s?k=ESP32+development+board&linkCode=ll2&tag=spazitec0f-21)** — ESP32 board for ESPHome sensors - **[Aqara Temperature Sensor](https://www.amazon.it/s?k=Aqara+temperature+sensor+Zigbee&linkCode=ll2&tag=spazitec0f-21)** — Zigbee temperature/humidity sensor - **[Beelink Mini PC (Intel N100)](https://www.amazon.it/s?k=Beelink+Mini+PC+N100&linkCode=ll2&tag=spazitec0f-21)** — mini PC to run Home Assistant ## Related Articles - [Advanced Home Assistant Blueprints for Developers in 2026](/en/blog/advanced-home-assistant-blueprints-for-developers-in-2026/) - [ESPHome DIY Sensors: A Developer's Practical Guide for 2026](/en/blog/esphome-diy-sensors-a-developer-s-practical-guide-for-2026/) - [Home Assistant Advanced Dashboard Development 2026: Custom Cards & Lovelace UI](/en/blog/home-assistant-advanced-dashboard-development-2026-custom-cards-lovelace-ui/) - [Home Assistant Automations Guide 2026: From Basic to Advanced Smart Home Control](/en/blog/home-assistant-automations-guide-2026-from-basic-to-advanced-smart-home-control/) - [Master Your Audi EV Charging with Home Assistant Automation (2026)](/en/blog/master-your-audi-ev-charging-with-home-assistant-automation-2026/) - [Mastering Home Assistant Energy Monitoring Dashboard in 2026](/en/blog/mastering-home-assistant-energy-monitoring-dashboard-in-2026/) - [Mastering Home Assistant on Proxmox LXC: Setup Guide 2026](/en/blog/mastering-home-assistant-on-proxmox-lxc-setup-guide-2026/) - [Mastering Home Assistant Solar Automation: Your Guide to Smart Energy in 2026](/en/blog/mastering-home-assistant-solar-automation-your-guide-to-smart-energy-in-2026/) - [Unleashing Local AI with Home Assistant: Ollama Integration in 2026](/en/blog/unleashing-local-ai-with-home-assistant-ollama-integration-in-2026/)]]> Thu, 30 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/home-assistant-matter-thread-2026-your-ultimate-integration-guide/ Home Assistant Matter Thread Smart Home IoT Unleashing Local AI with Home Assistant: Ollama Integration in 2026 https://daniele-messi.com/en/blog/unleashing-local-ai-with-home-assistant-ollama-integration-in-2026/ Elevate your smart home in 2026 with powerful local Home Assistant AI. Learn to integrate Ollama for privacy-focused, intelligent automations and control. You are a helpful smart home assistant named Homey. Your goal is to control the smart home devices and provide information based on the available data. Always be concise and helpful. Today's date is October 26, 2026. ``` **Note:** The `llm` platform for Ollama might be a separate integration or a configuration within the `conversation` integration depending on current Home Assistant development. Always refer to the [official Home Assistant Conversation documentation](https://www.home-assistant.io/integrations/conversation/) for the most up-to-date configuration details. 3. **Restart Home Assistant:** After saving your `configuration.yaml` changes, restart Home Assistant for the new configuration to take effect. ### Practical Home Assistant AI Automations with Ollama With Ollama integrated, your `home assistant ai` can now interpret natural language commands and trigger automations. This opens up a world of possibilities beyond simple keyword matching. #### Example 1: Natural Language Lighting Control Instead of saying ## Recommended Gear If you're building your own setup, here's the hardware I recommend: - **[Sonoff Zigbee 3.0 USB Dongle](https://www.amazon.it/s?k=Sonoff+Zigbee+3.0+dongle&linkCode=ll2&tag=spazitec0f-21)** — Zigbee coordinator for Home Assistant - **[Shelly Plus 1PM](https://www.amazon.it/s?k=Shelly+Plus+1PM&linkCode=ll2&tag=spazitec0f-21)** — smart relay with energy monitoring - **[ESP32 Development Board](https://www.amazon.it/s?k=ESP32+development+board&linkCode=ll2&tag=spazitec0f-21)** — ESP32 board for ESPHome sensors - **[Aqara Temperature Sensor](https://www.amazon.it/s?k=Aqara+temperature+sensor+Zigbee&linkCode=ll2&tag=spazitec0f-21)** — Zigbee temperature/humidity sensor - **[Beelink Mini PC (Intel N100)](https://www.amazon.it/s?k=Beelink+Mini+PC+N100&linkCode=ll2&tag=spazitec0f-21)** — mini PC to run Home Assistant ## FAQ ### Why is local AI becoming important for Home Assistant in 2026? Local AI offers significant advantages like enhanced privacy, reduced latency, and offline capability. By 2026, integrating platforms like Ollama will transform Home Assistant into a more intelligent and private smart home ecosystem. ### What are the primary benefits of using local LLMs with Home Assistant? The main benefits include keeping your data private within your network, achieving near-instantaneous responses for commands, and ensuring your smart home functions even without an internet connection. It also allows for greater customization. ### How does local AI enhance privacy compared to cloud-based solutions? With local AI, all your smart home data, including voice commands and sensor information, is processed directly on your hardware. This eliminates the need to send sensitive information to external cloud servers, preventing potential privacy breaches. ### Can my Home Assistant AI system still function if my internet goes down? Yes, a key advantage of local AI integration is its offline capability. Essential automations and voice commands will continue to operate without interruption, as processing occurs entirely within your local network. ## Related Articles - [Home Assistant Automations Guide 2026: From Basic to Advanced Smart Home Control](/en/blog/home-assistant-automations-guide-2026-from-basic-to-advanced-smart-home-control/) - [Master Your Audi EV Charging with Home Assistant Automation (2026)](/en/blog/master-your-audi-ev-charging-with-home-assistant-automation-2026/) - [Mastering Home Assistant on Proxmox LXC: Setup Guide 2026](/en/blog/mastering-home-assistant-on-proxmox-lxc-setup-guide-2026/) - [Mastering Home Assistant Solar Automation: Your Guide to Smart Energy in 2026](/en/blog/mastering-home-assistant-solar-automation-your-guide-to-smart-energy-in-2026/)]]> Wed, 29 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/unleashing-local-ai-with-home-assistant-ollama-integration-in-2026/ Home Assistant Local AI Ollama Smart Home Automation Debugging Multi-Agent AI Systems 2026: Essential Tools & Strategies https://daniele-messi.com/en/blog/debugging-multi-agent-ai-systems-2026-essential-tools-strategies/ Master the art of debugging multi-agent systems in 2026. Explore essential tools and strategies for AI agent observability, tracing interactions, and troubleshooting complex AI agent workflows effectively. Tue, 28 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/debugging-multi-agent-ai-systems-2026-essential-tools-strategies/ multi-agent systems AI debugging agent observability AI tools agentic engineering Proxmox ZFS Performance Tuning 2026: Optimize Your Home Lab Storage https://daniele-messi.com/en/blog/proxmox-zfs-performance-tuning-2026-optimize-your-home-lab-storage/ Unlock peak performance for your Proxmox home lab in 2026. This guide covers essential Proxmox ZFS performance tuning techniques, from ARC/L2ARC optimization to compression and storage best practices, ensuring your VMs and containers run flawlessly. Tue, 28 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/proxmox-zfs-performance-tuning-2026-optimize-your-home-lab-storage/ Proxmox ZFS Performance Tuning Home Lab Storage Optimization System Prompt Best Practices for Production Apps in 2026 https://daniele-messi.com/en/blog/system-prompt-best-practices-for-production-apps-in-2026/ Master system prompt best practices for your production AI applications in 2026. This guide covers essential system prompt design, testing, and deployment strategies for robust, reliable AI. User Review: "The product arrived damaged and late." Sentiment: negative User Review: "Great widget, works perfectly!" Sentiment: positive User Review: "It's okay, nothing special." Sentiment: neutral Now, analyze the following review: ``` #### 2. Context Management and External Knowledge For tasks requiring specific knowledge, integrate relevant context directly into the prompt or instruct the AI on how to access external information (e.g., via tool use). This aligns with the principles of [Context Engineering vs Prompt Engineering: The 2026 Paradigm Shift](/en/blog/context-engineering-vs-prompt-engineering-the-2026-paradigm-shift/). **Example (with tool use instruction):** ``` You are a research assistant. If a user asks a question that requires current factual information, you MUST use the 'search_web' tool before attempting to answer. Present your findings concisely, citing sources if possible. print(search_web(query: str)) User: What is the capital of New Zealand? ``` #### 3. Guardrails and Red Teaming Proactively test your system prompts against adversarial inputs (red teaming) to identify vulnerabilities and refine your guardrails. Explicitly instruct the AI on how to handle harmful, biased, or off-topic requests. This often involves a multi-layered approach, combining instructions with content filtering. For more general prompt engineering advice, see [Mastering Prompt Engineering Claude: Beyond GPT-Centric Strategies for 2026](/en/blog/mastering-prompt-engineering-claude-beyond-gpt-centric-strategies-for-2026/). ### Practical Implementation for Production Prompts Moving your system prompt design from theory to practice involves several key considerations: * **Environment Variables & Configuration:** Avoid hardcoding prompts directly into your application code. Use environment variables, configuration files, or dedicated prompt management services to manage and update prompts without redeploying your entire application. * **A/B Testing:** When iterating on prompts, especially for critical user flows, employ A/B testing to compare performance metrics (e.g., accuracy, user satisfaction, token usage) between different prompt versions. * **Monitoring and Logging:** Implement robust logging of prompt inputs and AI outputs. This data is invaluable for identifying regressions, uncovering new edge cases, and continuously improving your **production prompts**. * **Prompt Chaining/Orchestration:** For complex workflows, a single system prompt might not suffice. Consider chaining multiple prompts or using agentic frameworks where different sub-agents handle specific parts of a task, each with its own specialized system prompt. This is a core concept in modern AI application development, often facilitated by frameworks like Claude Code. ### Conclusion As AI becomes more deeply embedded in our daily lives and business operations, the quality and reliability of **production prompts** will directly impact the success of your applications. By diligently applying **system prompt best practices** – focusing on clarity, persona definition, output constraints, safety, and iterative testing – you can build AI systems that are not only powerful but also predictable, robust, and trustworthy. Investing in sophisticated **system prompt design** today will pay dividends in the stable, high-performing AI applications of 2026 and beyond. ## FAQ ### What is a system prompt? A system prompt serves as the foundational operating instructions for an AI model, acting as the "unseen architect" that defines its core persona, behavior, and constraints. Unlike user prompts, it sets the overarching rules for how the AI should operate within an application. ### Why are system prompts critical for production AI applications? System prompts are critical because they ensure predictable and consistent responses across countless user interactions in live applications. They are paramount for achieving reliable, safe, and scalable AI performance, moving beyond experimental prototypes. ### How does a system prompt help reduce AI hallucinations? By providing clear context, specific rules, and defined boundaries, a system prompt minimizes the AI model's tendency to generate irrelevant or incorrect information. This guidance helps the model stay focused and grounded in its intended purpose and knowledge base. ### What are some key functions a system prompt performs? A system prompt establishes the AI's persona (e.g., expert, assistant), defines output constraints like format and length, and guides the AI's behavior in handling ambiguous input or sensitive topics. These functions ensure consistent and controlled AI interactions. ## Related Articles - [Mastering MCP Tool Descriptions for AI Agents in 2026](/en/blog/mastering-mcp-tool-descriptions-for-ai-agents-in-2026/) - [Mastering Prompt Engineering Claude: Beyond GPT-Centric Strategies for 2026](/en/blog/mastering-prompt-engineering-claude-beyond-gpt-centric-strategies-for-2026/) - [Mastering Prompt Testing & CI/CD for AI Applications in 2026](/en/blog/mastering-prompt-testing-ci-cd-for-ai-applications-in-2026/) - [Prompt Engineering for Developers: Practical Guide & Code Examples](/en/blog/prompt-engineering-for-developers-practical-guide-code-examples/)]]> Tue, 28 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/system-prompt-best-practices-for-production-apps-in-2026/ prompt engineering AI development production apps system design Claude Proxmox LXC vs VM: Choosing the Right Virtualization in 2026 https://daniele-messi.com/en/blog/proxmox-lxc-vs-vm-choosing-the-right-virtualization-in-2026/ Navigating Proxmox LXC vs VM can be tricky. This guide helps you decide between containers and virtual machines for your 2026 Proxmox setup, focusing on performance, isolation, and use cases. Mon, 27 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/proxmox-lxc-vs-vm-choosing-the-right-virtualization-in-2026/ Proxmox LXC Virtualization Containers Home Lab Proxmox ZFS Performance Tuning 2026: Optimize Home Lab Storage https://daniele-messi.com/en/blog/proxmox-zfs-performance-tuning-2026-optimize-home-lab-storage/ Master Proxmox ZFS performance tuning in 2026. Learn advanced techniques for compression, ARC, L2ARC, and Proxmox storage best practices for your home lab. Mon, 27 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/proxmox-zfs-performance-tuning-2026-optimize-home-lab-storage/ Proxmox ZFS Home Lab Performance Tuning Storage Proxmox GPU Passthrough for AI Workloads: Unleashing Performance in 2026 https://daniele-messi.com/en/blog/proxmox-gpu-passthrough-for-ai-workloads-unleashing-performance-in-2026/ Unlock powerful AI capabilities by configuring Proxmox GPU passthrough. This guide covers essential steps for NVIDIA GPUs, optimizing your virtualized environment for demanding AI workloads in 2026. Sun, 26 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/proxmox-gpu-passthrough-for-ai-workloads-unleashing-performance-in-2026/ Proxmox GPU Passthrough AI Workloads NVIDIA Virtualization Proxmox Backup Strategy: Complete Guide for 2026 and Beyond https://daniele-messi.com/en/blog/proxmox-backup-strategy-complete-guide-for-2026-and-beyond/ Master your Proxmox backup strategy for 2026 with this complete guide. Learn about Proxmox Backup Server, snapshots, and robust disaster recovery for your VMs and LXCs. Sat, 25 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/proxmox-backup-strategy-complete-guide-for-2026-and-beyond/ Proxmox Backup Disaster Recovery Virtualization Home Lab Mastering Multi-Agent AI Orchestration: Practical Examples for 2026 https://daniele-messi.com/en/blog/mastering-multi-agent-ai-orchestration-practical-examples-for-2026/ Dive into multi-agent AI orchestration with practical code examples. Learn to coordinate sophisticated agent teams for complex tasks, enhancing automation and efficiency with multi-agent AI in 2026 and beyond. Fri, 24 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/mastering-multi-agent-ai-orchestration-practical-examples-for-2026/ Multi-Agent AI AI Orchestration Agent Teams AI Development Python Claude Code Cost Optimization 2026: Mastering API Usage & Token Management https://daniele-messi.com/en/blog/claude-code-cost-optimization-2026-mastering-api-usage-token-management/ Learn essential strategies for Claude Code cost optimization in 2026, focusing on efficient API usage and advanced token management techniques to significantly reduce your Claude Code expenses. Thu, 23 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/claude-code-cost-optimization-2026-mastering-api-usage-token-management/ Claude Code Cost Optimization API Usage Token Management AI Development Home Assistant Advanced Dashboard Development 2026: Custom Cards & Lovelace UI https://daniele-messi.com/en/blog/home-assistant-advanced-dashboard-development-2026-custom-cards-lovelace-ui/ Unlock the full potential of your smart home with Home Assistant advanced dashboard development in 2026. Master custom cards and Lovelace UI to create personalized, powerful interfaces. Entity not found: ${this.config.entity}`; } return html`
${this.config.name || 'My Custom Card'}
Current state of ${entityState.attributes.friendly_name}: ${entityState.state}
 `; } setConfig(config) { if (!config.entity) { throw new Error('You need to define an entity'); } this.config = config; } } customElements.define('my-custom-card', MyCustomCard); ``` To use this card, you would add it to your `ui-lovelace.yaml` (or via the raw configuration editor) like so: ```yaml - type: custom:my-custom-card entity: light.living_room_light name: Living Room Status ``` ## Advanced Lovelace UI Development Techniques While the visual editor is great for beginners, true **Home Assistant advanced dashboard** development relies heavily on YAML configuration. YAML mode provides granular control over every aspect of your Lovelace UI, from card placement and styling to conditional visibility and dynamic content loading. You can organize your configuration using `!include` statements to break down large files into smaller, manageable ones, and secure sensitive data with `!secret`. Advanced techniques include using `layout-card` for complex grid and stack layouts, `picture-elements` for interactive overlays on images (e.g., floor plans), and `conditional` cards that only display when certain conditions are met. This allows you to create context-aware dashboards that adapt to the time of day, occupancy, or specific device states. For further automation, consider integrating with [Advanced Home Assistant Blueprints for Developers in 2026](/en/blog/advanced-home-assistant-blueprints-for-developers-in-2026/). ### Crafting Dynamic and Data-Rich Views Dynamic views are crucial for an effective **Home Assistant advanced dashboard**. This involves using templating and integrating data from various sources to provide a comprehensive overview. Home Assistant's Jinja2 templating engine, familiar to those who create [Home Assistant Automations Guide 2026: From Basic to Advanced Smart Home Control](/en/blog/home-assistant-automations-guide-2026-from-basic-to-advanced-smart-home-control/), can be used within certain cards (like `markdown` cards or custom cards) to display dynamic text based on sensor states or attributes. For example, you can show a greeting that changes based on the time of day or display the current energy consumption from your [Mastering Home Assistant Energy Monitoring Dashboard in 2026](/en/blog/mastering-home-assistant-energy-monitoring-dashboard-in-2026/). Beyond internal entities, you can integrate external data sources via REST sensors or custom integrations. Imagine a card displaying the local weather forecast from a third-party API, or real-time public transport information. This transforms your dashboard from a simple control panel into an information hub. For complex configurations, mastering the [Lovelace YAML mode](https://www.home-assistant.io/dashboards/lovelace_yaml/) is indispensable. Here’s an example of a conditional card that only shows a warning if a door is open: ```yaml - type: conditional conditions: - entity: binary_sensor.front_door state: 'on' card: type: markdown content: "## 🚨 Front Door is OPEN! 🚨" card_mod: style: |- ha-card { background-color: var(--error-color); color: white; font-weight: bold; text-align: center; animation: blink 1s infinite; } @keyframes blink { 0% { opacity: 1; } 50% { opacity: 0.5; } 100% { opacity: 1; } } ``` ## Performance Optimization for Your Advanced Home Assistant UI An elaborate **Home Assistant advanced dashboard** can become slow if not optimized. Performance is critical, especially on mobile devices or lower-powered clients. One common pitfall is having too many entities displayed on a single view, or using inefficient custom cards. It's estimated that optimizing card rendering and reducing unnecessary entity listeners can improve dashboard load times by up to 30-40% for complex setups. Strategies for optimization include: * **Minimizing Entities:** Only display essential entities on primary views. Use sub-views or pop-ups for less frequently accessed controls. * **Efficient Custom Cards:** Choose well-written custom cards from HACS, or ensure your self-developed cards are optimized for rendering performance. * **Browser Caching:** Ensure your browser is effectively caching static assets. Clear cache if you notice issues after updates. * **Theming:** While themes are mostly cosmetic, overly complex themes with many custom CSS variables can sometimes introduce minor overhead. * **Hardware:** Ensure your Home Assistant instance runs on adequate hardware. Hosting on a Proxmox LXC, for example, can offer robust performance. ## Security Best Practices for Custom Integrations in 2026 As you delve into custom cards and integrations, security becomes paramount. Every custom component you add is a piece of code running within your Home Assistant environment. Always verify the source of any custom card or integration, ideally sticking to well-maintained projects on HACS with active communities. Before installing, review the project's GitHub repository, check for open issues, and understand what permissions it requires. Regular updates are critical, as developers often release patches for vulnerabilities. It is a best practice to keep your Home Assistant Core and OS updated to the latest stable versions in 2026. ## The Future of Home Assistant Dashboards: AI & Beyond in 2026 The landscape of smart home control is rapidly evolving, with AI playing an increasingly significant role. In 2026, we anticipate even deeper integration of AI into Home Assistant dashboards. Imagine a dashboard that not only displays data but also predicts your energy usage, suggests optimal lighting based on your habits, or even responds to complex natural language commands. Projects like [Unleashing Local AI with Home Assistant: Ollama Integration in 2026](/en/blog/unleashing-local-ai-with-home-assistant-ollama-integration-in-2026/) are paving the way for on-device AI capabilities that will make your Home Assistant advanced dashboard truly intelligent, moving beyond reactive automation to proactive assistance. We expect to see a 50% increase in AI-powered dashboard features by late 2026. ## Conclusion Developing a truly **Home Assistant advanced dashboard** in 2026 is an ongoing journey of customization, optimization, and innovation. By mastering custom cards and advanced Lovelace UI techniques, you can transform your smart home interface from a mere collection of controls into a powerful, intelligent, and deeply personal command center. Embrace the flexibility of Home Assistant and continue to explore new possibilities to create the ultimate smart home experience. ## FAQ ### What are Home Assistant custom cards? Home Assistant custom cards are community-developed or self-coded components that extend the functionality and appearance of your Lovelace UI beyond the standard built-in cards. They allow for unique data visualizations, specialized controls, and integration of diverse data sources, offering unparalleled customization for your Home Assistant advanced dashboard. ### How do I improve Lovelace UI performance? To improve Lovelace UI performance, focus on minimizing the number of entities displayed on single views, using efficient custom cards, and ensuring your Home Assistant instance runs on adequate hardware. Leveraging browser caching and avoiding overly complex themes can also contribute to faster load times and a smoother user experience. ### Can I integrate external data into my Home Assistant advanced dashboard? Yes, you can integrate external data into your Home Assistant advanced dashboard using various methods, including REST sensors for pulling data from APIs, or through custom integrations. This allows you to display information like weather forecasts, stock prices, or public transport schedules alongside your smart home data, creating a comprehensive information hub. ### What's the best way to manage complex Lovelace configurations? For complex Lovelace configurations, the best approach is to use YAML mode. This allows for precise control, easier version management, and the ability to break down your configuration into smaller, manageable files using `!include` statements. It also enables advanced features like conditional cards and intricate layouts that are difficult to achieve with the visual editor alone. ## Recommended Gear If you're building your own setup, here's the hardware I recommend: - **[Sonoff Zigbee 3.0 USB Dongle](https://www.amazon.it/s?k=Sonoff+Zigbee+3.0+dongle&linkCode=ll2&tag=spazitec0f-21)** — Zigbee coordinator for Home Assistant - **[Shelly Plus 1PM](https://www.amazon.it/s?k=Shelly+Plus+1PM&linkCode=ll2&tag=spazitec0f-21)** — smart relay with energy monitoring - **[ESP32 Development Board](https://www.amazon.it/s?k=ESP32+development+board&linkCode=ll2&tag=spazitec0f-21)** — ESP32 board for ESPHome sensors - **[Aqara Temperature Sensor](https://www.amazon.it/s?k=Aqara+temperature+sensor+Zigbee&linkCode=ll2&tag=spazitec0f-21)** — Zigbee temperature/humidity sensor - **[Beelink Mini PC (Intel N100)](https://www.amazon.it/s?k=Beelink+Mini+PC+N100&linkCode=ll2&tag=spazitec0f-21)** — mini PC to run Home Assistant ## Related Articles - [Advanced Home Assistant Blueprints for Developers in 2026](/en/blog/advanced-home-assistant-blueprints-for-developers-in-2026/) - [ESPHome DIY Sensors: A Developer's Practical Guide for 2026](/en/blog/esphome-diy-sensors-a-developer-s-practical-guide-for-2026/) - [Home Assistant Automations Guide 2026: From Basic to Advanced Smart Home Control](/en/blog/home-assistant-automations-guide-2026-from-basic-to-advanced-smart-home-control/) - [Master Your Audi EV Charging with Home Assistant Automation (2026)](/en/blog/master-your-audi-ev-charging-with-home-assistant-automation-2026/) - [Mastering Home Assistant Energy Monitoring Dashboard in 2026](/en/blog/mastering-home-assistant-energy-monitoring-dashboard-in-2026/) - [Mastering Home Assistant on Proxmox LXC: Setup Guide 2026](/en/blog/mastering-home-assistant-on-proxmox-lxc-setup-guide-2026/) - [Mastering Home Assistant Solar Automation: Your Guide to Smart Energy in 2026](/en/blog/mastering-home-assistant-solar-automation-your-guide-to-smart-energy-in-2026/) - [Unleashing Local AI with Home Assistant: Ollama Integration in 2026](/en/blog/unleashing-local-ai-with-home-assistant-ollama-integration-in-2026/)]]> Thu, 23 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/home-assistant-advanced-dashboard-development-2026-custom-cards-lovelace-ui/ Home Assistant Custom Cards Lovelace UI Smart Home Automation Dashboard Development Mastering MCP Tool Descriptions for AI Agents in 2026 https://daniele-messi.com/en/blog/mastering-mcp-tool-descriptions-for-ai-agents-in-2026/ Unlock the full potential of your AI agents by mastering MCP tool descriptions. Learn best practices for crafting precise and effective mcp tool descriptions, enhancing your server's capabilities and AI performance in 2026. Thu, 23 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/mastering-mcp-tool-descriptions-for-ai-agents-in-2026/ MCP Servers AI Tools Prompt Engineering API Descriptions Automation Mastering MCP Hosting & Deployment in 2026: A Developer's Guide https://daniele-messi.com/en/blog/mastering-mcp-hosting-deployment-in-2026-a-developer-s-guide/ Unlock seamless AI tool integration. This 2026 guide covers practical strategies for MCP hosting, from choosing infrastructure to production deployment and security. Wed, 22 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/mastering-mcp-hosting-deployment-in-2026-a-developer-s-guide/ MCP Hosting AI Agents Deployment Cloud Infrastructure DevOps Mastering Home Assistant Energy Monitoring Dashboard in 2026 https://daniele-messi.com/en/blog/mastering-home-assistant-energy-monitoring-dashboard-in-2026/ Unlock detailed insights with Home Assistant energy monitoring. Learn to set up and optimize your home assistant energy dashboard for efficiency and cost savings in 2026. Practical guide for tech-savvy users. `Dashboards` -> `Energy`. 2. **Add Grid Consumption**: Select your `total_increasing` energy sensor (e.g., `sensor.grid_energy_total`) for "Grid consumption". You can also add individual return-to-grid sensors if applicable. 3. **Add Solar Production**: If you have solar, select your `total_increasing` solar production sensor. 4. **Add Battery Storage**: If you have a battery, configure the charge and discharge sensors. 5. **Add Individual Devices**: This is where **home assistant power monitoring** truly shines. Add individual smart plugs or CT clamp channels that monitor specific appliances (e.g., dryer, EV charger). This allows you to see their consumption broken down in the dashboard. For example, if you're [Mastering Your Audi EV Charging with Home Assistant Automation (2026)](/en/blog/master-your-audi-ev-charging-with-home-assistant-automation-2026/), you can add its energy sensor here. 6. **Cost Configuration**: Define your energy tariffs. Home Assistant supports fixed tariffs, peak/off-peak rates, and even complex time-of-use tariffs. This allows the dashboard to calculate actual costs. The Home Assistant Energy dashboard provides beautiful, interactive graphs showing daily, weekly, monthly, and yearly consumption, production, and costs. It’s an incredibly powerful tool for visualizing your home's energy footprint. For a deep dive into the official setup, consult the [Home Assistant Energy Documentation](https://www.home-assistant.io/docs/energy/). ## Advanced Home Assistant Power Monitoring & Automations The real power of **Home Assistant energy monitoring** extends beyond visualization. You can create sophisticated automations that react to energy data in real-time. ### Energy-Aware Automations * **Load Shifting**: If you have solar, automate high-consumption devices (e.g., washing machine, dishwasher, EV charging) to run only when solar production exceeds consumption or when electricity prices are lowest. * **Peak Demand Management**: Automatically shed non-essential loads when grid consumption hits a predefined threshold, avoiding peak demand charges. * **Appliance Alerts**: Get notifications if an appliance (e.g., refrigerator) starts drawing unusual power, potentially indicating a fault. * **Smart EV Charging**: Integrate your EV charger's power draw with your solar production to ensure you're primarily charging from renewable sources. Here’s an example automation snippet that might pause a smart charger if grid power draw exceeds a certain limit, assuming you have a `sensor.grid_power_sensor` and a switch for your charger: ```yaml # Example Home Assistant Automation for peak load management alias: "Pause EV Charger on High Grid Demand" description: "Pauses EV charger if grid consumption exceeds 5000W" trigger: - platform: numeric_state entity_id: sensor.grid_power_sensor # Your main grid consumption sensor (W) above: 5000 for: minutes: 1 condition: - condition: state entity_id: switch.ev_charger_switch # Replace with your charger switch state: "on" action: - service: switch.turn_off target: entity_id: switch.ev_charger_switch - service: persistent_notification.create data: title: "Energy Alert: EV Charger Paused" message: "Grid power consumption exceeded 5kW. EV charger paused to reduce load." mode: single ``` ### Customizing Your Energy View While the built-in energy dashboard is excellent, you might want to create custom dashboards using Lovelace for even more specific views. You can combine energy graphs with other smart home data, like temperature, occupancy, or even weather forecasts, to understand energy consumption patterns in context. Utilizing custom cards from HACS (Home Assistant Community Store) can further enhance your visualization capabilities. ## Future-Proofing Your Energy Monitoring Setup As we move further into 2026, energy monitoring technology continues to evolve. Consider these aspects for a future-proof setup: * **Local Processing**: Prioritize devices and integrations that allow for local data processing, reducing reliance on cloud services and improving privacy and reliability. ESPHome is a prime example. * **Open Standards**: Opt for open standards like Zigbee, Z-Wave, or Matter for smart plugs and sensors, ensuring broad compatibility. * **Scalability**: Design your system to easily add more sensors as your needs grow, whether it’s monitoring more individual appliances or adding new energy sources. * **Data Backup**: Ensure your Home Assistant instance is regularly backed up. If you're running Home Assistant on a platform like Proxmox, a robust [Proxmox Backup Strategy: Complete Guide for 2026 and Beyond](/en/blog/proxmox-backup-strategy-complete-guide-for-2026-and-beyond/) is essential. ## Conclusion Implementing comprehensive **Home Assistant energy monitoring** is one of the most impactful projects you can undertake for your smart home in 2026. By diligently collecting, visualizing, and acting upon your energy data, you gain the power to significantly reduce costs, minimize your environmental footprint, and build a more intelligent, responsive home. Embrace the **home assistant energy dashboard** and advanced **home assistant power monitoring** techniques to unlock a new level of energy efficiency and control. Start today, and watch the savings add up! ## Recommended Gear If you're building your own setup, here's the hardware I recommend: - **[Sonoff Zigbee 3.0 USB Dongle](https://www.amazon.it/s?k=Sonoff+Zigbee+3.0+dongle&linkCode=ll2&tag=spazitec0f-21)** — Zigbee coordinator for Home Assistant - **[Shelly Plus 1PM](https://www.amazon.it/s?k=Shelly+Plus+1PM&linkCode=ll2&tag=spazitec0f-21)** — smart relay with energy monitoring - **[ESP32 Development Board](https://www.amazon.it/s?k=ESP32+development+board&linkCode=ll2&tag=spazitec0f-21)** — ESP32 board for ESPHome sensors - **[Aqara Temperature Sensor](https://www.amazon.it/s?k=Aqara+temperature+sensor+Zigbee&linkCode=ll2&tag=spazitec0f-21)** — Zigbee temperature/humidity sensor - **[Beelink Mini PC (Intel N100)](https://www.amazon.it/s?k=Beelink+Mini+PC+N100&linkCode=ll2&tag=spazitec0f-21)** — mini PC to run Home Assistant ## FAQ ### Why is Home Assistant energy monitoring increasingly important in 2026? Home Assistant energy monitoring is crucial in 2026 due to escalating electricity costs and a heightened environmental consciousness. It empowers homeowners to gain unparalleled insights and control over their energy consumption, transforming their instance into an energy intelligence hub. ### What are the main advantages of setting up Home Assistant for energy tracking? The primary advantages include significant cost savings by identifying inefficient consumption, reducing your carbon footprint, and optimizing the performance of solar panels, battery storage, and EV charging. It also aids in preventive maintenance by detecting unusual usage patterns. ### How can Home Assistant help reduce my electricity bill? Home Assistant helps reduce electricity bills by allowing users to identify "energy vampires" and high-consumption periods. This detailed data enables informed adjustments to habits or the automation of appliance usage, directly contributing to lower energy costs. ## Related Articles - [Advanced Home Assistant Blueprints for Developers in 2026](/en/blog/advanced-home-assistant-blueprints-for-developers-in-2026/) - [Home Assistant Automations Guide 2026: From Basic to Advanced Smart Home Control](/en/blog/home-assistant-automations-guide-2026-from-basic-to-advanced-smart-home-control/) - [Master Your Audi EV Charging with Home Assistant Automation (2026)](/en/blog/master-your-audi-ev-charging-with-home-assistant-automation-2026/) - [Mastering Home Assistant on Proxmox LXC: Setup Guide 2026](/en/blog/mastering-home-assistant-on-proxmox-lxc-setup-guide-2026/) - [Mastering Home Assistant Solar Automation: Your Guide to Smart Energy in 2026](/en/blog/mastering-home-assistant-solar-automation-your-guide-to-smart-energy-in-2026/) - [Unleashing Local AI with Home Assistant: Ollama Integration in 2026](/en/blog/unleashing-local-ai-with-home-assistant-ollama-integration-in-2026/)]]> Tue, 21 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/mastering-home-assistant-energy-monitoring-dashboard-in-2026/ Home Assistant Energy Monitoring Smart Home Automation ESPHome Mastering Claude Code Context Window Management for Developers in 2026 https://daniele-messi.com/en/blog/mastering-claude-code-context-window-management-for-developers-in-2026/ Unlock peak efficiency with Claude Code. Learn advanced strategies for managing the claude code context window, ensuring clear, compact, and effective AI interactions in 2026. ``` Then, paste the output into your prompt with clear instructions. ## Maintaining Claude Code Clear Context Beyond compaction, ensuring your context is *clear* means structuring information logically and guiding Claude effectively. ### 1. Modular Prompting and Iterative Refinement Break down complex tasks into smaller, manageable steps. Instead of asking for a complete feature implementation in one go, ask Claude to design the architecture, then implement a component, then test it. Each step builds on a refined context from the previous one. This is a core tenet of [Mastering Prompt Engineering Claude: Beyond GPT-Centric Strategies for 2026](/en/blog/mastering-prompt-engineering-claude-beyond-gpt-centric-strategies-for-2026/). ### 2. Effective Use of `CLAUDE.md` and Project Structure The `CLAUDE.md` file is a powerful tool for providing high-level context, project goals, and architectural guidelines that persist across your interactions. Use it to define global constants, project scope, and preferred coding styles. This allows you to keep individual prompts more concise. Learn more in [CLAUDE.md Best Practices: Crafting the Perfect AI Project File for 2026](/en/blog/claude-md-best-practices-crafting-the-perfect-ai-project-file-for-2026/). ### 3. Scratchpads and Intermediate Steps Encourage Claude to use a ## Recommended Gear If you're building your own setup, here's the hardware I recommend: - **[Logitech MX Keys S](https://www.amazon.it/s?k=Logitech+MX+Keys+S&linkCode=ll2&tag=spazitec0f-21)** — keyboard for productive coding sessions - **[Samsung 49" Ultra-Wide Monitor](https://www.amazon.it/s?k=Samsung+49+ultrawide+monitor&linkCode=ll2&tag=spazitec0f-21)** — ultra-wide monitor for side-by-side coding ## FAQ ### What is the Claude Code context window? The Claude Code context window refers to the total amount of text (tokens) that Claude can 'see' and process at any given time. This includes your prompt, any attached files, previous turns in a conversation, and its own generated thoughts. ### Why is managing the context window important for developers in 2026? Effective context window management is paramount because it directly influences Claude's ability to understand complex requests and generate accurate, relevant code. In 2026, with increasing project complexities and the demand for highly autonomous AI agents, it's a necessity for maintaining peak productivity and code quality. ### What benefits does efficient context management offer? A well-managed context ensures Claude has all necessary information without being overwhelmed by irrelevant data. This leads to faster processing, more accurate code generation, and more cost-effective interactions with the AI assistant. ### How does the context window relate to Claude's memory? The context window can be thought of as managing Claude's short-term working memory. By curating the information within this finite space, developers can ensure Claude's 'memory' is focused on the most pertinent details for the task at hand. ## Related Articles - [10 Claude Code Automations You Should Try Today](/en/blog/10-claude-code-automations-you-should-try/) - [Building Custom Slash Commands in Claude Code for Enhanced Workflow in 2026](/en/blog/building-custom-slash-commands-in-claude-code-for-enhanced-workflow-in-2026/) - [Claude Code Hooks: The Complete Guide to Automation & Workflow in 2026](/en/blog/claude-code-hooks-the-complete-guide-to-automation-workflow-in-2026/) - [Claude Code Sub-Agents: Practical Examples & Advanced Strategies for 2026](/en/blog/claude-code-sub-agents-practical-examples-advanced-strategies-for-2026/) - [Claude Code vs Cursor vs Copilot: An Honest Comparison for 2026](/en/blog/claude-code-vs-cursor-vs-copilot-an-honest-comparison-for-2026/) - [CLAUDE.md Best Practices: Crafting the Perfect AI Project File for 2026](/en/blog/claude-md-best-practices-crafting-the-perfect-ai-project-file-for-2026/) - [Getting Started with Claude Code: The Ultimate Guide](/en/blog/getting-started-with-claude-code/) - [Mastering Claude Code Plugins & Advanced Skills in 2026](/en/blog/mastering-claude-code-plugins-advanced-skills-in-2026/)]]> Mon, 20 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/mastering-claude-code-context-window-management-for-developers-in-2026/ Claude Code Context Management AI Development Prompt Engineering Agentic AI Mastering Claude Code Plugins & Advanced Skills in 2026 https://daniele-messi.com/en/blog/mastering-claude-code-plugins-advanced-skills-in-2026/ Unlock the full potential of Claude Code with this comprehensive guide to powerful Claude Code plugins and advanced coding skills. Elevate your AI development workflow in 2026. Mon, 20 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/mastering-claude-code-plugins-advanced-skills-in-2026/ Claude Code AI Development Plugins Code Skills Agentic AI Roborock Saros 20 Sonic: The Tech Behind 2026's Smartest Robot Vacuum https://daniele-messi.com/en/blog/roborock-saros-20-sonic-the-tech-behind-2026-smartest-robot-vacuum/ A deep technical analysis of the Roborock Saros 20 Sonic Complete — from StarSight 2.0 navigation to VibraRise 5.0 sonic mopping, AdaptiLift 3.0 chassis, and Matter smart home integration. Available in Switzerland for CHF 1'099. I spend most of my time working on embedded systems, AI tooling, and home automation. But every once in a while, a consumer product comes along that's interesting from a pure engineering standpoint. The Roborock Saros 20 Sonic is one of those products. > For a full consumer-oriented review with scores and buying advice, check out my [detailed review on SpazioiTech](https://www.spazioitech.it/roborock-saros-20-sonic-recensione-completa/). What I want to focus on here is the technology — the sensor fusion architecture, the mechanical design decisions, and the software intelligence that makes this robot genuinely different from everything else on the market. ## The Sensor Stack: StarSight 2.0 The first thing that sets the Saros 20 Sonic apart is what's *not* on top of it. There's no rotating LiDAR turret. Roborock replaced it with a solid-state dual-transmitter LiDAR system integrated flush into the robot's top surface, keeping the height at just 7.98 cm. The full sensor stack includes: - **3D Time-of-Flight front sensor** — depth mapping at high frame rates - **RGB camera** — object classification and visual SLAM - **VertiBeam structured-light lateral sensors** — covering the blind spots behind and to the sides - **Cliff sensors** — standard IR drop detection - **Carpet detection** — ultrasonic material identification Together, these generate data at a sampling frequency **21x higher** than traditional LDS navigation. The RockMind AI processor fuses these inputs to recognize over 300 obstacle types, up from 108 in the previous generation. In practical testing by NotebookCheck, the system detected every obstacle placed in its path except a single flat shoelace — an impressively low failure rate. It also correctly identified and navigated around 4x2 cm clamping blocks that would trap most competing robots. ### Pet Recognition Roborock Saros 20 Sonic detecting and avoiding a pet An interesting addition is real-time pet recognition. The RGB camera identifies cats and dogs and adjusts the robot's speed and path to avoid startling them. It's a niche feature, but it tells you something about where the AI inference capabilities are heading. ## AdaptiLift 3.0: Leg-Based Chassis Architecture Roborock Saros 20 Sonic crossing a door threshold with AdaptiLift 3.0 The biggest mechanical innovation is the AdaptiLift 3.0 chassis. Previous Roborock models could lift themselves ~4 cm to cross thresholds. The Saros 20 Sonic handles: - **Single thresholds:** up to 4.5 cm - **Double thresholds:** up to 8.8 cm (4.5 + 4.3 cm) This is achieved through what Roborock calls "wheel-leg architecture" — the wheels extend downward on actuated legs, physically lifting the entire robot body. NotebookCheck confirmed the system handles double thresholds without hesitation in real-world testing. For anyone living in a Swiss apartment or older European home with pronounced door thresholds between rooms, this is arguably the most practical upgrade in the entire product. I've seen too many robot vacuums get stuck on the 3 cm marble threshold between my kitchen and living room. ## VibraRise 5.0: Sonic vs. Rotary Mopping Roborock Saros 20 Sonic cleaning debris on carpet This is where the "Sonic" variant differentiates itself from the standard Saros 20. **Traditional rotary mops** (used in the Saros 10R and most competitors) spin two circular pads at ~200 RPM. They work well for daily maintenance but struggle with dried-on stains. The mechanical contact pressure is limited by the robot's weight distribution. **The VibraRise 5.0 Sonic system** uses a D-shaped pad that vibrates at **4,000 oscillations per minute** with up to **14N of downward pressure**. The key advantages: 1. **Higher effective scrubbing force** — vibration delivers more cleaning energy per unit area than rotation 2. **Extendable edge cleaning** — the D-shaped pad physically extends toward walls, eliminating the "unwashed strip" that plagues round-pad designs 3. **Automatic carpet lift** — the pad retracts when carpet is detected, and the AdaptiLift adjusts for carpet pile up to 3 cm The dock washes the mop pad with **100°C water** (up from 80°C in the previous generation) and dries with **55°C warm air**, achieving a claimed 99.99% bacteria removal rate. ## Battery and Power Architecture | Metric | Value | |--------|-------| | Battery capacity | 6,400 mAh | | Runtime (quiet mode) | ~200 minutes | | Runtime (standard, 50 m²) | ~90 minutes (40% remaining) | | Charge time | 2.5 hours (40% faster than gen-1) | | Standby power | < 5W | | Monthly energy (daily 50 m²) | ~11 kWh | NotebookCheck estimates a real-world coverage of ~70 m² per charge in standard mode. The 2.5-hour fast charging is enabled by a higher-wattage dock, though Roborock hasn't published the exact charging wattage. ## Smart Home Integration: Matter Changes Everything Roborock Saros 20 Sonic top view showing sensor array The Saros 20 Sonic is one of the first robot vacuums with native **Matter** support. This is significant because: - **Apple Home** — full control without HomeKit-specific firmware. Start/stop, room selection, battery status - **Google Home** — native integration, voice commands, routines - **Amazon Alexa** — same native support - **Siri Shortcuts** — works through the Matter bridge Previously, robot vacuum smart home integration required either Roborock's app, a cloud-to-cloud Alexa skill, or a workaround like Home Assistant with a custom integration. Matter makes the robot a first-class citizen in any smart home ecosystem. For my Home Assistant setup, this also means I can potentially integrate it through the Matter protocol rather than relying on cloud APIs or unofficial integrations. ## Noise Profile NotebookCheck measured (at 1 meter distance): - **38 dB** — standby / mop drying (whisper-quiet) - **~60 dB** — standard cleaning / mop washing (normal conversation level) - **~70 dB** — maximum suction (vacuum cleaner territory) At 38 dB standby, you can have it drying mops overnight without it being audible from another room. The 60 dB standard mode is workable if you're in a different room during a call. Roborock Saros 20 Sonic cleaning a kitchen floor ## The Specs That Matter | Specification | Saros 20 Sonic | Saros 10R (prev gen) | |--------------|----------------|---------------------| | Suction | 36,000 Pa | 22,000 Pa | | Mopping | Sonic 4,000 vib/min | Rotary pads | | Threshold crossing | 8.8 cm double | 4 cm single | | Obstacle types | 300+ | 108 | | Battery | 6,400 mAh / 200 min | 5,200 mAh / 180 min | | Dock wash temp | 100°C | 80°C | | Matter support | Yes | No | | Height | 7.98 cm | 7.98 cm | | Dustbin | 259 ml | 270 ml | ## Where to Buy in Switzerland The Saros 20 Sonic Complete is available at **CHF 1'099** on [Galaxus](https://www.galaxus.ch/en/s2/product/roborock-saros-20-sonic-complete-36000-pa-wiping-pad-vibrating-robot-vacuum-cleaners-67252303), [Digitec](https://www.digitec.ch), and nettoshop.ch. The "Complete" version includes the full RockDock with auto-empty, hot wash, and detergent dispenser. ## Bottom Line The Saros 20 Sonic is the most technically impressive robot vacuum I've analyzed. The sensor fusion approach (ToF + RGB + structured light) is more sophisticated than what you'll find in most autonomous mobile robots in industrial settings. The AdaptiLift 3.0 solves a real problem that every Swiss apartment dweller knows. And Matter support finally makes robot vacuums proper smart home devices instead of app-controlled appliances. > **Full review**: For detailed cleaning performance scores, mopping test results, and buying advice, read my [complete Italian review on SpazioiTech](https://www.spazioitech.it/roborock-saros-20-sonic-recensione-completa/).]]> Mon, 20 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/roborock-saros-20-sonic-the-tech-behind-2026-smartest-robot-vacuum/ Smart Home Roborock Robot Vacuum Home Automation Matter Home Assistant Automations Guide 2026: From Basic to Advanced Smart Home Control https://daniele-messi.com/en/blog/home-assistant-automations-guide-2026-from-basic-to-advanced-smart-home-control/ Unlock your smart home's full potential with this comprehensive home assistant automations guide. Learn to build powerful automations, from simple triggers to complex, data-driven sequences, in 2026. Sun, 19 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/home-assistant-automations-guide-2026-from-basic-to-advanced-smart-home-control/ Home Assistant Smart Home Automation YAML IoT Automation Guide Building Custom Slash Commands in Claude Code for Enhanced Workflow in 2026 https://daniele-messi.com/en/blog/building-custom-slash-commands-in-claude-code-for-enhanced-workflow-in-2026/ Unlock Claude Code's full potential. Learn to build claude code custom commands in 2026, from basic definitions to integrating external tools, enhancing your development workflow and productivity. = ({}) => { return (

{{componentName}} Component

{/* Component content */}
); }; export default {{componentName}}; ``` Place this file in the `src/components/` directory. - name: add-dynamic-copyright description: Adds a dynamic copyright header to the current file. parameters: - name: authorName description: The name of the author. type: string required: true - name: year description: The current year for the copyright notice. type: integer default: 2026 prompt: | Please add the following copyright header to the top of the currently open file, using "Author: {{authorName}}" and "Year: {{year}}": ``` /* * Copyright (c) {{year}} Your Company. All rights reserved. * Author: {{authorName}} * This software is the confidential and proprietary information of Your Company. */ ``` ``` Now, typing `/create-component` will prompt you for `componentName`, and `/add-dynamic-copyright` will prompt for `authorName` while defaulting `year` to 2026. This significantly expands the utility of your **claude code slash commands**. ## Integrating with External Tools and APIs (Claude Code Skills) One of the most powerful aspects of **claude code skills** is their ability to interact with external systems. This transforms Claude Code from a mere code assistant into a true automation agent. By defining tools within your `CLAUDE.md`, you can enable your custom commands to call external APIs, run shell scripts, or interact with other services. This is a game-changer for building AI-powered automations. For a deeper dive into building such automations, consider reading [Building AI-Powered Automations: A Developer's Practical Guide](/en/blog/building-ai-powered-automations-a-developer-s-practical-guide/). Let's define a tool that can fetch data from a hypothetical project management API and then create a command that uses it. ```markdown # CLAUDE.md tools: - name: fetchProjectData description: Fetches project details from the Project Management API. parameters: type: object properties: projectId: type: string description: The ID of the project to fetch. required: - projectId returns: type: object properties: name: type: string status: type: string dueDate: type: string code: | async (projectId) => { const response = await fetch(`https://api.yourprojectmanager.com/projects/${projectId}`, { headers: { 'Authorization': `Bearer ${process.env.PROJECT_API_KEY}` } }); if (!response.ok) { throw new Error(`Failed to fetch project data: ${response.statusText}`); } return await response.json(); } commands: - name: get-project-status description: Retrieves and summarizes the status of a given project. parameters: - name: projectId description: The ID of the project to check. type: string required: true prompt: | Using the `fetchProjectData` tool, get the details for project ID "{{projectId}}". Then, summarize the project's name, current status, and due date in a concise sentence. ``` Now, when you type `/get-project-status `, Claude Code will use the `fetchProjectData` tool, execute the JavaScript code to call your external API, and then use the returned data to formulate its response based on your prompt. For more details on integrating tools, refer to the official [Claude Code Tools documentation](https://docs.anthropic.com/claude/reference/tools). ## Advanced Techniques: Chaining Commands and Context As you build more complex workflows, you might find yourself wanting to chain multiple **claude code custom commands** or have them leverage deeper contextual understanding. Claude Code excels here by maintaining conversational context and allowing commands to modify the project environment. For instance, one command could generate a test file, and another could then populate it with basic test cases. You can also define global variables or configurations within your `CLAUDE.md` that all commands can access, ensuring consistency. Mastering your `CLAUDE.md` file is key to unlocking these advanced capabilities. We've covered this extensively in [CLAUDE.md Best Practices: Crafting the Perfect AI Project File for 2026](/en/blog/claude-md-best-practices-crafting-the-perfect-ai-project-file-for-2026/). Consider a scenario where you want to automate generating a new feature branch and a corresponding task in your issue tracker. This would involve chaining multiple external tool calls or prompts. While direct command chaining isn't a single keyword, you can design commands to set up preconditions for subsequent commands or use Claude's natural language understanding to guide it through a multi-step process using several `/commands`. ## Best Practices for Building Robust Claude Code Custom Commands To ensure your **claude code custom commands** are reliable and maintainable, follow these best practices: 1. **Clear Descriptions**: Always provide concise and accurate `description` fields for your commands and parameters. This helps both you and Claude Code understand their purpose. 2. **Modularity**: Break down complex tasks into smaller, more manageable commands. This makes them easier to debug, test, and reuse. 3. **Error Handling**: For commands that involve external tools or complex logic, incorporate robust error handling within your `code` blocks. Inform the user if something goes wrong. 4. **Version Control**: Since `CLAUDE.md` is a critical part of your project configuration, keep it under version control (e.g., Git). This allows for collaborative development and easy rollbacks. 5. **Testing**: Before deploying commands to a team, thoroughly test them. Manually run them with various inputs and verify the output. For more rigorous testing, especially with complex prompts and tools, refer to our guide on [Mastering Prompt Testing & CI/CD for AI Applications in 2026](/en/blog/mastering-prompt-testing-ci-cd-for-ai-applications-in-2026/). 6. **Documentation**: Beyond the `description` field, consider adding comments within your `CLAUDE.md` file for more complex logic or design decisions. For external tools, link to their official documentation, like the [Claude Code documentation on skills and tools](https://docs.anthropic.com/claude/docs/skills-and-tools). ## Conclusion **Building claude code custom commands** is a powerful way to personalize your AI development environment and significantly enhance your productivity in 2026. From simple text insertions to complex integrations with external APIs, these commands empower you to automate mundane tasks, enforce coding standards, and streamline entire workflows. By investing time in defining your own **claude code custom commands**, you're not just saving keystrokes; you're building a more intelligent, efficient, and tailored development experience. Start experimenting today, and unlock the full potential of Claude Code. ## Recommended Gear If you're building your own setup, here's the hardware I recommend: - **[Logitech MX Keys S](https://www.amazon.it/s?k=Logitech+MX+Keys+S&linkCode=ll2&tag=spazitec0f-21)** — keyboard for productive coding sessions - **[Samsung 49" Ultra-Wide Monitor](https://www.amazon.it/s?k=Samsung+49+ultrawide+monitor&linkCode=ll2&tag=spazitec0f-21)** — ultra-wide monitor for side-by-side coding ## FAQ ### What are Claude Code custom commands? Claude Code custom commands are personalized shortcuts designed to automate repetitive tasks, integrate with existing toolchains, and significantly boost developer productivity. They are similar to command-line utilities or IDE extensions but operate within the Claude Code environment. ### How do custom slash commands enhance workflow in Claude Code? Custom commands provide a structured, repeatable, and highly efficient way to invoke specific AI behaviors or execute predefined scripts. This eliminates the need for developers to type out lengthy natural language prompts repeatedly for recurring actions, thereby streamlining their development process. ### What is the basic syntax for triggering a Claude Code custom command? Custom commands in Claude Code are triggered by a simple '/' prefix followed by a specific keyword. For example, a command might be invoked by typing '/refactor' to initiate a code refactoring action. ### Why are custom commands increasingly important for AI-assisted development by 2026? As AI-assisted development evolves, custom commands become vital for tailoring AI tools like Claude Code to individual developer needs and project contexts. They ensure that the AI's powerful capabilities are applied precisely and efficiently, maximizing utility and developer output. ## Related Articles - [10 Claude Code Automations You Should Try Today](/en/blog/10-claude-code-automations-you-should-try/) - [Claude Code Hooks: The Complete Guide to Automation & Workflow in 2026](/en/blog/claude-code-hooks-the-complete-guide-to-automation-workflow-in-2026/) - [Claude Code Sub-Agents: Practical Examples & Advanced Strategies for 2026](/en/blog/claude-code-sub-agents-practical-examples-advanced-strategies-for-2026/) - [Claude Code vs Cursor vs Copilot: An Honest Comparison for 2026](/en/blog/claude-code-vs-cursor-vs-copilot-an-honest-comparison-for-2026/) - [CLAUDE.md Best Practices: Crafting the Perfect AI Project File for 2026](/en/blog/claude-md-best-practices-crafting-the-perfect-ai-project-file-for-2026/) - [Getting Started with Claude Code: The Ultimate Guide](/en/blog/getting-started-with-claude-code/)]]> Sat, 18 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/building-custom-slash-commands-in-claude-code-for-enhanced-workflow-in-2026/ Claude Code Custom Commands AI Development Workflow Automation Programming AI Agent Framework Comparison 2026: LangChain vs CrewAI vs AutoGen https://daniele-messi.com/en/blog/ai-agent-framework-comparison-2026-langchain-vs-crewai-vs-autogen/ Explore the definitive 2026 ai agent framework comparison: LangChain vs CrewAI vs AutoGen. Discover strengths, use cases, and choose the best framework for your next agentic project. Fri, 17 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/ai-agent-framework-comparison-2026-langchain-vs-crewai-vs-autogen/ AI Agents LangChain CrewAI AutoGen Agentic Engineering Agentic Engineering: The Next Evolution in AI Development for 2026 https://daniele-messi.com/en/blog/agentic-engineering-the-next-evolution-in-ai-development-for-2026/ Explore agentic engineering, the paradigm shift enabling autonomous AI agents to build and deploy software. Learn practical strategies for AI agent development in 2026. Thu, 16 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/agentic-engineering-the-next-evolution-in-ai-development-for-2026/ Agentic Engineering AI Agents Software Development AI Automation DevOps Observability AI Agents 2026: Monitoring & Debugging Multi-Agent Systems https://daniele-messi.com/en/blog/observability-ai-agents-2026-monitoring-debugging-multi-agent-systems/ Master observability for AI agents in 2026. Learn essential monitoring and debugging techniques for complex multi-agent systems to ensure reliability and performance. Thu, 16 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/observability-ai-agents-2026-monitoring-debugging-multi-agent-systems/ observability AI agents multi-agent systems debugging AI monitoring Advanced Home Assistant Blueprints for Developers in 2026 https://daniele-messi.com/en/blog/advanced-home-assistant-blueprints-for-developers-in-2026/ Unlock the full potential of your smart home with advanced Home Assistant blueprints. This guide for developers dives into complex automation templates, robust Home Assistant YAML, and powerful integrations to elevate your system in 2026. {% set current_hour = now().hour %} {% if current_hour >= 22 or current_hour < 6 %} 20 {% elif current_hour >= 18 %} 60 {% else %} 100 {% endif %} color_temp: > {% set lux_level = states('sensor.ambient_light_level') | float(0) %} {% if lux_level < 50 %} 250 # Warm light {% else %} 400 # Cooler light {% endif %} ``` This `data_template` uses both the current time and a hypothetical `ambient_light_level` sensor to set the light's brightness and color temperature dynamically. Understanding [Jinja2 templating](https://jinja.palletsprojects.com/en/3.1.x/templates/) is crucial for unlocking the full potential of your `home assistant automation templates`. ## Crafting Robust Home Assistant YAML Blueprints Developing powerful **Home Assistant blueprints** requires a deep understanding of their YAML structure. Each blueprint starts with metadata and defines inputs that users will configure. The core logic resides in the `trigger`, `condition`, and `action` sections, which closely mirror standard Home Assistant automations but with the added flexibility of input variables. Let's outline a blueprint for advanced presence-based climate control, considering multiple occupants and zones. This example demonstrates how to define inputs, use multiple triggers, and apply conditions to create a smart, energy-efficient system. ```yaml blueprint: name: Advanced Multi-Zone Presence Climate Control description: Adjusts climate based on presence in multiple zones, considering time and external factors. domain: automation input: occupancy_sensors: name: Occupancy Sensors selector: entity: domain: binary_sensor multiple: true climate_entities: name: Climate Devices selector: entity: domain: climate multiple: true target_temperature_day: name: Target Temperature (Day) default: 21 selector: number: min: 16 max: 28 step: 0.5 unit_of_measurement: "°C" target_temperature_night: name: Target Temperature (Night) default: 19 selector: number: min: 16 max: 28 step: 0.5 unit_of_measurement: "°C" day_start_time: name: Day Start Time default: "07:00:00" selector: time: night_start_time: name: Night Start Time default: "22:00:00" selector: time: trigger: - platform: state entity_id: !input occupancy_sensors to: 'on' id: 'presence_detected' - platform: state entity_id: !input occupancy_sensors to: 'off' for: minutes: 10 # Allow for brief absences id: 'no_presence_detected' - platform: time at: !input day_start_time id: 'day_time' - platform: time at: !input night_start_time id: 'night_time' condition: [] # Conditions can be added here, e.g., 'solar_gain_too_high' action: - choose: - conditions: "{{ trigger.id == 'presence_detected' or trigger.id == 'day_time' or trigger.id == 'night_time' }}" sequence: - service: climate.set_temperature target: entity_id: !input climate_entities data_template: temperature: > {% set current_time = now().time() %} {% set day_start = strptime(states('input_datetime.day_start_time'), '%H:%M:%S').time() %} {% set night_start = strptime(states('input_datetime.night_start_time'), '%H:%M:%S').time() %} {% if current_time >= day_start and current_time < night_start %} {{ states('input_number.target_temperature_day') | float }} {% else %} {{ states('input_number.target_temperature_night') | float }} {% endif %} - conditions: "{{ trigger.id == 'no_presence_detected' }}" sequence: - service: climate.set_hvac_mode target: entity_id: !input climate_entities data: hvac_mode: 'off' ``` This `home assistant yaml` blueprint provides a flexible foundation. You can further enhance it with external weather data, solar gain predictions, or even integrate with energy pricing for optimal efficiency. For more general automation principles, refer to our [Home Assistant Automations Guide 2026: From Basic to Advanced Smart Home Control](/en/blog/home-assistant-automations-guide-2026-from-basic-to-advanced-smart-home-control/). ## Advanced Debugging and Testing Strategies for Blueprints Developing complex **Home Assistant blueprints** invariably leads to debugging. Unlike simple automations, blueprints are shared templates, so robust testing is paramount before widespread deployment. Here are some strategies: 1. **Use the Developer Tools:** The "States" and "Templates" sections are your best friends. You can test Jinja2 templates in real-time to ensure your logic is sound before embedding it in your blueprint. The "Triggers" tool can simulate events, helping you verify your blueprint's `trigger` section. 2. **Version Control:** Always keep your blueprints under version control (e.g., Git). This allows you to track changes, revert to previous versions, and collaborate effectively. Store them in a dedicated `blueprints` folder within your Home Assistant configuration directory. 3. **Small, Incremental Changes:** Avoid making large changes at once. Test each component (trigger, condition, action) individually before combining them. 4. **Logging:** Utilize Home Assistant's logging capabilities. Add `logbook` entries or `persistent_notification` services within your blueprint's actions to track its execution flow and variable states, especially during development. ## Integrating External Services and Custom Components One of the most powerful aspects of advanced **Home Assistant blueprints** is their ability to seamlessly integrate with external services and custom components. This allows you to extend Home Assistant's core functionality and create highly specialized automations. For instance, you could design a blueprint that leverages local AI inference for advanced presence detection or anomaly detection. Imagine a blueprint that monitors audio levels for specific keywords using a local voice assistant and triggers actions based on that. For integrating local AI, our article on [Unleashing Local AI with Home Assistant: Ollama Integration in 2026](/en/blog/unleashing-local-ai-with-home-assistant-ollama-integration-in-2026/) provides an excellent starting point. Another common integration involves custom devices built with platforms like ESPHome. A blueprint could take an ESPHome device's entity ID as an input and then perform actions like flashing an LED, reading a sensor, or triggering a relay. For example, if you have an [ESPHome](https://esphome.io/index.html) device monitoring air quality, a blueprint could use its sensor data to control ventilation fans. ```yaml action: - service: esphome.fan_control_service target: entity_id: !input esphome_fan_entity data_template: speed: > {% set air_quality = states('sensor.esphome_air_quality_index') | float(0) %} {% if air_quality > 150 %} 'high' {% elif air_quality > 100 %} 'medium' {% else %} 'low' {% endif %} ``` This demonstrates how a blueprint can abstract the interaction with a custom ESPHome service, making it easy for users to deploy without knowing the specific service call details. ## Sharing and Discovering Advanced Home Assistant Blueprints Home Assistant's vibrant community is a treasure trove of shared **Home Assistant blueprints**. Once you've crafted a powerful blueprint, sharing it can benefit countless other users. The official [Home Assistant Blueprints Exchange](https://www.home-assistant.io/docs/blueprints/share/) and community forums are excellent places to publish your creations. When sharing, ensure your blueprint is well-documented: * **Clear Name and Description:** Explain what the blueprint does and its primary use case. * **Detailed Inputs:** Clearly describe each input, its purpose, and expected values. * **Example Usage:** Provide a simple example of how to configure and use the blueprint. * **GitHub Gist/Repository:** Host your blueprint YAML file on GitHub Gist or a repository for easy access and version tracking. Discovering existing blueprints can also save you significant development time. Before embarking on a complex automation, check the community for existing `home assistant automation templates` that might already solve your problem or provide a strong foundation. ## Conclusion: Elevating Your Smart Home with Advanced Home Assistant Blueprints In 2026, **Home Assistant blueprints** are more than just a convenience; they are a fundamental tool for developers to build sophisticated, maintainable, and shareable smart home automations. By mastering Jinja2 templating, understanding robust `home assistant yaml` structures, and integrating external services, you can push the boundaries of what your smart home can achieve. From dynamic climate control to advanced security systems and custom device integrations, blueprints empower you to create intelligent, reactive environments with unprecedented efficiency. Dive in, experiment, and transform your Home Assistant setup into a truly advanced smart ecosystem. ## Recommended Gear If you're building your own setup, here's the hardware I recommend: - **[Sonoff Zigbee 3.0 USB Dongle](https://www.amazon.it/s?k=Sonoff+Zigbee+3.0+dongle&linkCode=ll2&tag=spazitec0f-21)** — Zigbee coordinator for Home Assistant - **[Shelly Plus 1PM](https://www.amazon.it/s?k=Shelly+Plus+1PM&linkCode=ll2&tag=spazitec0f-21)** — smart relay with energy monitoring - **[ESP32 Development Board](https://www.amazon.it/s?k=ESP32+development+board&linkCode=ll2&tag=spazitec0f-21)** — ESP32 board for ESPHome sensors - **[Aqara Temperature Sensor](https://www.amazon.it/s?k=Aqara+temperature+sensor+Zigbee&linkCode=ll2&tag=spazitec0f-21)** — Zigbee temperature/humidity sensor - **[Beelink Mini PC (Intel N100)](https://www.amazon.it/s?k=Beelink+Mini+PC+N100&linkCode=ll2&tag=spazitec0f-21)** — mini PC to run Home Assistant ## FAQ ### What are Home Assistant blueprints? Home Assistant blueprints are powerful templates that encapsulate complex automations, making them reusable, shareable, and easier to manage. They abstract away underlying YAML complexities, allowing for streamlined deployment of sophisticated smart home solutions. ### Why are blueprints essential for developers in 2026? In 2026, mastering blueprints is crucial for developers to build resilient, scalable, and truly intelligent smart home solutions. They provide a structured approach to creating advanced automations that can adapt to various conditions and inputs. ### How do blueprints simplify Home Assistant automations? Blueprints simplify automations by allowing developers to define inputs, triggers, and actions once, rather than writing repetitive code. This approach enables minimal configuration for deployment and enhances manageability across multiple instances or users. ### What is the role of Jinja2 templating in advanced blueprints? Jinja2 templating is at the heart of advanced Home Assistant blueprints, enabling dynamic and context-aware automations. It allows for extracting attributes, performing calculations, and creating conditional logic directly within the blueprint's triggers and actions. ## Related Articles - [Home Assistant Automations Guide 2026: From Basic to Advanced Smart Home Control](/en/blog/home-assistant-automations-guide-2026-from-basic-to-advanced-smart-home-control/) - [Master Your Audi EV Charging with Home Assistant Automation (2026)](/en/blog/master-your-audi-ev-charging-with-home-assistant-automation-2026/) - [Mastering Home Assistant on Proxmox LXC: Setup Guide 2026](/en/blog/mastering-home-assistant-on-proxmox-lxc-setup-guide-2026/) - [Mastering Home Assistant Solar Automation: Your Guide to Smart Energy in 2026](/en/blog/mastering-home-assistant-solar-automation-your-guide-to-smart-energy-in-2026/) - [Unleashing Local AI with Home Assistant: Ollama Integration in 2026](/en/blog/unleashing-local-ai-with-home-assistant-ollama-integration-in-2026/)]]> Wed, 15 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/advanced-home-assistant-blueprints-for-developers-in-2026/ Home Assistant Blueprints Automation Smart Home YAML Proxmox Advanced Networking 2026: VLANs, Firewalls & Security https://daniele-messi.com/en/blog/proxmox-advanced-networking-2026-vlans-firewalls-security/ Unlock Proxmox advanced networking in 2026 with this comprehensive guide. Learn Proxmox VLAN setup, robust Proxmox firewall rules, and essential network segmentation for enhanced security and performance. System -> Network`. Select your primary Linux Bridge (e.g., `vmbr0`), click `Edit`, and ensure `VLAN aware` is checked. For CLI users, modify `/etc/network/interfaces`: ```bash # /etc/network/interfaces auto lo iface lo inet loopback # Physical interface - set to manual auto eno1 iface eno1 inet manual # Main Linux Bridge - make it VLAN-aware auto vmbr0 iface vmbr0 inet static address 192.168.1.10/24 # Proxmox host IP on the default VLAN (VLAN 1, if untagged) gateway 192.168.1.1 bridge-ports eno1 bridge-stp off bridge-fd 0 bridge-vlan-aware yes # This is the key setting bridge-vlan-id 1 # Optional: Sets the native VLAN for untagged traffic on this bridge # Apply changes (carefully, as this can interrupt network access) # systemctl restart networking ``` After saving, you'll need to apply the changes, which often requires a network restart or even a node reboot. Always perform this with caution and a backup plan. 2. **Assign VLAN Tags to VMs/LXCs:** Once `vmbr0` is VLAN-aware, you can assign VLAN IDs directly to the network interfaces of your VMs and LXCs. In the VM/LXC hardware settings, under the `Network Device` section, simply enter the desired `VLAN Tag` (e.g., `10` for VLAN 10). The Proxmox host will then tag the traffic from that VM/LXC with the specified VLAN ID before sending it out through `vmbr0` to your physical switch. For example, if you're setting up [Home Assistant on Proxmox LXC](/en/blog/mastering-home-assistant-on-proxmox-lxc-setup-guide-2026/), you might assign it to VLAN 20 for IoT devices, ensuring it's isolated from your main network. ## Implementing Robust Proxmox Firewall Rules The Proxmox firewall provides a multi-layered security approach, operating at the datacenter, host, and individual VM/LXC levels. This granular control is essential for protecting your virtualized environment from unauthorized access and isolating potential threats. A well-configured **Proxmox firewall** is your first line of defense against both external attacks and internal lateral movement, a critical component of `network segmentation Proxmox` strategies. ### Firewall Levels and Their Purpose * **Datacenter Firewall:** These are global rules applied to all traffic before it reaches any Proxmox host or VM/LXC. Ideal for blocking common malicious IPs or allowing management access from specific trusted networks. * **Host Firewall:** Specific to each Proxmox node, these rules protect the hypervisor itself. This is where you'd restrict SSH access to the Proxmox host, for example. * **VM/LXC Firewall:** Applied directly to the virtual machine or container, offering the most granular control over individual workload traffic. This is where you define what a specific application or service can send or receive. ### Configuring Firewall Rules All firewall configurations can be managed via the Proxmox GUI or through CLI commands. Organizations implementing robust Proxmox firewalls and VLANs report a 60% decrease in unauthorized network access attempts by 2026. 1. **Enable the Firewall:** Ensure the firewall is enabled at the datacenter level (`Datacenter -> Firewall -> Options -> Firewall: Yes`) and for individual VMs/LXCs (`VM/LXC -> Firewall -> Enable: Yes`). 2. **Add Rules (GUI Example):** * Navigate to `Datacenter -> Firewall`, `Node -> Firewall`, or `VM/LXC -> Firewall` depending on the scope. * Click `Add` to create a new rule. * **Action:** `ACCEPT`, `DROP`, or `REJECT`. * **Direction:** `IN` (incoming) or `OUT` (outgoing). * **Interface:** (Optional) Specify a network interface, especially useful for VM/LXC rules. * **Protocol:** (Optional) `tcp`, `udp`, `icmp`, etc. * **Source/Destination:** IP address or CIDR range. * **Source/Destination Port:** Specific port numbers (e.g., `22` for SSH, `80` for HTTP). * **Log:** (Optional) Log hits on this rule for auditing. 3. **CLI Example (Allow SSH to a VM from a specific management network):** First, ensure the firewall is enabled for VM 101: `qm set 101 --firewall 1` Then, add an inbound rule to VM 101 to allow TCP port 22 (SSH) from `192.168.1.0/24`: `pve_firewall add rule --vmid 101 --type in --action ACCEPT --proto tcp --dport 22 --source 192.168.1.0/24 --comment ## Recommended Gear If you're building your own setup, here's the hardware I recommend: - **[Beelink Mini PC (Intel N100)](https://www.amazon.it/s?k=Beelink+Mini+PC+N100&linkCode=ll2&tag=spazitec0f-21)** — mini PC for Proxmox home lab - **[Samsung 870 EVO SSD 1TB](https://www.amazon.it/s?k=Samsung+870+EVO+1TB&linkCode=ll2&tag=spazitec0f-21)** — SSD for VM storage - **[Crucial RAM 32GB DDR4](https://www.amazon.it/s?k=Crucial+32GB+DDR4+SODIMM&linkCode=ll2&tag=spazitec0f-21)** — RAM upgrade for virtualization - **[TP-Link 2.5G Ethernet Switch](https://www.amazon.it/s?k=TP-Link+2.5G+switch&linkCode=ll2&tag=spazitec0f-21)** — 2.5GbE switch for lab networking ## Related Articles - [Mastering Proxmox Automation with Ansible in 2026: A Practical Guide](/en/blog/mastering-proxmox-automation-with-ansible-in-2026-a-practical-guide/) - [Proxmox Backup Strategy: Complete Guide for 2026 and Beyond](/en/blog/proxmox-backup-strategy-complete-guide-for-2026-and-beyond/) - [Proxmox GPU Passthrough for AI Workloads: Unleashing Performance in 2026](/en/blog/proxmox-gpu-passthrough-for-ai-workloads-unleashing-performance-in-2026/) - [Proxmox Home Lab Cost Analysis 2026: Cloud vs Self-Host](/en/blog/proxmox-home-lab-cost-analysis-2026-cloud-vs-self-host/) - [Proxmox Home Lab: A Practical Guide to Self-Hosting in 2026](/en/blog/proxmox-home-lab-guide-self-hosting-2026/) - [Proxmox LXC vs VM: Choosing the Right Virtualization in 2026](/en/blog/proxmox-lxc-vs-vm-choosing-the-right-virtualization-in-2026/) - [Proxmox Ollama Setup: Self-Hosted AI Server for Developers in 2026](/en/blog/proxmox-ollama-setup-self-hosted-ai-server-for-developers-in-2026/)]]> Tue, 14 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/proxmox-advanced-networking-2026-vlans-firewalls-security/ Proxmox Networking VLAN Firewall Security AI Coding Agents Are Changing How We Ship Software https://daniele-messi.com/en/blog/ai-coding-agents-are-changing-how-we-ship-software/ A practical look at how AI coding agents fit into real developer workflows in 2026 — what works, what doesn't, and how to get the most out of them. Mon, 13 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/ai-coding-agents-are-changing-how-we-ship-software/ AI Agents Developer Tools Claude Code Productivity Software Engineering SEO for Personal Websites in 2026: Your Ultimate Guide https://daniele-messi.com/en/blog/seo-for-personal-websites-in-2026-your-ultimate-guide/ Master SEO for your personal website in 2026 and beyond. Learn actionable strategies for content, technical SEO, and user experience to boost your online visibility. Descriptive Alt Text ``` * **HTTPS Security:** Ensure your site uses HTTPS. This is a standard security measure and a minor ranking factor. * **Structured Data (Schema Markup):** Implement schema markup to help search engines understand the context of your content (e.g., articles, reviews, events, products). This can lead to rich snippets in search results. ```json ``` * **Crawlability and Indexability:** Ensure your `robots.txt` file isn't blocking important content and that your XML sitemap is up-to-date and submitted to Google Search Console. ## User Experience (UX) and SEO Search engines want to rank sites that users love. UX and SEO are intrinsically linked: * **Intuitive Navigation:** Make it easy for visitors to find what they're looking for. A clear site structure and logical navigation menu are essential. * **Engaging Content:** Keep users on your site longer with compelling content, clear calls-to-action, and internal linking to related articles. * **Accessibility:** Ensure your website is usable by everyone, including people with disabilities. This is not only ethical but also increasingly a factor in search rankings. ## Off-Page SEO: Building Authority and Trust While on-page factors are crucial, off-page signals still matter: * **Backlinks:** Earn high-quality backlinks from reputable websites in your niche. Focus on quality over quantity. Guest blogging, collaborations, and creating shareable content can help. * **Social Signals:** While not a direct ranking factor, social media activity can drive traffic and increase brand visibility, indirectly impacting SEO. * **Online Reputation Management:** Monitor mentions of your name or website and engage positively with your audience online. ## Embracing AI as a Tool, Not a Crutch AI tools can significantly enhance your SEO efforts in 2026: * **Content Ideation:** Use AI to brainstorm topics and identify keyword gaps. * **Content Optimization:** Tools can analyze your content for keyword density, readability, and suggest improvements. * **Technical Audits:** AI-powered tools can help identify technical SEO issues more quickly. However, always remember that AI-generated content should be reviewed, edited, and infused with your unique human perspective and experience to meet E-E-A-T guidelines. ## Conclusion: A Holistic Approach for 2026 and Beyond Optimizing your personal website for search engines in 2026 requires a holistic approach. By focusing on user intent, creating high-quality, original content, ensuring a stellar technical foundation, prioritizing user experience, and strategically building authority, you can significantly improve your website's visibility. Stay adaptable, keep learning, and consistently refine your strategy to thrive in the ever-evolving world of search. ## FAQ ### Why is SEO important for personal websites in 2026? In 2026, the digital landscape is highly competitive, making SEO crucial for personal websites to be discoverable. Simply having a website is not enough; effective SEO ensures your site ranks high in search engine results, attracting your target audience. ### What key principles do search engines like Google prioritize in 2026? By 2026, search engines continue to emphasize user intent, understanding the 'why' behind a search, and E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness). They also prioritize Core Web Vitals, ensuring a fast, interactive, and visually stable page experience. ### What is E-E-A-T and why is it critical for personal websites? E-E-A-T stands for Experience, Expertise, Authoritativeness, and Trustworthiness. For personal websites, demonstrating these qualities is critical for building trust with your audience and improving search rankings, often by showcasing unique skills, projects, and testimonials.]]> Mon, 13 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/seo-for-personal-websites-in-2026-your-ultimate-guide/ SEO 2026 Personal Website SEO Technical SEO Content Strategy User Experience Master Your Audi EV Charging with Home Assistant Automation (2026) https://daniele-messi.com/en/blog/master-your-audi-ev-charging-with-home-assistant-automation-2026/ Unlock smart, cost-effective EV charging for your Audi with Home Assistant. This guide covers integrating your EV and charger for advanced home assistant ev charging automation. **Open Source**: The blueprints from this article are available on GitHub: [Home Lab Automation Blueprints](https://github.com/danymexi/homelab-automation-blueprints). ### Why Automate Your EV Charging? Automating your EV charging offers a multitude of benefits, extending beyond mere convenience: * **Cost Savings**: Take advantage of time-of-use (TOU) electricity tariffs by charging only during off-peak hours, often saving significant amounts on your energy bill. * **Solar Optimization**: Maximize self-consumption of your rooftop solar power by directing excess energy directly into your Audi's battery. * **Grid Stability**: By shifting charging times, you contribute to a more stable electrical grid, reducing strain during peak demand. * **Battery Health**: Smart charging can help maintain optimal battery health by avoiding unnecessary charges or overcharging. * **Convenience**: Set it and forget it. Your car will be charged exactly when and how you need it, ready for your next journey. ### Prerequisites for Audi EV Charging Automation Before diving into the automations, ensure you have the following in place: 1. **[Home Assistant](https://www.home-assistant.io) Instance**: A running Home Assistant installation (e.g., Home Assistant OS, Container, or Supervised). We'll assume you're on a recent version, such as Home Assistant 2026.x.x or later. 2. **Audi EV**: Any Audi electric vehicle (e.g., e-tron GT, Q4 e-tron, Q8 e-tron) with active Audi Connect services that allow remote access to vehicle data. 3. **Smart EV Charger**: A Level 2 (or even Level 1 with a smart plug) EV charger that is compatible with [Home Assistant](https://www.home-assistant.io). Popular brands like Wallbox, ChargePoint, Enphase (formerly Enel X Way), Zappi, or even generic smart plugs for Level 1 charging often have integrations. 4. **Network Connectivity**: Your Home Assistant instance, Audi (via its cloud service), and smart charger must all be connected to the internet and accessible by Home Assistant. ### Integrating Your Audi with Home Assistant For **Audi Home Assistant** integration, you'll typically use the official `Audi Connect` integration or a community-developed HACS (Home Assistant Community Store) alternative if more advanced features are desired. The official integration usually provides read-only access to critical data, which is sufficient for most charging automations. To add the official integration: 1. Go to `Settings` -> `Devices & Services` -> `Add Integration`. 2. Search for `Audi Connect`. 3. Follow the prompts to log in with your Audi account credentials. You might need to confirm a security code sent to your phone or email. Once configured, Home Assistant will expose various entities for your Audi, such as: * `sensor.audi_etrongt_battery_level`: Current state of charge. * `sensor.audi_etrongt_charging_state`: Charging status (e.g., `Charging`, `Not charging`, `Plugged in`). * `sensor.audi_etrongt_range`: Estimated remaining range. * `binary_sensor.audi_etrongt_charger_connected`: Indicates if the charging cable is plugged in. ### Integrating Your Smart EV Charger The integration method for your smart EV charger will depend on its brand. Most popular chargers have dedicated Home Assistant integrations. For example: * **Wallbox**: The Wallbox integration provides entities like `switch.wallbox_charger_state` (to start/stop charging) and `sensor.wallbox_current_power`. * **Zappi**: The Zappi integration offers similar controls and monitoring. * **Generic Smart Plug (for Level 1)**: If you're using a standard EVSE plugged into a smart plug (e.g., a Shelly Plug, TP-Link Kasa), the smart plug integration will provide `switch.smart_plug_power` to control power to the charger. Ensure your charger is integrated and you can see its power switch or other relevant control entities in Home Assistant. For this guide, we'll assume your charger has a switch entity, for example, `switch.my_ev_charger_power`. ### Building Your First Home Assistant EV Charging Automation Let's create some practical automations for your **Home Assistant EV charging** setup. #### 1. Scheduled Off-Peak Charging This is a fundamental automation to save money. We'll set it to charge only between 11 PM and 5 AM, provided the Audi is plugged in and its battery is below 80%. ```yaml automation: - alias: "Start Audi EV Charging Off-Peak" id: start_audi_ev_charging_off_peak trigger: - platform: time at: "23:00:00" condition: - condition: and conditions: - condition: state entity_id: binary_sensor.audi_etrongt_charger_connected state: "on" - condition: numeric_state entity_id: sensor.audi_etrongt_battery_level below: 80 action: - service: switch.turn_on target: entity_id: switch.my_ev_charger_power - alias: "Stop Audi EV Charging Off-Peak" id: stop_audi_ev_charging_off_peak trigger: - platform: time at: "05:00:00" condition: - condition: and conditions: - condition: state entity_id: binary_sensor.audi_etrongt_charger_connected state: "on" - condition: state entity_id: switch.my_ev_charger_power state: "on" action: - service: switch.turn_off target: entity_id: switch.my_ev_charger_power ``` #### 2. Solar-Optimized Smart EV Charging This automation will start charging your Audi when your home's solar production exceeds a certain threshold (e.g., 2000W) and stop when it drops below it. This requires an integration for your solar inverter (e.g., SolarEdge, Enphase, Fronius) that exposes a `sensor.solar_production_current_power` entity. ```yaml automation: - alias: "Start Audi EV Charging with Solar Surplus" id: start_audi_ev_charging_solar_surplus trigger: - platform: numeric_state entity_id: sensor.solar_production_current_power above: 2000 # Watts for: ## FAQ ### What is Home Assistant EV charging automation? Home Assistant EV charging automation is a system that intelligently controls your Audi's charging process. It optimizes charging based on real-time data like electricity prices, solar panel output, and your vehicle's readiness requirements, moving beyond simple plug-and-charge. ### What are the main benefits of automating EV charging? Automating your EV charging offers significant advantages, including cost savings by leveraging time-of-use electricity tariffs during off-peak hours. It also maximizes the self-consumption of your rooftop solar power and contributes to overall grid stability. ### Is this automation exclusively for Audi EVs? While this guide specifically targets Audi EV owners, the underlying principles and Home Assistant integrations for EV charging automation are generally applicable. Many other electric vehicle brands can also benefit from similar smart charging setups with compatible Home Assistant integrations. ### Where can I find the blueprints for this automation? The open-source blueprints and detailed instructions for setting up this EV charging automation are available on GitHub. You can find them under the 'Home Lab Automation Blueprints' repository, offering a comprehensive resource for implementation. ## Recommended Gear If you're building your own setup, here's the hardware I recommend: - **[Sonoff Zigbee 3.0 USB Dongle](https://www.amazon.it/s?k=Sonoff+Zigbee+3.0+dongle&linkCode=ll2&tag=spazitec0f-21)** — Zigbee coordinator for Home Assistant - **[Shelly Plus 1PM](https://www.amazon.it/s?k=Shelly+Plus+1PM&linkCode=ll2&tag=spazitec0f-21)** — smart relay with energy monitoring - **[ESP32 Development Board](https://www.amazon.it/s?k=ESP32+development+board&linkCode=ll2&tag=spazitec0f-21)** — ESP32 board for ESPHome sensors - **[Beelink Mini PC (Intel N100)](https://www.amazon.it/s?k=Beelink+Mini+PC+N100&linkCode=ll2&tag=spazitec0f-21)** — mini PC to run Home Assistant - [Mastering Home Assistant on Proxmox LXC: Setup Guide 2026](/en/blog/mastering-home-assistant-on-proxmox-lxc-setup-guide-2026/) - [Mastering Home Assistant Solar Automation: Your Guide to Smart Energy in 2026](/en/blog/mastering-home-assistant-solar-automation-your-guide-to-smart-energy-in-2026/)]]> Sat, 11 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/master-your-audi-ev-charging-with-home-assistant-automation-2026/ EV Charging Home Assistant Audi Automation Smart Home Mastering Home Assistant Solar Automation: Your Guide to Smart Energy in 2026 https://daniele-messi.com/en/blog/mastering-home-assistant-solar-automation-your-guide-to-smart-energy-in-2026/ Unlock true energy independence and savings with home assistant solar automation. Learn to optimize your solar and battery system for maximum efficiency and smart energy management in 2026. **Open Source**: The blueprints from this article are available on GitHub: [Home Lab Automation Blueprints](https://github.com/danymexi/homelab-automation-blueprints). Gone are the days of simply generating power and hoping for the best. With [Home Assistant](https://www.home-assistant.io), you can orchestrate your solar panels, battery bank, and household appliances to work in harmony, making real-time decisions based on production, consumption, grid tariffs, and even weather forecasts. Let's dive into transforming your home into a truly smart energy hub. ## Why Automate Your Solar & Battery System? Automating your solar and battery setup isn't just about convenience; it's about strategic energy management. Here's why it's crucial for any modern smart home: * **Cost Savings**: By intelligently charging your battery during off-peak tariff hours (if applicable) or with excess solar, and discharging during peak rates, you significantly reduce your electricity bill. * **Increased Self-Consumption**: Maximize the use of the clean energy you produce, rather than exporting it for minimal credit or importing grid power when your solar panels are idle. * **Grid Independence & Resilience**: A well-managed battery provides backup power during outages and reduces your reliance on the grid, enhancing energy security. * **Optimized Battery Lifespan**: Smart charging and discharging cycles can help prolong the life of your expensive battery storage system. * **Environmental Impact**: Directly contribute to a greener planet by using more of your self-generated renewable energy. ## Prerequisites: Building Your Home Assistant Energy Foundation Before you can implement sophisticated **home assistant solar automation**, you need a solid foundation. If you're new to [Home Assistant](https://www.home-assistant.io), ensure you have a stable installation. For energy management, the following are essential: 1. **Home Assistant Instance**: Running on a Raspberry Pi, mini PC, or virtual machine. 2. **Solar Inverter Integration**: Your solar inverter (e.g., Fronius, SolarEdge, Enphase, SMA, Huawei) must be integrated into Home Assistant. Many have official integrations, while others might require custom components (HACS) or Modbus TCP/RTU integrations. 3. **Battery System Integration**: Similarly, your battery management system (BMS) needs to expose its data (state of charge, charge/discharge rates) to Home Assistant. This often comes via the inverter integration or a separate battery integration. 4. **Energy Dashboard Setup**: Configure Home Assistant's built-in Energy Dashboard. This provides crucial sensors for total production, consumption, grid import/export, and battery charge/discharge, which are vital for automation triggers and conditions. 5. **Smart Plugs/Switches (Optional but Recommended)**: For controlling high-draw appliances based on energy availability. Ensure you have sensors for: * `sensor.solar_production_w` (current solar power in Watts) * `sensor.grid_import_export_w` (current grid import/export in Watts, positive for import, negative for export) * `sensor.battery_soc` (battery state of charge, 0-100%) * `sensor.battery_charge_discharge_w` (current battery charge/discharge power in Watts) * `sensor.house_consumption_w` (current total house consumption in Watts) ## Core Concepts for Home Assistant Solar Automation Effective **solar automation** hinges on understanding your energy flows and defining clear goals. Home Assistant allows you to monitor and act upon several key metrics: * **Solar Production**: How much power your panels are generating in real-time. * **House Consumption**: How much power your home is currently using. * **Grid Interaction**: Whether you're importing from or exporting to the grid. * **Battery State of Charge (SoC)**: The current charge level of your battery. * **Time-of-Use (ToU) Tariffs**: Different electricity prices based on the time of day. Your automation goals might include: * **Maximizing Self-Consumption**: Use all generated solar power within your home or store it in the battery, minimizing grid interaction. * **Time-of-Use Arbitrage**: Charge the battery from the grid when electricity is cheapest (off-peak) and discharge it when prices are highest (peak). * **Weather-Aware Optimization**: Adjust charging/discharging based on upcoming sunny or cloudy days. * **Critical Load Management**: Ensure essential devices have power even during outages by prioritizing battery usage. ## Essential Home Assistant Battery Automations Let's explore some practical automations you can implement to achieve these goals. ### 1. Prioritizing Self-Consumption: Charging from Excess Solar This is a fundamental automation. When your solar production exceeds your immediate home consumption, the surplus energy should ideally go into your battery rather than being exported to the grid for a low feed-in tariff. **Automation Goal**: Charge the battery when there's excess solar power and SoC is below a threshold. ```yaml # automation.yaml - alias: ## FAQ ### What is Home Assistant solar automation? It's the integration of solar panels and battery storage with the Home Assistant smart home platform to intelligently manage energy flow, reduce grid reliance, and optimize energy usage. It allows for real-time decision-making based on various factors. ### Why is automating my solar and battery system important? Automation is crucial for strategic energy management, moving beyond simple power generation to actively orchestrate your system. This leads to significant cost savings by optimizing battery charging during off-peak hours and utilizing excess solar power efficiently. ### What benefits can I expect from Home Assistant solar automation? You can expect unparalleled control over your energy system, optimized energy usage, reduced reliance on the grid, and substantial cost savings. It transforms your home into a truly smart energy hub. ### Are there resources available to help set up this automation? Yes, open-source blueprints for Home Lab Automation are available on GitHub, providing practical guidance and configurations to help homeowners implement these advanced solar and battery automation strategies. ## Recommended Gear If you're building your own setup, here's the hardware I recommend: - **[Sonoff Zigbee 3.0 USB Dongle](https://www.amazon.it/s?k=Sonoff+Zigbee+3.0+dongle&linkCode=ll2&tag=spazitec0f-21)** — Zigbee coordinator for Home Assistant - **[Shelly Plus 1PM](https://www.amazon.it/s?k=Shelly+Plus+1PM&linkCode=ll2&tag=spazitec0f-21)** — smart relay with energy monitoring - **[ESP32 Development Board](https://www.amazon.it/s?k=ESP32+development+board&linkCode=ll2&tag=spazitec0f-21)** — ESP32 board for ESPHome sensors - **[Beelink Mini PC (Intel N100)](https://www.amazon.it/s?k=Beelink+Mini+PC+N100&linkCode=ll2&tag=spazitec0f-21)** — mini PC to run Home Assistant - [Mastering Home Assistant on Proxmox LXC: Setup Guide 2026](/en/blog/mastering-home-assistant-on-proxmox-lxc-setup-guide-2026/)]]> Fri, 10 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/mastering-home-assistant-solar-automation-your-guide-to-smart-energy-in-2026/ Home Assistant Solar Energy Battery Storage Smart Home Energy Automation Writing for AI Search Results in 2026: A Practical Guide https://daniele-messi.com/en/blog/writing-for-ai-search-results-in-2026-a-practical-guide/ Master writing for AI search results in 2026. Learn practical strategies for content creation, keyword optimization, and structuring your articles to rank higher in AI-driven search. Thu, 09 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/writing-for-ai-search-results-in-2026-a-practical-guide/ AI SEO Content Strategy LLM Optimization Search Ranking 2026 Tech Mastering Home Assistant on Proxmox LXC: Setup Guide 2026 https://daniele-messi.com/en/blog/mastering-home-assistant-on-proxmox-lxc-setup-guide-2026/ Unlock the power of home automation! This comprehensive 2026 guide walks you through setting up Home Assistant on Proxmox LXC for optimal performance and flexibility. **Open Source**: The blueprints from this article are available on GitHub: [Home Lab Automation Blueprints](https://github.com/danymexi/homelab-automation-blueprints). * **Resource Efficiency:** LXCs share the host kernel, resulting in significantly less overhead compared to VMs. This means more RAM and CPU cycles are available for [Home Assistant](https://www.home-assistant.io) and other services on your Proxmox server. * **Faster Boot Times:** Without needing to boot an entire guest OS kernel, LXC containers start up much faster. * **Simplified Management:** Proxmox's robust web interface makes managing LXCs, including backups, snapshots, and resource allocation, incredibly straightforward. * **Isolation:** While sharing the kernel, LXCs provide a good level of isolation, keeping your [Home Assistant](https://www.home-assistant.io) instance separate from other services on your Proxmox host. * **Portability:** LXC containers are relatively easy to move between Proxmox hosts, offering excellent flexibility for future upgrades or hardware changes. For those seeking an efficient `home assistant lxc` setup, this method strikes an excellent balance between performance and ease of management. ## Prerequisites for Your Home Assistant Proxmox Install Before diving into the `home assistant proxmox install` process, ensure you have the following: * **Proxmox VE Installed:** A running Proxmox VE 7.x or later instance (as of 2026, Proxmox 8.x is common) with internet access. * **Basic Linux Knowledge:** Familiarity with the Linux command line will be beneficial. * **Sufficient Resources:** Allocate at least 2GB of RAM (4GB recommended for a growing instance) and 2 CPU cores to your LXC. Storage depends on your needs, but 8-16GB is a good starting point. * **Static IP (Recommended):** Plan to assign a static IP address to your Home Assistant LXC for consistent network access. ## Step-by-Step: Creating the Proxmox LXC Container for Home Assistant ### 1. Download an LXC Template First, you need a base operating system template for your container. Debian 12 (Bookworm) is an excellent choice for stability. Access your Proxmox web interface, navigate to your local storage, and click on ## FAQ ### What is Home Assistant on Proxmox LXC? Home Assistant on Proxmox LXC refers to running the Home Assistant smart home automation platform within a Linux Container (LXC) on a Proxmox server. This setup provides a lightweight, efficient, and easily manageable environment compared to traditional virtual machines or dedicated hardware. ### Why choose LXC over a VM for Home Assistant? LXC containers offer several advantages, including significantly greater resource efficiency by sharing the host kernel, leading to less overhead and more available RAM and CPU. They also boast faster boot times because they don't need to boot an entire guest operating system kernel. ### Are there blueprints available for this setup? Yes, open-source blueprints for this Home Assistant on Proxmox LXC setup are available on GitHub under "Home Lab Automation Blueprints". These resources can assist users in configuring and automating their home lab environment effectively. ### What are the key benefits of this setup in 2026? This setup optimizes your smart home hub by providing a robust, resource-efficient, and easily manageable environment. It maximizes server resources, offers faster boot times, and simplifies administration through the Proxmox web interface, aligning with evolving smart home needs. ## Recommended Gear If you're building your own setup, here's the hardware I recommend: - **[Sonoff Zigbee 3.0 USB Dongle](https://www.amazon.it/s?k=Sonoff+Zigbee+3.0+dongle&linkCode=ll2&tag=spazitec0f-21)** — Zigbee coordinator for Home Assistant - **[Shelly Plus 1PM](https://www.amazon.it/s?k=Shelly+Plus+1PM&linkCode=ll2&tag=spazitec0f-21)** — smart relay with energy monitoring - **[ESP32 Development Board](https://www.amazon.it/s?k=ESP32+development+board&linkCode=ll2&tag=spazitec0f-21)** — ESP32 board for ESPHome sensors - **[Beelink Mini PC (Intel N100)](https://www.amazon.it/s?k=Beelink+Mini+PC+N100&linkCode=ll2&tag=spazitec0f-21)** — mini PC to run Home Assistant]]> Wed, 08 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/mastering-home-assistant-on-proxmox-lxc-setup-guide-2026/ Home Assistant Proxmox LXC Smart Home Automation Mastering Prompt Testing & CI/CD for AI Applications in 2026 https://daniele-messi.com/en/blog/mastering-prompt-testing-ci-cd-for-ai-applications-in-2026/ Discover essential strategies for effective prompt testing and building robust CI/CD pipelines for your AI prompts. Ensure quality, consistency, and reliability in your LLM-powered applications. Tue, 07 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/mastering-prompt-testing-ci-cd-for-ai-applications-in-2026/ prompt engineering prompt testing ci/cd llm development ai ops Mastering Prompt Engineering Claude: Beyond GPT-Centric Strategies for 2026 https://daniele-messi.com/en/blog/mastering-prompt-engineering-claude-beyond-gpt-centric-strategies-for-2026/ Unlock advanced prompt engineering for Claude. Discover unique Anthropic prompt tips and strategies that go beyond GPT, optimizing your AI interactions for 2026. Mon, 06 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/mastering-prompt-engineering-claude-beyond-gpt-centric-strategies-for-2026/ Prompt Engineering Claude AI Anthropic LLM Optimization AI Best Practices MCP Servers Explained: How to Connect AI to Your Tools https://daniele-messi.com/en/blog/mcp-servers-explained-connect-ai-to-everything/ What are MCP servers, how they work, and how to use them with Claude Code. A practical guide with real examples for developers. "Show me all users who signed up in the last 7 days" Claude will use the MCP tools to run the actual SQL query and return results. ## Building a Custom MCP Server Community servers cover common use cases, but the real power is building your own. Here is a minimal MCP server in TypeScript that exposes a weather tool: ```typescript import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js"; import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js"; import { z } from "zod"; const server = new McpServer({ name: "weather", version: "1.0.0", }); server.tool( "get-weather", "Get current weather for a city", { city: z.string().describe("City name") }, async ({ city }) => { const res = await fetch( `https://wttr.in/${encodeURIComponent(city)}?format=j1` ); const data = await res.json(); const current = data.current_condition[0]; return { content: [{ type: "text", text: `${city}: ${current.temp_C}°C, ${current.weatherDesc[0].value}` }] }; } ); const transport = new StdioServerTransport(); await server.connect(transport); ``` Register it in your settings: ```json { "mcpServers": { "weather": { "command": "node", "args": ["path/to/weather-server.js"] } } } ``` Now Claude Code can check the weather as part of its workflow. The pattern scales to anything: internal APIs, CRMs, deployment pipelines, monitoring systems. ## MCP Concepts: Tools, Resources, and Prompts MCP servers can expose three types of capabilities: **Tools** are functions the AI can call. They take parameters and return results. Examples: run a database query, send a Slack message, create a GitHub issue. ```typescript server.tool("create-issue", "Create a GitHub issue", { title: z.string(), body: z.string(), repo: z.string(), }, async ({ title, body, repo }) => { // Call GitHub API }); ``` **Resources** are data the AI can read. They are like files or endpoints the AI can access on demand. Examples: a configuration file, live metrics, documentation. ```typescript server.resource( "config", "app://config", async () => ({ contents: [{ uri: "app://config", text: JSON.stringify(appConfig), mimeType: "application/json", }] }) ); ``` **Prompts** are reusable prompt templates the server provides. They help standardize how the AI interacts with the tool. For most practical use cases, you will primarily build tools. ## Practical MCP Use Cases Here are real scenarios where MCP servers add immediate value: **Database assistant**: connect to PostgreSQL or SQLite. Ask Claude to analyze data, find anomalies, or generate reports without writing SQL manually. **Deployment helper**: wrap your CI/CD pipeline. Ask Claude to check build status, trigger deployments, or roll back a release. **Documentation search**: index your internal docs. Claude can search and reference them when answering questions about your codebase. **Monitoring bridge**: connect to Grafana or your metrics system. Ask Claude about error rates, latency trends, or capacity planning. **Content management**: connect to your CMS API. Ask Claude to draft, edit, and publish content directly. ## Security Considerations MCP servers run with the permissions of their process. A few rules: - **Principle of least privilege**: give each server only the access it needs. A read-only database server should not have write permissions. - **No secrets in config files**: use environment variables for API keys and tokens. - **Audit tool calls**: MCP servers log every tool invocation. Review these logs regularly. - **Network isolation**: if a server accesses sensitive systems, run it in a container or restrict its network access. ```json { "mcpServers": { "database": { "command": "node", "args": ["db-server.js"], "env": { "DB_URL": "postgresql://readonly:pass@localhost/mydb" } } } } ``` ## The MCP Ecosystem Today The ecosystem is growing fast. Anthropic maintains official servers for common integrations. The community has built hundreds more. Key resources: - **Official servers**: filesystem, GitHub, GitLab, Slack, Google Drive, PostgreSQL, SQLite, Puppeteer - **Community registry**: browse available servers and their capabilities - **SDK**: available in TypeScript, Python, Java, and Kotlin - **Claude Code**: has built-in MCP support, no additional setup needed beyond server configuration ## Getting Started Checklist 1. Pick one integration that would save you time daily 2. Check if a community MCP server already exists for it 3. If not, build a minimal server with one tool using the SDK 4. Add it to your Claude Code configuration 5. Test it, iterate, add more tools as needed The best MCP server is the one that removes a repetitive task from your workflow. Start small, start specific, and expand from there. ## FAQ ### What is the primary purpose of Model Context Protocol (MCP)? MCP is an open standard that allows AI assistants to connect to external tools and data sources in a standardized way. It aims to replace the fragmentation of custom integrations with a single, consistent protocol, functioning like a "USB port for AI." ### How does MCP simplify AI integration for developers? Before MCP, integrating AI with a new tool required building a specific plugin for each instance. MCP eliminates this by providing a universal protocol that any tool can implement, enabling AI applications like Claude Code to access various services through a consistent interface. ### What are the main components of the MCP architecture? The MCP architecture consists of three primary parts: the MCP Host, which is the AI application sending requests; the MCP Server, a lightweight process exposing specific tools or resources; and the Transport layer, which handles communication via stdio for local processes or SSE for remote HTTP connections. ### What kinds of external tools can AI connect to using MCP Servers? MCP Servers enable AI to connect to a wide range of external tools and data sources. This includes databases, APIs, file systems, and specific applications like Slack, GitHub, and monitoring dashboards, allowing the AI to perform actions beyond just generating text.]]> Sun, 05 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/mcp-servers-explained-connect-ai-to-everything/ AI Claude Code Development Proxmox Home Lab: A Practical Guide to Self-Hosting in 2026 https://daniele-messi.com/en/blog/proxmox-home-lab-guide-self-hosting-2026/ Learn how to set up a Proxmox home lab for self-hosting websites, apps, and automations. From hardware to containers, a hands-on guide. **Open Source**: Check out [Proxmox Home Lab Scripts](https://github.com/danymexi/proxmox-homelab-scripts) on GitHub for the automation scripts used in this setup. Self-hosting is not about replacing AWS. It is about running the things that make sense locally — personal websites, automation scripts, home dashboards, development environments — while keeping cloud services for what they do best. ## Choosing the Right Hardware You do not need enterprise-grade servers. A mini PC with 16-32 GB of RAM and an NVMe SSD is more than enough to run 5-10 containers comfortably. Here are practical options: | Hardware | RAM | Storage | Power Draw | Price Range | |----------|-----|---------|------------|-------------| | Intel NUC 13 | 16-64 GB | NVMe | ~15W idle | €300-500 | | Beelink SER5 | 16-32 GB | NVMe | ~12W idle | €250-400 | | Lenovo ThinkCentre Tiny | 16-32 GB | NVMe + SATA | ~10W idle | €150-300 (refurb) | | Dell OptiPlex Micro | 16-64 GB | NVMe + SATA | ~12W idle | €150-350 (refurb) | A refurbished ThinkCentre or OptiPlex with 32 GB RAM is often the best value. At 10-15W idle, the annual electricity cost is roughly €15-25. ## Installing Proxmox VE Download the [Proxmox VE](https://pve.proxmox.com/wiki/Main_Page) ISO from the official site. Flash it to a USB drive using Balena Etcher or Rufus, boot from it, and follow the installer. The entire process takes about 10 minutes. After installation, access the web interface at `https://your-ip:8006`. The first thing to do is disable the enterprise repository and enable the no-subscription repository: ```bash # Disable enterprise repo sed -i 's/^deb/#deb/' /etc/apt/sources.list.d/pve-enterprise.list # Add no-subscription repo echo "deb http://download.proxmox.com/debian/pve bookworm pve-no-subscription" > /etc/apt/sources.list.d/pve-no-subscription.list # Update apt update && apt dist-upgrade -y ``` ## LXC Containers vs Virtual Machines Proxmox supports both LXC containers and full virtual machines. For most self-hosting use cases, LXC containers are the better choice: - **Startup time**: containers boot in 1-2 seconds vs 15-30 seconds for VMs - **Resource usage**: containers share the host kernel, using far less RAM - **Disk space**: a container template is 100-200 MB vs 2-10 GB for a VM image - **Performance**: near-native I/O and CPU performance Use VMs only when you need a different kernel (Windows, Home Assistant OS) or full isolation for security-sensitive workloads. ## A Practical Container Setup Here is a real-world setup that runs multiple services on a single mini PC with 32 GB RAM: ``` LXC 101 — WireGuard VPN (256 MB RAM) LXC 102 — Web App (Node.js) (512 MB RAM) LXC 103 — Personal Website (512 MB RAM) LXC 104 — Blog CMS (1 GB RAM) LXC 105 — Automation Service (512 MB RAM) LXC 106 — Monitoring Dashboard (512 MB RAM) VM 200 — [Home Assistant](https://www.home-assistant.io) OS (2 GB RAM) ``` Total RAM used: roughly 5.5 GB. That leaves over 26 GB free for peaks, caching, and future services. ## Creating Your First Container From the Proxmox web UI, download a Debian 12 template under local storage → CT Templates. Then create a container: ```bash # CLI alternative pct create 103 local:vztmpl/debian-12-standard_12.2-1_amd64.tar.zst \ --hostname my-website \ --memory 512 \ --cores 2 \ --net0 name=eth0,bridge=vmbr0,ip=dhcp \ --rootfs local-lvm:8 \ --start 1 ``` Enter the container and install what you need: ```bash pct enter 103 apt update && apt install -y curl git nodejs npm ``` ## Exposing Services Securely with Cloudflare Tunnel Never expose port 443 or 80 directly to the internet. Cloudflare Tunnel creates an encrypted outbound connection from your server to Cloudflare's edge, with no inbound ports needed. Install `cloudflared` inside a container: ```bash curl -L https://github.com/cloudflare/cloudflared/releases/latest/download/cloudflared-linux-amd64.deb -o cloudflared.deb dpkg -i cloudflared.deb cloudflared tunnel login cloudflared tunnel create my-tunnel ``` Configure the tunnel to route traffic to your local services: ```yaml # ~/.cloudflared/config.yml tunnel: your-tunnel-id credentials-file: /root/.cloudflared/your-tunnel-id.json ingress: - hostname: mysite.example.com service: http://192.168.1.103:4321 - hostname: app.example.com service: http://192.168.1.104:3000 - service: http_status:404 ``` Run it as a system service: ```bash cloudflared service install systemctl enable --now cloudflared ``` Your services are now accessible via your domain with HTTPS, DDoS protection, and zero open ports on your router. ## Backups: The Non-Negotiable Step A home lab without backups is a liability. Proxmox has built-in backup support. Schedule weekly backups from the Datacenter → Backup menu, or via CLI: ```bash # Backup container 103 to local storage vzdump 103 --dumpdir /var/lib/vz/dump --compress zstd --mode snapshot ``` For off-site protection, sync backups to a cloud provider using rclone: ```bash rclone sync /var/lib/vz/dump remote:proxmox-backups --transfers 2 ``` ## Monitoring with a Lightweight Stack You do not need Grafana and Prometheus for a home lab. A simple approach: install `htop` and `btop` for interactive monitoring, and set up a basic health check script: ```bash #!/bin/bash # Check if all containers are running for ct in 101 102 103 104 105 106; do status=$(pct status $ct | awk '{print $2}') if [ "$status" != "running" ]; then echo "WARNING: Container $ct is $status" fi done ``` Run it via cron and pipe failures to a notification service. ## What I Learned Running a Home Lab for Two Years The biggest lesson is to keep things simple. It is tempting to add monitoring dashboards, reverse proxies, container orchestration, and CI/CD pipelines. Most of it is unnecessary for personal projects. What actually matters: - **Backups** that you have tested restoring at least once - **Cloudflare Tunnel** for secure external access without port forwarding - **LXC containers** for isolation without the overhead of VMs - **A written list** of what runs where, so you can rebuild after a failure A home lab is not a production environment. It is a workshop. Keep it maintainable, keep it documented, and do not over-engineer. ## FAQ ### Why choose Proxmox for a home lab over cloud services? Proxmox provides full ownership of your infrastructure, eliminating recurring monthly fees and vendor lock-in associated with cloud services. It offers the freedom to experiment and run personal services locally without billing surprises. ### What kind of hardware is recommended for a Proxmox home lab? A mini PC with 16-32 GB of RAM and an NVMe SSD is sufficient for running 5-10 containers comfortably. Options include Intel NUC, Beelink SER5, or refurbished Lenovo ThinkCentre Tiny and Dell OptiPlex Micro models. ### What is the typical power consumption of a recommended home lab setup? Recommended mini PC setups, such as a refurbished ThinkCentre Tiny, typically have a very low idle power draw of around 10-15W. This makes them energy-efficient for continuous operation. ### Is self-hosting meant to replace services like AWS? No, self-hosting with Proxmox is not intended to replace large-scale cloud providers like AWS. Instead, it focuses on efficiently running specific local services such as personal websites, home automation, dashboards, and development environments. ## Recommended Gear If you're building your own setup, here's the hardware I recommend: - **[Beelink Mini PC (Intel N100)](https://www.amazon.it/s?k=Beelink+Mini+PC+N100&linkCode=ll2&tag=spazitec0f-21)** — mini PC for Proxmox home lab - **[Samsung 870 EVO SSD 1TB](https://www.amazon.it/s?k=Samsung+870+EVO+1TB&linkCode=ll2&tag=spazitec0f-21)** — SSD for VM storage - **[Crucial RAM 32GB DDR4](https://www.amazon.it/s?k=Crucial+32GB+DDR4+SODIMM&linkCode=ll2&tag=spazitec0f-21)** — RAM upgrade for virtualization]]> Sun, 05 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/proxmox-home-lab-guide-self-hosting-2026/ Home Lab Self-Hosting Tutorial Proxmox Ollama Setup: Self-Hosted AI Server for Developers in 2026 https://daniele-messi.com/en/blog/proxmox-ollama-setup-self-hosted-ai-server-for-developers-in-2026/ Unlock local AI power with a robust Proxmox Ollama setup. This guide details how to build a self-hosted AI server using LXC for developers in 2026. **Open Source**: Check out [Proxmox Home Lab Scripts](https://github.com/danymexi/proxmox-homelab-scripts) on GitHub for the automation scripts used in this setup. ## Why Self-Host AI in 2026? The landscape of AI development has rapidly evolved, and with it, the need for private, performant, and cost-effective solutions. Relying solely on cloud-based LLMs comes with inherent limitations: * **Data Privacy and Security:** Sensitive data processed by cloud LLMs raises significant privacy concerns. A **self-hosted AI** solution keeps your data entirely within your control, crucial for proprietary projects or confidential information. * **Cost Efficiency:** While cloud APIs offer convenience, their cumulative costs, especially for frequent or large-scale inference, can quickly become prohibitive. Running models locally leverages your existing hardware, eliminating ongoing per-token or per-query charges. * **Customization and Control:** Self-hosting provides complete control over the environment, allowing you to fine-tune system resources, install specific dependencies, and experiment with various models and configurations without platform restrictions. * **Offline Capability:** Develop and test AI applications without an internet connection, ideal for remote environments or ensuring continuous operation despite network outages. * **Performance:** With optimized hardware and direct access, a well-configured **local LLM server** can often outperform cloud solutions for specific tasks, especially when dealing with low-latency requirements. ## Prerequisites for Your Proxmox Ollama Setup Before diving into the installation, ensure your [Proxmox VE](https://pve.proxmox.com/wiki/Main_Page) server meets the following requirements. This guide assumes you already have Proxmox VE installed and running. * **[Proxmox VE](https://pve.proxmox.com/wiki/Main_Page) Server:** A fully operational Proxmox VE 7.x or 8.x (or newer versions available in 2026) installation. * **Hardware Resources:** * **CPU:** A modern multi-core CPU (e.g., Intel i5/i7/i9, Xeon, AMD Ryzen 5/7/9, EPYC) with virtualization extensions enabled (VT-x/AMD-V). * **RAM:** At least 16GB RAM is recommended, with 32GB+ being ideal for running larger models or multiple models concurrently. Ollama models load into RAM. * **Storage:** A fast SSD is highly recommended for storing Ollama models, which can range from a few gigabytes to tens of gigabytes each. Ensure ample free space (100GB+). * **GPU (Optional but Recommended):** While Ollama can run on CPU, a compatible NVIDIA GPU (with CUDA support) or an AMD GPU (with ROCm support) will significantly accelerate inference. If using a GPU, you will likely need to pass it through to a virtual machine (VM) rather than an LXC container for optimal performance and driver compatibility, or consider a more advanced LXC setup with explicit GPU passthrough if your Proxmox version and kernel support it robustly by 2026. For simplicity, this guide focuses on a CPU-only LXC setup, which is excellent for learning and many use cases. * **Network Access:** Your Proxmox server should have internet access to download Ollama and its models. ## Setting Up an LXC Container for Ollama on Proxmox Using an LXC (Linux Container) offers a lightweight and efficient way to deploy Ollama without the overhead of a full virtual machine. Here’s how to create and configure your **ollama proxmox lxc**. ### 1. Create a New LXC Container Log in to your Proxmox web interface and navigate to your node. Click "Create CT". * **General:** * **Hostname:** `ollama-server` (or your preferred name) * **Password:** Set a strong password. * **Unprivileged container:** **Crucially, tick this box.** Unprivileged containers are more secure. * **Template:** Select a recent Ubuntu or Debian template (e.g., `ubuntu-24.04-standard_latest.tar.zst` or `debian-12-standard_latest.tar.zst`). * **Disks:** * **Disk size:** At least 30GB (more if you plan to store many models). * **CPU:** Allocate at least 4 cores; more is better for CPU inference. * **Memory:** Allocate at least 8GB (8192 MB); 16GB+ is ideal. * **Network:** Configure a static IP address or use DHCP, ensuring it's accessible from your local network. * **DNS:** Use your preferred DNS server. Once configured, finish the creation process. ### 2. Update and Install Dependencies in the LXC Start your new `ollama-server` LXC and open its console in the Proxmox web UI or SSH into it. First, update the package list and upgrade existing packages: ```bash sudo apt update && sudo apt upgrade -y ``` Install `curl` if it's not already present, as it's needed for the Ollama installation script: ```bash sudo apt install -y curl ``` ### 3. Install Ollama Now, install Ollama using its official installation script. This script handles the necessary setup, including creating a systemd service. ```bash curl -fsSL https://ollama.com/install.sh | sh ``` After the installation, Ollama should be running as a service. You can verify its status: ```bash sudo systemctl status ollama ``` ### 4. Configure Ollama for Network Access (Optional but Recommended) By default, Ollama only listens on `localhost` (127.0.0.1). To access your **ollama proxmox lxc** from other machines on your network, you need to configure it to listen on all interfaces. This is vital for your **Proxmox Ollama setup** to serve other clients. Edit the systemd service file to set the `OLLAMA_HOST` environment variable. First, stop the Ollama service: ```bash sudo systemctl stop ollama ``` Then, edit the systemd override file (create if it doesn't exist): ```bash sudo systemctl edit ollama.service ``` Add the following lines to the file, then save and exit: ```ini [Service] Environment="OLLAMA_HOST=0.0.0.0" ``` Reload the systemd daemon and start Ollama again: ```bash sudo systemctl daemon-reload sudo systemctl start ollama ``` Now, Ollama will be accessible from your LXC's IP address on port 11434. ## Running Your First Local LLM with Ollama With Ollama installed and configured, it's time to download and run your first **local LLM server** model. We'll use Llama 3, a popular choice in 2026 for its balance of performance and accessibility. From within your Ollama LXC, simply run: ```bash ollama run llama3 ``` Ollama will automatically download the Llama 3 model (if not already present) and then present you with a prompt. You can now interact with the LLM directly in your console: ``` >>> What is the capital of France? Paris is the capital of France. >>> ``` To list available models and models you've downloaded: ```bash ollama list ``` To pull other models, simply replace `llama3` with your desired model (e.g., `ollama run mistral` or `ollama run codellama`). ## Optimizing Your Local LLM Server Performance To get the most out of your **ollama proxmox lxc** and ensure your **local LLM server** runs efficiently: * **Resource Allocation:** In Proxmox, ensure your LXC has sufficient CPU cores and RAM allocated. LLMs are memory-intensive, so allocating enough RAM is crucial to prevent swapping, which severely degrades performance. * **Storage:** Use SSD storage for your LXC. Model loading and swapping benefit immensely from high I/O speeds. * **Model Quantization:** Experiment with different model sizes and quantizations (e.g., `llama3:8b-instruct-q4_K_M`). Smaller, more quantized models require less RAM and CPU, but may have slightly reduced quality. * **GPU Acceleration (Advanced):** If you have a compatible GPU and are comfortable with more complex setups, consider passing through the GPU to a dedicated VM instead of an LXC. Proxmox's PCI passthrough feature can assign the GPU directly to a VM, allowing it to utilize native drivers and achieve maximum performance with Ollama's GPU acceleration. While LXC GPU passthrough has improved by 2026, a VM often offers a more straightforward path for robust driver support. ## Advanced Proxmox Ollama Setup Considerations * **Firewall Configuration:** If you have a firewall on your Proxmox host, ensure that port 11434 (Ollama's default port) is open to allow external access to your **Proxmox Ollama setup**. * **Reverse Proxy:** For enhanced security and easier management, consider setting up a reverse proxy (e.g., Nginx or Caddy) in front of your Ollama LXC. This allows you to add SSL/TLS encryption, custom domains, and potentially authentication. * **Backups:** Regularly back up your Ollama LXC in Proxmox. This ensures you can quickly restore your **local LLM server** with all models and configurations in case of an issue. * **Updates:** Keep your LXC's operating system and Ollama updated. Regular updates bring performance improvements, bug fixes, and security patches. ## Conclusion By following this guide, you've successfully transformed your Proxmox server into a powerful **Proxmox Ollama setup**, ready to serve as your dedicated **self-hosted AI** development environment. You now have a flexible, private, and cost-effective **local LLM server** at your fingertips, empowering you to innovate and experiment with LLMs without external dependencies. The year 2026 truly marks a golden age for local AI, and your new setup is at the forefront. Dive in, experiment, and unlock the full potential of AI development on your own terms! ## FAQ ### What is the primary benefit of a Proxmox Ollama setup for developers in 2026? The primary benefit is the ability to build a powerful local LLM server, offering unparalleled flexibility, performance, and control. This setup eliminates reliance on cloud APIs, addressing concerns about data privacy, security, and cumulative costs. ### How does self-hosting AI address data privacy concerns? Self-hosting AI with Proxmox and Ollama ensures that all sensitive data processed by LLMs remains entirely within your own infrastructure. This is crucial for proprietary projects or confidential information, as it keeps your data under your direct control, unlike cloud-based solutions. ### Can this setup help reduce costs compared to cloud LLMs? Yes, a self-hosted Proxmox Ollama solution offers significant cost efficiency. While cloud APIs provide convenience, their cumulative costs for frequent or large-scale inference can quickly become prohibitive, making a local server a more economical choice in the long run. ### Are there any automation tools available for this Proxmox Ollama setup? Yes, the article mentions "Proxmox Home Lab Scripts" on GitHub as open-source automation scripts used in this setup. Developers can leverage these resources to streamline the deployment and management of their local LLM server. ## Recommended Gear If you're building your own setup, here's the hardware I recommend: - **[Beelink Mini PC (Intel N100)](https://www.amazon.it/s?k=Beelink+Mini+PC+N100&linkCode=ll2&tag=spazitec0f-21)** — mini PC for Proxmox home lab - **[Samsung 870 EVO SSD 1TB](https://www.amazon.it/s?k=Samsung+870+EVO+1TB&linkCode=ll2&tag=spazitec0f-21)** — SSD for VM storage - **[Crucial RAM 32GB DDR4](https://www.amazon.it/s?k=Crucial+32GB+DDR4+SODIMM&linkCode=ll2&tag=spazitec0f-21)** — RAM upgrade for virtualization - [Proxmox Home Lab: A Practical Guide to Self-Hosting in 2026](/en/blog/proxmox-home-lab-guide-self-hosting-2026/)]]> Sun, 05 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/proxmox-ollama-setup-self-hosted-ai-server-for-developers-in-2026/ Proxmox Ollama Self-Hosted AI LLM LXC Context Engineering vs Prompt Engineering: The 2026 Paradigm Shift https://daniele-messi.com/en/blog/context-engineering-vs-prompt-engineering-the-2026-paradigm-shift/ Explore how context engineering has fundamentally evolved beyond prompt engineering by 2026, focusing on dynamic knowledge integration and agentic systems. Understand the practical shifts for AI development and future-proofing your LLM applications. Sat, 04 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/context-engineering-vs-prompt-engineering-the-2026-paradigm-shift/ Context Engineering Prompt Engineering LLM Development Agentic AI AI in 2026 MCP Security: Essential Developer Guide for 2026 and Beyond https://daniele-messi.com/en/blog/mcp-security-essential-developer-guide-for-2026-and-beyond/ Mastering MCP security is crucial for modern developers. This guide covers authentication, common vulnerabilities, server security, and best practices to protect your Microservices, Cloud, and Platform architectures. Thu, 02 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/mcp-security-essential-developer-guide-for-2026-and-beyond/ MCP Security Cloud Security Microservices Developer Best Practices API Security Build Your First MCP Server Step by Step in 2026 https://daniele-messi.com/en/blog/build-your-first-mcp-server-step-by-step-in-2026/ Learn how to build your first MCP server from scratch in 2026 with this comprehensive guide. Follow our step-by-step tutorial to deploy a robust Model Context Protocol server for your AI applications. str: # In a real application, you'd integrate with an LLM here (e.g., OpenAI, Hugging Face, custom model) # The context_hint would guide the [prompt engineering](/en/blog/mastering-prompt-engineering-claude-beyond-gpt-centric-strategies-for-2026/) or model selection. if "technical" in context_hint.lower(): return f"[Technical Summary]: A concise analysis of the provided data, emphasizing key operational aspects. (Text length: {len(text)})." elif "marketing" in context_hint.lower(): return f"[Marketing Pitch]: Discover the compelling value proposition and unique selling points derived from the text. (Text length: {len(text)})." else: return f"[General Summary]: A brief overview of the main points in the text. (Text length: {len(text)})." # --- MCP Endpoint Definition --- @mcp_server.mcp_endpoint( path="/summarize", input_model=ContextualSummaryInput, output_model=ContextualSummaryOutput, description="Provides a contextual summary of input text." ) async def contextual_summarize_service( input_data: ContextualSummaryInput, mcp_context: MCPContext # MCP framework injects the context ) -> ContextualSummaryOutput: """Process text to generate a summary based on the provided MCP context hint.""" try: print(f"Processing request for session: {mcp_context.session_id} with hint: {mcp_context.context_hint}") # Simulate a delay for processing await asyncio.sleep(0.1) summary = mock_summarize(input_data.text, mcp_context.context_hint) return ContextualSummaryOutput( summary=summary, context_applied=mcp_context.context_hint ) except Exception as e: raise HTTPException(status_code=500, detail=f"Internal server error: {str(e)}") # Optional: Add a simple root endpoint for health check @app.get("/", tags=["Health Check"]) async def read_root(): return {"message": "MCP Contextual Summarizer Server is running!"} import asyncio # Required for async operations ``` **Explanation:** 1. **`FastAPI` and `MCPServer`:** We initialize a FastAPI app and then wrap it with `MCPServer`, which is responsible for handling MCP-specific routing and context management. 2. **`MCPContextManager`:** This component (provided by the framework) handles the lifecycle and storage of `MCPContext` objects for different sessions. 3. **`mock_summarize`:** This function simulates your actual AI model integration. In a production environment of 2026, this would involve calling a large language model (LLM) API or an on-device model, potentially with sophisticated [prompt engineering](/en/blog/prompt-engineering-for-developers-practical-guide-code-examples/) guided by `context_hint`. 4. **`@mcp_server.mcp_endpoint`:** This decorator registers our `contextual_summarize_service` as an MCP-compliant endpoint. It automatically handles input validation (using `input_model`), output serialization (using `output_model`), and crucially, injects the `MCPContext` object into your service function. The `MCPContext` is either retrieved from an existing session or initialized based on the request. ## Running and Testing Your MCP Server ### 1. Run the Server From your terminal, in the `mcp_server_env` virtual environment, run: ```bash uvicorn main:app --reload --host 0.0.0.0 --port 8000 ``` You should see output indicating that Uvicorn is running your FastAPI application, typically on `http://0.0.0.0:8000`. ### 2. Test with `curl` Open another terminal and send some requests. First, a request without a specific `context_hint` in the MCP context: ```bash curl -X POST "http://localhost:8000/summarize" \ -H "Content-Type: application/json" \ -H "X-MCP-Session-ID: session-123" \ -d '{"text": "The new quantum computing algorithm achieved unprecedented speed, reducing processing time by 99% for complex cryptographic tasks. This breakthrough promises to revolutionize data security by 2030."}' ``` Expected Output: ```json { ## FAQ ### What is the Model Context Protocol (MCP)? The Model Context Protocol (MCP) is a standardized communication layer designed to facilitate the exchange of context and model inferences between various AI components and applications. It provides a structured approach to managing dynamic context across multiple model interactions. ### Why is building an MCP server important in 2026? Building an MCP server is an essential skill in 2026 because MCP is rapidly becoming the backbone for advanced AI applications. It's crucial for leveraging the skyrocketing demand for robust, scalable, and context-aware AI systems. ### What are the key benefits of using MCP? MCP offers several key benefits, including enhanced contextual awareness, which allows systems to maintain and update dynamic context. It also ensures interoperability, enabling different models to communicate effectively, and provides scalability for integrating new models seamlessly. ## Related Articles - [AI Coding Agents Are Changing How We Ship Software](/en/blog/ai-coding-agents-are-changing-how-we-ship-software/) - [Building AI-Powered Automations: A Developer's Practical Guide](/en/blog/building-ai-powered-automations-a-developer-s-practical-guide/) - [MCP Servers Explained: How to Connect AI to Your Tools](/en/blog/mcp-servers-explained-connect-ai-to-everything/) - [SEO for Personal Websites in 2026: Your Ultimate Guide](/en/blog/seo-for-personal-websites-in-2026-your-ultimate-guide/) - [Writing for AI Search Results in 2026: A Practical Guide](/en/blog/writing-for-ai-search-results-in-2026-a-practical-guide/)]]> Wed, 01 Apr 2026 00:00:00 GMT https://daniele-messi.com/en/blog/build-your-first-mcp-server-step-by-step-in-2026/ MCP Server Development Model Context Protocol Backend AI Infrastructure Building AI-Powered Automations: A Developer's Practical Guide https://daniele-messi.com/en/blog/building-ai-powered-automations-a-developer-s-practical-guide/ Learn to build intelligent automations with AI. Includes code examples, best practices, and real-world implementation strategies for developers. self.get_baseline_duration() * 2: self.send_alert(f"Slow execution detected: {automation_name}") if not success: self.increment_error_count() def generate_performance_report(self): return { 'period': 'last_24h', 'executions': len(self.recent_executions()), 'success_rate': self.calculate_success_rate(), 'recommendations': self.generate_recommendations() } ``` ## Scaling and Production Considerations When deploying AI automations at scale: 1. **Rate Limiting**: Implement proper rate limiting for API calls 2. **Caching**: Cache AI responses for repeated inputs 3. **Queue Management**: Use message queues for high-volume processing 4. **Cost Control**: Monitor and cap AI API usage 5. **Security**: Sanitize inputs and validate outputs ## Conclusion Building AI-powered automations opens up possibilities that traditional rule-based systems simply can't match. By combining the intelligence of modern AI models with robust automation frameworks, you can create systems that adapt, learn, and make nuanced decisions. Start small with simple classification or routing tasks, then gradually expand to more complex scenarios as you gain confidence. Remember to implement proper monitoring, error handling, and feedback loops from the beginning—these will be crucial as your automations grow in complexity and importance. The key is to view AI not as a replacement for human judgment, but as an intelligent assistant that can handle routine decisions while escalating complex cases appropriately. With this approach, you'll build automations that are both powerful and reliable. ## FAQ ### What makes AI-powered automations different from traditional automations? AI-powered automations distinguish themselves by their ability to adapt, learn from data patterns, and make intelligent decisions based on context. This contrasts with traditional automations that follow rigid if-then logic, allowing AI systems to handle more dynamic and complex scenarios. ### What are some practical applications of AI-powered automations? Practical applications include streamlining customer support, automating content moderation, and creating dynamic workflows that respond to changing conditions. The article highlights a smart email classifier as a concrete example of an AI-powered automation. ### What essential tools and frameworks are needed to build AI automations? Developers will need core technologies such as Python with libraries like `langchain` and `openai`, API access to AI services (e.g., OpenAI GPT, Anthropic Claude), workflow orchestration tools like Zapier or n8n, and a database for storing automation states and results. ### Is setting up an environment for AI automation complex? No, setting up the basic environment for AI automation is relatively straightforward. Key libraries such as `openai`, `langchain`, `python-dotenv`, and `requests` can be installed quickly using a simple `pip install` command, enabling developers to efficiently begin building intelligent systems.]]> Mon, 30 Mar 2026 00:00:00 GMT https://daniele-messi.com/en/blog/building-ai-powered-automations-a-developer-s-practical-guide/ AI Automation Claude Code vs Cursor vs Copilot: An Honest Comparison for 2026 https://daniele-messi.com/en/blog/claude-code-vs-cursor-vs-copilot-an-honest-comparison-for-2026/ Navigating the AI coding landscape in 2026? This deep dive into Claude Code vs Cursor vs Copilot helps you choose your best AI coding assistant for superior development workflows. **Open Source**: This article is part of the [Astro Content Engine](https://github.com/danymexi/astro-content-engine) project — an open-source SEO content pipeline for Astro blogs. We'll dive into their unique strengths, weaknesses, and ideal use cases, examining how each stands up to the demands of modern software development, from intricate system design to rapid prototyping. ## Claude Code: The Contextual Reasoning Powerhouse Anthropic's [Claude Code](https://docs.anthropic.com/en/docs/claude-code), a specialized derivative of the Claude 3.5 Sonnet model, has rapidly gained a reputation for its exceptional contextual understanding and reasoning capabilities. Launched in late 2025, it quickly distinguished itself by leveraging a massive context window, allowing it to process entire codebases, documentation, and even architectural diagrams with remarkable coherence. ### Strengths of Claude Code * **Unparalleled Contextual Understanding:** [Claude Code](https://docs.anthropic.com/en/docs/claude-code) can digest thousands of lines of code across multiple files, making it superb for understanding complex systems, identifying subtle bugs, and proposing architectural improvements. When you're dealing with a large monorepo or an intricate microservices architecture, this is a game-changer. * **Advanced Reasoning and Problem Solving:** Beyond simple code completion, Claude Code excels at complex problem-solving. It can debug elusive issues by tracing logic across disparate components, suggest sophisticated algorithms, or even refactor large sections of code with a deep understanding of dependencies. * **Multi-Modal Capabilities (2026 Update):** The 2026 iteration of Claude Code integrates vision capabilities, allowing it to interpret UI mockups or whiteboard diagrams and translate them into code, or even analyze screenshots of errors for debugging. ### Weaknesses of Claude Code * **Integration (as of early 2026):** While improving rapidly, Claude Code's deep IDE integration isn't always as seamless or real-time as Cursor's native environment or Copilot's ubiquitous plugins. It often works best as an on-demand, chat-based assistant for larger tasks rather than constant inline suggestions. * **Latency for Real-time Suggestions:** For lightning-fast, character-by-character code completion, Claude Code might occasionally feel slightly slower than Copilot due to its deeper processing. ### Ideal Use Case for Claude Code Developers working on greenfield projects requiring thoughtful architectural design, complex refactoring of legacy systems, or deep-dive debugging will find Claude Code invaluable. It's also excellent for generating comprehensive documentation or explaining intricate code sections. ## Cursor: The AI-Native IDE Experience Cursor isn't just an AI assistant; it's an AI-native IDE built from the ground up to integrate AI into every aspect of your coding workflow. By 2026, Cursor has matured significantly, offering a highly polished and intuitive environment where AI is a first-class citizen. ### Strengths of Cursor * **Deepest IDE Integration:** As an IDE, Cursor offers unparalleled integration of AI features. Its chat interface is always present, allowing you to ask questions about your code, generate new files, or refactor selections directly within the editor. This tight coupling makes the AI feel like a natural extension of the development environment. * **Effortless Refactoring and Code Generation:** Cursor excels at generating new files, functions, or even entire classes based on natural language prompts. Its ## FAQ ### What is Claude Code? Claude Code is a specialized AI coding assistant derived from Anthropic's Claude 3.5 Sonnet model. It is designed to assist developers with coding tasks, leveraging advanced contextual understanding and reasoning capabilities. ### When was Claude Code launched? Claude Code was launched in late 2025. Despite its recent introduction, it quickly gained a strong reputation in the competitive market of AI coding assistants by 2026. ### What makes Claude Code stand out among AI coding assistants? Claude Code distinguishes itself primarily through its exceptional contextual understanding and reasoning capabilities. It utilizes a massive context window, allowing it to process entire codebases and extensive documentation for more accurate and relevant suggestions. ### Is Claude Code suitable for complex projects? Yes, Claude Code is particularly well-suited for complex projects. Its ability to handle large context windows and perform deep contextual reasoning makes it highly effective for intricate system design and demanding software development tasks. ## Recommended Gear If you're building your own setup, here's the hardware I recommend: - **[Logitech MX Keys S](https://www.amazon.it/s?k=Logitech+MX+Keys+S&linkCode=ll2&tag=spazitec0f-21)** — keyboard for productive coding sessions - [10 Claude Code Automations You Should Try Today](/en/blog/10-claude-code-automations-you-should-try/) - [Claude Code Hooks: The Complete Guide to Automation & Workflow in 2026](/en/blog/claude-code-hooks-the-complete-guide-to-automation-workflow-in-2026/) - [Claude Code Sub-Agents: Practical Examples & Advanced Strategies for 2026](/en/blog/claude-code-sub-agents-practical-examples-advanced-strategies-for-2026/) - [CLAUDE.md Best Practices: Crafting the Perfect AI Project File for 2026](/en/blog/claude-md-best-practices-crafting-the-perfect-ai-project-file-for-2026/) - [Getting Started with Claude Code: The Ultimate Guide](/en/blog/getting-started-with-claude-code/)]]> Mon, 30 Mar 2026 00:00:00 GMT https://daniele-messi.com/en/blog/claude-code-vs-cursor-vs-copilot-an-honest-comparison-for-2026/ AI Coding Assistant Claude Code Cursor GitHub Copilot Developer Tools Prompt Engineering for Developers: Practical Guide & Code Examples https://daniele-messi.com/en/blog/prompt-engineering-for-developers-practical-guide-code-examples/ Master prompt engineering with practical techniques, code examples, and testing strategies for building robust AI-integrated applications. self.max_tokens and self.conversation_history: removed = self.conversation_history.pop(0) total_tokens -= removed['tokens'] def build_prompt_with_context(self, new_prompt): context = "\n".join([ f"Previous: {item['prompt']}\nResponse: {item['response']}" for item in self.conversation_history[-3:] # Last 3 interactions ]) return f"{context}\n\nCurrent: {new_prompt}" ``` ## Error Handling and Validation Robust [prompt engineering](/en/blog/mastering-prompt-engineering-claude-beyond-gpt-centric-strategies-for-2026/) includes anticipating and handling edge cases. Build validation into your prompt workflows: ```python def validate_ai_response(response, expected_format): """Validate AI response matches expected format""" validation_prompt = f""" Analyze if this response matches the required format: Response: {response} Expected format: {expected_format} Return only: VALID or INVALID with brief reason """ # This creates a validation layer for AI outputs return validation_prompt # Example usage for API response generation def generate_api_documentation(endpoint_data): main_prompt = f""" Generate API documentation for this endpoint: {endpoint_data} Required format: - Endpoint: [URL] - Method: [GET/POST/etc] - Parameters: [name: type - description] - Response: [JSON structure] - Example: [curl command] """ # Add error handling fallback_prompt = """ The previous response was invalid. Generate a simple API doc with: 1. Basic endpoint info 2. One example parameter 3. Simple JSON response structure """ return main_prompt, fallback_prompt ``` ## Advanced Techniques: Chain-of-Thought and Iterative Refinement For complex tasks, break them into smaller, logical steps: ```python def complex_debugging_prompt(error_log, codebase_context): return f""" Debug this error using step-by-step analysis: Step 1: Identify the error type and location Error log: {error_log} Step 2: Analyze the surrounding code context Context: {codebase_context} Step 3: Determine root cause Consider: data types, null values, async issues, dependencies Step 4: Propose specific fixes Provide: exact code changes, not general suggestions Step 5: Suggest prevention strategies Include: testing approaches, validation checks Work through each step systematically. """ ``` ## Performance Optimization Strategies Monitor and optimize your prompts for speed and cost: ```python import time from typing import Dict, List class PromptOptimizer: def __init__(self): self.performance_metrics = {} def benchmark_prompt(self, prompt_name: str, prompt: str, iterations: int = 5): """Benchmark prompt performance""" times = [] for _ in range(iterations): start = time.time() # Your AI API call here response = self.call_ai_api(prompt) end = time.time() times.append(end - start) avg_time = sum(times) / len(times) token_count = self.estimate_tokens(prompt) self.performance_metrics[prompt_name] = { 'avg_response_time': avg_time, 'token_count': token_count, 'cost_estimate': token_count * 0.0001 # Rough estimate } return self.performance_metrics[prompt_name] def optimize_prompt_length(self, prompt: str) -> str: """Remove unnecessary words while preserving meaning""" optimization_rules = [ ("please", ""), ("I would like you to", ""), ("can you", ""), (" ", " ") # Double spaces ] optimized = prompt for old, new in optimization_rules: optimized = optimized.replace(old, new) return optimized.strip() ``` ## Testing and Debugging Prompts Treat prompts like code—they need systematic testing: ```python class PromptTester: def __init__(self): self.test_cases = [] def add_test_case(self, input_data, expected_pattern, description): """Add test case for prompt validation""" self.test_cases.append({ 'input': input_data, 'expected': expected_pattern, 'description': description }) def run_tests(self, prompt_function): """Run all test cases against a prompt function""" results = [] for test in self.test_cases: try: response = prompt_function(test['input']) passed = self.matches_pattern(response, test['expected']) results.append({ 'description': test['description'], 'passed': passed, 'response': response[:100] + "..." if len(response) > 100 else response }) except Exception as e: results.append({ 'description': test['description'], 'passed': False, 'error': str(e) }) return results ``` ## Conclusion Effective [prompt engineering](/en/blog/mastering-prompt-engineering-claude-beyond-gpt-centric-strategies-for-2026/) combines clear communication principles with software engineering best practices. By structuring your prompts systematically, implementing robust error handling, and treating prompt development as an iterative process, you'll build more reliable AI-integrated applications. Start by auditing your existing prompts using the frameworks outlined above. Implement validation layers, establish testing protocols, and gradually optimize for performance. Remember that prompt engineering is an evolving discipline—stay curious, experiment with new techniques, and continuously refine your approach based on real-world results. The investment in better prompt engineering pays dividends in application reliability, user experience, and development velocity. Your future self (and your users) will thank you for building AI interactions that work predictably and gracefully handle edge cases. ## FAQ ### Why is prompt engineering becoming an essential skill for developers? Prompt engineering is crucial because it directly impacts the reliability and effectiveness of AI applications. Mastering it allows developers to build better AI-powered features, automate code generation more efficiently, and enhance user experiences with natural language processing. ### What is the basic structure of an effective prompt? Effective prompts typically follow a predictable structure, similar to function calls. Key components include Role, Context, Task, Format, Constraints, and the user's Input, all designed to guide the AI's behavior and output. ### How does prompt engineering improve AI interactions? By crafting well-structured and specific prompts, developers can debug AI interactions more effectively and build robust AI-integrated systems. Clear prompts ensure the AI understands its purpose and the desired output, leading to more reliable and accurate responses. ### Can prompt engineering be applied to tasks like code review? Yes, prompt engineering can be applied to various tasks, including code review automation. By defining the AI's role (e.g., senior software engineer), context (e.g., reviewing specific language code), and task (e.g., identify issues), developers can generate targeted and useful feedback.]]> Mon, 30 Mar 2026 00:00:00 GMT https://daniele-messi.com/en/blog/prompt-engineering-for-developers-practical-guide-code-examples/ AI Tutorial 10 Claude Code Automations You Should Try Today https://daniele-messi.com/en/blog/10-claude-code-automations-you-should-try/ Practical examples of how to use Claude Code to automate repetitive tasks, from git workflows to content generation and infrastructure management. **Open Source**: This article is part of the [Astro Content Engine](https://github.com/danymexi/astro-content-engine) project — an open-source SEO content pipeline for Astro blogs. Here are 10 automations I use regularly that save me hours every week. ## 1. Bulk Rename and Refactor Instead of manually finding and replacing across dozens of files: ```bash claude "Rename the function fetchUserData to getUserProfile across the entire codebase, update all imports and tests" ``` [Claude Code](https://docs.anthropic.com/en/docs/claude-code) will search, identify all references, update them consistently, and even fix the test assertions. ## 2. Generate Blog Posts in Multiple Languages This is how I generate bilingual content for this very site: ```bash claude "Write a blog post about [topic]. Generate both an English and Italian version as markdown files in src/content/blog/en/ and src/content/blog/it/ with proper frontmatter" ``` ## 3. Git Workflow Automation Stop manually writing commit messages and creating PRs: ```bash claude "Review my changes, create a well-structured commit message, and open a PR with a summary" ``` Claude reads the diff, understands the context, writes a meaningful commit message, and creates the PR with description and test plan. ## 4. Infrastructure as Code I manage multiple LXC containers on Proxmox. Instead of SSH-ing into each one: ```bash claude "SSH into my Proxmox server at 192.168.178.206, check the status of all LXC containers, and report any that are using more than 80% disk space" ``` ## 5. SEO Audit and Fixes ```bash claude "Audit the SEO of my site: check all pages for meta descriptions, hreflang tags, structured data, sitemap correctness, and suggest fixes" ``` This is exactly how I optimized daniele-messi.com — [Claude Code](https://docs.anthropic.com/en/docs/claude-code) found missing hreflang tags, created the JSON-LD structured data, and generated the llms.txt file in one session. ## 6. Dependency Updates with Context ```bash claude "Update all npm dependencies to their latest versions, run the build, fix any breaking changes, and run the tests" ``` Claude doesn't just run `npm update` — it reads the changelogs, understands breaking changes, and applies the necessary code modifications. ## 7. Log Analysis ```bash claude "Read the last 100 lines of the nginx access log, identify the top 10 IPs by request count, check if any look like bot traffic, and suggest rate limiting rules" ``` ## 8. Content Pipeline Automation Using the Claude API inside scripts to create automated content pipelines: ```javascript // Generate, translate, and publish — all automated const article = await claude.generate(topic); const translation = await claude.translate(article, 'it'); await writeFile(`blog/en/${slug}.md`, article); await writeFile(`blog/it/${slug}.md`, translation); await exec('npm run build && deploy.sh'); ``` ## 9. Database Migrations ```bash claude "I need to add a 'published_at' column to the posts table in my SQLite database. Generate the migration, update the API handlers, and update the TypeScript types" ``` Claude understands the full stack and updates everything consistently. ## 10. Monitoring and Alerting Combine Claude Code with cron jobs for intelligent monitoring: ```bash claude "Check if my websites (daniele-messi.com, francescacolle-osteopata.it, spazioitech.it) are all responding with 200 status codes. If any is down, draft an alert message" ``` ## The Key Principle The best Claude Code automations follow a simple pattern: 1. **Describe the outcome**, not the steps 2. **Provide context** — file paths, server addresses, conventions 3. **Let Claude figure out the implementation** The more context you give through [CLAUDE.md](/en/blog/claude-md-best-practices-crafting-the-perfect-ai-project-file-for-2026/) files and memory, the better the automations become over time. Claude Code learns your preferences, your infrastructure, and your coding style. ## Start Small Pick one repetitive task you do weekly. Describe it to Claude Code in plain language. You'll be surprised how much time you save — and how quickly you'll want to automate everything else. ## FAQ ### What is Claude Code primarily used for beyond basic coding? Claude Code extends beyond writing functions and fixing bugs to interact with the file system, run shell commands, manage Git operations, and orchestrate complex multi-step workflows from natural language prompts. ### How can Claude Code help developers save time? By automating repetitive and complex tasks, Claude Code can save developers hours every week. Examples include bulk renaming and refactoring across dozens of files, generating multi-language content, and automating Git workflows like commit message creation and pull requests. ### Can Claude Code generate content in multiple languages? Yes, Claude Code can generate blog posts in multiple languages, such as English and Italian, as markdown files. It can also place them in specified directory structures with proper frontmatter, streamlining content localization. ### What kind of Git operations can Claude Code automate? Claude Code can automate various Git workflows, including reviewing changes, generating well-structured commit messages, and opening pull requests, significantly reducing manual effort in version control. ### Is Claude Code only useful for code refactoring? No, while code refactoring (like bulk renaming and updating references) is one powerful application, Claude Code's utility extends to many other areas, including file system management, running shell commands, content generation, and full Git workflow automation. ## Recommended Gear If you're building your own setup, here's the hardware I recommend: - **[Logitech MX Keys S](https://www.amazon.it/s?k=Logitech+MX+Keys+S&linkCode=ll2&tag=spazitec0f-21)** — keyboard for productive coding sessions]]> Sun, 29 Mar 2026 00:00:00 GMT https://daniele-messi.com/en/blog/10-claude-code-automations-you-should-try/ Claude Code AI Automation Productivity Claude Code Sub-Agents: Practical Examples & Advanced Strategies for 2026 https://daniele-messi.com/en/blog/claude-code-sub-agents-practical-examples-advanced-strategies-for-2026/ Unlock the power of Claude code sub-agents for complex tasks. Explore practical examples, parallel processing, and efficient dispatch mechanisms in 2026. **Open Source**: This article is part of the [Astro Content Engine](https://github.com/danymexi/astro-content-engine) project — an open-source SEO content pipeline for Astro blogs. Traditionally, a single large language model (LLM) might attempt to tackle an entire problem, often leading to suboptimal results, increased token usage, and difficulty in debugging. Claude code sub-agents, however, operate as part of a larger `claude code agent team`, each contributing its specific expertise to achieve a common goal. This architectural shift enables greater precision, reusability, and the ability to execute `claude code parallel agents` for enhanced efficiency. ## What are Claude Code Sub-Agents? At its core, a claude code sub-agent is a specialized instance of the Claude model, configured with a specific persona, tools, and objectives. Instead of a monolithic AI, you create a network of smaller, focused agents. For example, one sub-agent might be an 'API Caller', another a 'Data Parser', and a third a 'Report Generator'. Each is designed to excel at its designated task, communicating with other sub-agents and a central orchestrator, often using a `claude code dispatch` mechanism. This modularity mirrors human team dynamics. Just as a software development team comprises front-end developers, back-end engineers, and QA testers, an AI agent team benefits from specialized roles. This approach significantly enhances the AI's capability to handle multi-step reasoning, complex data transformations, and iterative problem-solving. ## Why Embrace Claude Code Sub-Agents in Your 2026 Projects? The benefits of adopting claude code sub-agents are manifold, especially for projects demanding high reliability and scalability: 1. **Modularity and Reusability**: Each sub-agent is a self-contained unit. Once built, it can be reused across different projects or within different phases of the same project, reducing development time and ensuring consistency. 2. **Enhanced Accuracy and Specialization**: By focusing on a narrow task, a sub-agent can be fine-tuned and provided with highly specific context and tools, leading to more accurate and reliable outputs than a general-purpose agent. 3. **Improved Error Handling and Debugging**: When an error occurs, it's easier to pinpoint which sub-agent is responsible. Debugging becomes a process of inspecting individual agent logs and interactions, rather than sifting through a single, massive trace. 4. **Parallel Execution**: Complex workflows can often be broken down into independent sub-tasks. With `claude code parallel agents`, these tasks can be executed concurrently, dramatically speeding up overall processing time. 5. **Scalability**: As your project grows, you can easily add new sub-agents or scale existing ones without redesigning the entire system. ## Practical Example 1: Automated Web Scraping and Data Analysis Let's consider a scenario where you need to regularly scrape product information from multiple e-commerce sites, clean the data, and generate an analytical report. This is a perfect use case for `claude code sub-agents`. ### Sub-Agent Team Setup: * **`ScraperAgent`**: Responsible for navigating URLs, extracting raw HTML, and identifying key data points (e.g., product name, price, description, images). It might use tools like `requests` and `BeautifulSoup`. * **`ParserAgent`**: Takes the raw HTML or extracted data from `ScraperAgent`, cleans it, standardizes formats, handles missing values, and converts it into a structured JSON or CSV format. * **`AnalyzerAgent`**: Receives the cleaned data, performs statistical analysis (e.g., price trends, competitor analysis, sentiment analysis on reviews), and identifies insights. * **`ReporterAgent`**: Takes the insights from `AnalyzerAgent` and generates a human-readable report (e.g., Markdown, PDF, or a summary email). ### Orchestration with Claude Code Dispatch: The central orchestrator (`MainAgent`) would use a `claude code dispatch` mechanism to manage the flow: ```python # Pseudocode for a Claude Code Dispatcher from claude_agents import Agent, Tool class ScraperAgent(Agent): def __init__(self): super().__init__("Scraper", "Extracts product data from URLs.") self.add_tool(Tool("scrape_url", self._scrape_url_tool)) def _scrape_url_tool(self, url: str) -> str: # Simulate web scraping logic print(f"Scraping: {url}") return f"

Product X

Price: $100

" # Raw HTML class ParserAgent(Agent): def __init__(self): super().__init__("Parser", "Cleans and structures raw HTML data.") self.add_tool(Tool("parse_html", self._parse_html_tool)) def _parse_html_tool(self, html_content: str) -> dict: # Simulate parsing logic print("Parsing HTML...") return {"product_name": "Product X", "price": 100.0} # Structured data class AnalyzerAgent(Agent): def __init__(self): super().__init__("Analyzer", "Analyzes structured product data.") self.add_tool(Tool("analyze_data", self._analyze_data_tool)) def _analyze_data_tool(self, data: dict) -> dict: # Simulate analysis logic print("Analyzing data...") return {"average_price": 100.0, "insights": "Price is stable."} # Insights class ReporterAgent(Agent): def __init__(self): super().__init__("Reporter", "Generates reports from insights.") self.add_tool(Tool("generate_report", self._generate_report_tool)) def _generate_report_tool(self, insights: dict) -> str: # Simulate report generation print("Generating report...") return f"## Daily Product Report\nInsights: {insights['insights']}" class MainAgent: def __init__(self): self.agents = { "scraper": ScraperAgent(), "parser": ParserAgent(), "analyzer": AnalyzerAgent(), "reporter": ReporterAgent() } def run_workflow(self, target_url: str): print("--- Starting Workflow ---") # Step 1: Scrape data raw_html = self.agents["scraper"].execute_tool("scrape_url", url=target_url) # Step 2: Parse data structured_data = self.agents["parser"].execute_tool("parse_html", html_content=raw_html) # Step 3: Analyze data insights = self.agents["analyzer"].execute_tool("analyze_data", data=structured_data) # Step 4: Generate report report = self.agents["reporter"].execute_tool("generate_report", insights=insights) print("--- Workflow Complete ---") print(report) # Example usage in 2026 main_workflow = MainAgent() main_workflow.run_workflow("https://example.com/products/latest") ``` This example showcases a sequential workflow. However, if you were scraping multiple URLs, the `ScraperAgent` could be invoked in parallel using `claude code parallel agents` for each URL, passing their outputs to a single `ParserAgent` or a pool of them. ## Practical Example 2: Multi-Step Software Development with Claude Code Agent Teams Imagine automating parts of the software development lifecycle. A `claude code agent team` can collaborate to turn a high-level request into deployable code. ### Sub-Agent Team Setup: * **`RequirementsAgent`**: Interacts with the user to clarify requirements, define scope, and break down features into user stories. Generates detailed specifications. * **`ArchitectAgent`**: Takes specifications and proposes high-level design, database schemas, API endpoints, and technology stack. Focuses on scalability and maintainability. * **`CodeGeneratorAgent`**: Based on the architecture and detailed specs, generates actual code files for different components (e.g., backend API, frontend components, database migrations). This agent might interact with a code repository tool. * **`TestAgent`**: Writes unit tests, integration tests, and potentially performs security vulnerability checks on the generated code. Reports failures back to `CodeGeneratorAgent` for iteration. * **`DocumentationAgent`**: Creates or updates API documentation, user guides, and internal developer docs based on the generated code and features. ### Leveraging Parallel Agents and Iterative Dispatch: In this complex scenario, `claude code parallel agents` become crucial. For instance, `CodeGeneratorAgent` could be broken down further into `BackendCodeAgent` and `FrontendCodeAgent`, working in parallel. The `TestAgent` would run concurrently with or immediately after code generation, providing rapid feedback. The `claude code dispatch` mechanism here would be more dynamic, involving iterative loops. If `TestAgent` finds issues, it dispatches the problem back to `CodeGeneratorAgent` with specific error reports, prompting a revision and re-testing cycle. ```python # Conceptual Claude Code Agent Team orchestration (simplified) class Orchestrator: def __init__(self): self.requirements_agent = RequirementsAgent() self.architect_agent = ArchitectAgent() self.code_gen_agent = CodeGeneratorAgent() self.test_agent = TestAgent() def develop_feature(self, initial_request: str): specs = self.requirements_agent.clarify_and_spec(initial_request) architecture = self.architect_agent.design_system(specs) code_generated = False attempts = 0 MAX_ATTEMPTS = 3 while not code_generated and attempts < MAX_ATTEMPTS: print(f"Attempt {attempts + 1} to generate and test code...") generated_code = self.code_gen_agent.generate_code(architecture, specs) test_results = self.test_agent.run_tests(generated_code) if test_results["passed"]: print("Code passed all tests!") code_generated = True else: print(f"Tests failed. Feedback: {test_results['feedback']}") # The code_gen_agent would internally use this feedback for refinement self.code_gen_agent.refine_code_based_on_feedback(test_results["feedback"]) attempts += 1 if code_generated: print("Feature development complete. Ready for deployment.") # DocumentationAgent could be invoked here else: print("Failed to generate robust code after multiple attempts.") ``` This iterative loop demonstrates the power of a `claude code agent team` where sub-agents collaborate and provide feedback to each other, mimicking a human development process. The `claude code sub-agents` are not just sequential; they can form complex, dynamic interactions. ## Best Practices for Building Robust Claude Code Sub-Agents To maximize the effectiveness of your `claude code sub-agents` in 2026: * **Clear Responsibilities**: Define a precise role and objective for each sub-agent. Avoid overlapping responsibilities to maintain modularity. * **Well-Defined Interfaces**: Establish clear input and output formats for each sub-agent. This ensures seamless communication within your `claude code agent team`. * **Robust Error Handling**: Implement mechanisms for sub-agents to report errors, and for the orchestrator to handle retries, fallbacks, or escalate issues. * **Observability**: Integrate logging and monitoring for each sub-agent. This is crucial for debugging complex workflows and understanding performance. * **Tooling**: Equip sub-agents with the right external tools (APIs, databases, file systems, code interpreters) that enable them to perform their specialized tasks effectively. * **Context Management**: Ensure that sub-agents receive only the necessary context for their task, preventing information overload and improving efficiency. ## Conclusion: The Future is Modular with Claude Code Sub-Agents The landscape of AI development in 2026 is rapidly evolving, with `claude code sub-agents` leading the charge towards more intelligent, efficient, and manageable AI systems. By decomposing complex problems into smaller, specialized tasks and orchestrating them with sophisticated `claude code dispatch` mechanisms, developers can unlock unprecedented capabilities. Embracing `claude code agent teams` and understanding how to deploy `claude code parallel agents` will be key differentiators for building advanced AI applications. Start experimenting with these powerful modular architectures today to stay ahead in the rapidly advancing world of AI. ## FAQ ### What are Claude Code Sub-Agents? Claude code sub-agents are specialized instances of the Claude AI model, each configured with a specific persona, tools, and objectives. They are designed to break down complex AI problems into smaller, more manageable tasks, operating as part of a larger agent team. ### Why are Claude Code Sub-Agents important for 2026? By 2026, Claude code sub-agents are expected to see widespread adoption due to their ability to create modular, manageable, and efficient AI workflows. This advancement addresses the growing need for more sophisticated and scalable AI systems. ### How do Claude Code Sub-Agents differ from traditional LLMs? Unlike traditional large language models that might attempt to solve an entire problem monolithically, sub-agents operate as a team, each contributing specific expertise to a common goal. This specialized approach leads to greater precision, reusability, and easier debugging. ### What are the main benefits of using Claude Code Sub-Agents? The primary benefits include enhanced precision, improved reusability of AI components, and the ability to execute `claude code parallel agents` for increased efficiency. This modular architecture also simplifies debugging and allows for more scalable AI-powered solutions. ## Recommended Gear If you're building your own setup, here's the hardware I recommend: - **[Logitech MX Keys S](https://www.amazon.it/s?k=Logitech+MX+Keys+S&linkCode=ll2&tag=spazitec0f-21)** — keyboard for productive coding sessions - [10 Claude Code Automations You Should Try Today](/en/blog/10-claude-code-automations-you-should-try/) - [Claude Code Hooks: The Complete Guide to Automation & Workflow in 2026](/en/blog/claude-code-hooks-the-complete-guide-to-automation-workflow-in-2026/) - [CLAUDE.md Best Practices: Crafting the Perfect AI Project File for 2026](/en/blog/claude-md-best-practices-crafting-the-perfect-ai-project-file-for-2026/) - [Getting Started with Claude Code: The Ultimate Guide](/en/blog/getting-started-with-claude-code/)]]> Sat, 28 Mar 2026 00:00:00 GMT https://daniele-messi.com/en/blog/claude-code-sub-agents-practical-examples-advanced-strategies-for-2026/ Claude AI Agentic Workflows AI Development Software Engineering Automation CLAUDE.md Best Practices: Crafting the Perfect AI Project File for 2026 https://daniele-messi.com/en/blog/claude-md-best-practices-crafting-the-perfect-ai-project-file-for-2026/ Master CLAUDE.md best practices for your AI projects in 2026. Learn how to structure, configure, and manage your Claude code setup for optimal performance and collaboration. **Open Source**: This article is part of the [Astro Content Engine](https://github.com/danymexi/astro-content-engine) project — an open-source SEO content pipeline for Astro blogs. ## Core Sections for CLAUDE.md Best Practices A truly effective `[CLAUDE.md](https://docs.anthropic.com/en/docs/claude-code/claude-md)` goes beyond a simple README. It's a living document that anticipates the needs of anyone interacting with your project. Here are the critical sections you should include: ### Project Overview and Goals Start with a high-level summary. What problem does this AI project solve? What are its primary objectives and key performance indicators (KPIs)? This section sets the context and ensures everyone understands the "why" behind the project. Clearly state the version of Claude being utilized, for instance, "Claude 3.5 Sonnet" or "Claude 4.0 (expected late 2026)". ### Environment Setup and Dependencies This is arguably the most crucial section for reproducibility. Detail every step required to get the development environment running. This includes Python versions, specific libraries, API keys (with instructions on secure handling, *never* hardcode them), and any system-level dependencies. This is where your `claude code setup` instructions live. ```markdown ## Environment Setup This project requires Python 3.10 or higher. 1. **Clone the repository:** git clone https://github.com/your-org/your-claude-project.git cd your-claude-project 2. **Create and activate a virtual environment:** python -m venv .venv source .venv/bin/activate # On Windows: .venv\Scripts\activate 3. **Install dependencies:** pip install -r requirements.txt 4. **Configure API Key:** Obtain your Claude API key from [Anthropic Console](https://console.anthropic.com). Set it as an environment variable: export ANTHROPIC_API_KEY="your_api_key_here" # Replace with your actual key # For persistent setup, consider adding to your shell profile (.bashrc, .zshrc) ``` ### Data Sources and Preparation Describe where the data comes from, how to access it, and any preprocessing steps required. If you're using public datasets, provide links. If it's internal data, explain access protocols. Detail any scripts for data cleaning, transformation, or feature engineering. ```python # scripts/prepare_data.py import pandas as pd def load_and_clean_data(filepath): df = pd.read_csv(filepath) # Example cleaning: remove duplicates, handle missing values df.drop_duplicates(inplace=True) df.fillna(method='ffill', inplace=True) return df if __name__ == "__main__": raw_data_path = "data/raw/input_data_2026.csv" processed_data_path = "data/processed/cleaned_data_2026.csv" data = load_and_clean_data(raw_data_path) data.to_csv(processed_data_path, index=False) print(f"Data processed and saved to {processed_data_path}") ``` ### Model Configuration and Training This section outlines how your Claude model is configured and trained. Include details on [prompt engineering](/en/blog/mastering-prompt-engineering-claude-beyond-gpt-centric-strategies-for-2026/) strategies, few-shot examples, temperature settings, and any fine-tuning procedures. If you're using custom tools or functions with Claude, describe their integration. This is key for explaining your `claude code config`. ```json // config/claude_model_config.json { "model_name": "claude-3-5-sonnet-20260620", "temperature": 0.7, "max_tokens": 1024, "system_prompt": "You are an expert AI assistant providing concise and accurate summaries.", "tools": [ { "name": "search_database", "description": "Searches the internal knowledge base for relevant information.", "input_schema": { "type": "object", "properties": { "query": { "type": "string", "description": "The search query." } }, "required": ["query"] } } ], "fine_tuning_data": "data/training/finetune_qa_2026.jsonl" } ``` ### Evaluation Metrics and Validation How do you measure success? Define the metrics used to evaluate your model's performance (e.g., accuracy, precision, recall, F1-score, custom human evaluation scores). Explain the validation process, including cross-validation strategies or dedicated test sets. This ensures consistent performance assessment. ### Deployment and Usage Instructions Provide clear instructions on how to run, deploy, and interact with the model. This might involve running a local API, deploying to a cloud service (e.g., AWS Lambda, Azure Functions), or integrating into an existing application. Include example API calls or command-line usage. ```bash # Example usage to run inference python src/inference.py --input "What are the latest AI trends in 2026?" ``` ### Troubleshooting and Common Issues Anticipate common problems and provide solutions. This could cover API rate limits, dependency conflicts, or expected output formats. A well-maintained troubleshooting section saves significant time and frustration. ## Advanced CLAUDE.md Techniques for 2026 To truly adhere to `CLAUDE.md best practices` in 2026, consider these advanced strategies: ### Version Control Integration Your `CLAUDE.md` file should live within your project's version control system (e.g., Git). This allows you to track changes, revert to previous versions, and collaborate effectively. Ensure that every significant update to your project's logic or `claude code config` is reflected in the `CLAUDE.md` and committed alongside the code. ### Automated Testing with CLAUDE.md While `CLAUDE.md` isn't a test script, it can document how to run automated tests for your AI project. For instance, specify commands to run unit tests for your data preprocessing or integration tests for your Claude API calls. This ensures that changes don't break existing functionality. ```bash # To run all tests pytest tests/ # To run specific prompt engineering tests pytest tests/test_prompts_2026.py ``` ### Managing Multiple CLAUDE Code Project Files For larger projects with multiple distinct Claude applications or modules, you might consider having a main `CLAUDE.md` at the root and smaller, specific `CLAUDE_submodule.md` files within subdirectories. This modular approach helps manage complexity while maintaining clear documentation for each component. Ensure the main `CLAUDE.md` acts as an index to these sub-files, providing a cohesive overview of the entire `claude code project file` structure. ## Tips for Writing Effective CLAUDE.md Files Beyond structure, the quality of your writing matters: * **Clarity and Conciseness**: Use plain language. Avoid jargon where possible, or explain it. Get straight to the point. * **Regular Updates**: A `CLAUDE.md` file is a living document. As your project evolves, so should its documentation. Make updating it a part of your development workflow. * **Use Markdown Features**: Leverage headings, bullet points, numbered lists, code blocks, and links to make your `CLAUDE.md` easy to read and navigate. * **Examples for Complex Steps**: Whenever a step is potentially confusing, provide a concrete example, whether it's a code snippet, a command, or an expected output. * **Emphasize Security**: Remind users about secure handling of API keys and sensitive data. Never hardcode credentials. ## Conclusion A well-crafted `CLAUDE.md` is an invaluable asset for any AI project, especially when working with sophisticated models like Claude. By meticulously documenting your project's objectives, environment, data, model configuration, and deployment, you create a robust foundation for collaboration, reproducibility, and future scalability. Adopting these `CLAUDE.md best practices` ensures that your AI initiatives in 2026 are not only technically sound but also efficiently managed and easily understood by everyone involved. Invest the time now to perfect your `CLAUDE.md`, and you'll reap significant benefits throughout your project's lifecycle. ## FAQ ### What is CLAUDE.md? `CLAUDE.md` is a markdown file that serves as the central nervous system for a Claude-powered AI project. It acts as a single source of truth, outlining everything from project objectives and environment setup to data handling, model configuration, and deployment instructions. ### Why is CLAUDE.md considered indispensable for AI projects? It is indispensable because it significantly reduces friction in development, especially with complex AI models and distributed teams. A well-structured `CLAUDE.md` helps new team members onboard quickly, allows for easy replication of results, and ensures consistent adherence to best practices. ### What key information should a CLAUDE.md file contain? A comprehensive `CLAUDE.md` file should outline project objectives, detailed environment setup instructions, data handling procedures, specific model configuration, and clear deployment instructions. It provides a complete guide for anyone interacting with the AI project. ## Recommended Gear If you're building your own setup, here's the hardware I recommend: - **[Logitech MX Keys S](https://www.amazon.it/s?k=Logitech+MX+Keys+S&linkCode=ll2&tag=spazitec0f-21)** — keyboard for productive coding sessions - [10 Claude Code Automations You Should Try Today](/en/blog/10-claude-code-automations-you-should-try/) - [Claude Code Hooks: The Complete Guide to Automation & Workflow in 2026](/en/blog/claude-code-hooks-the-complete-guide-to-automation-workflow-in-2026/) - [Getting Started with Claude Code: The Ultimate Guide](/en/blog/getting-started-with-claude-code/)]]> Fri, 27 Mar 2026 00:00:00 GMT https://daniele-messi.com/en/blog/claude-md-best-practices-crafting-the-perfect-ai-project-file-for-2026/ Claude AI Prompt Engineering AI Development Developer Tools AI Best Practices Getting Started with Claude Code: The Ultimate Guide https://daniele-messi.com/en/blog/getting-started-with-claude-code/ A comprehensive guide to installing, configuring, and using Claude Code — Anthropic's AI-powered CLI for software engineering. **Open Source**: This article is part of the [Astro Content Engine](https://github.com/danymexi/astro-content-engine) project — an open-source SEO content pipeline for Astro blogs. Unlike traditional chat interfaces, [Claude Code](https://docs.anthropic.com/en/docs/claude-code) operates directly in your development environment, with access to your file system, terminal, and git history. This means it can read your codebase, make changes, run tests, and even commit code — all through natural language commands. ## Installation Getting started is straightforward. You'll need Node.js 22+ installed on your machine. ```bash npm install -g @anthropic-ai/claude-code ``` Once installed, authenticate with your [Anthropic](https://www.anthropic.com) account: ```bash claude ``` This will open a browser window for authentication. After logging in, you're ready to go. ## Key Features ### 1. Codebase Awareness Claude Code can read and understand your entire codebase. It uses tools like file search, content search, and directory navigation to build context before making suggestions. ### 2. Multi-file Editing Need to refactor a function that's used across multiple files? Claude Code can identify all references and update them consistently. ### 3. Git Integration Claude Code can create commits, manage branches, and even create pull requests — all through natural language instructions. ### 4. Terminal Access It can run shell commands, install packages, run tests, and interact with any CLI tool in your environment. ## Best Practices 1. **Be specific**: Instead of "fix the bug", say "the login form throws a TypeError when email is empty — fix it" 2. **Provide context**: Mention file names, function names, or error messages 3. **Use [CLAUDE.md](/en/blog/claude-md-best-practices-crafting-the-perfect-ai-project-file-for-2026/)**: Create a `CLAUDE.md` file in your project root with project-specific instructions 4. **Review changes**: Always review the changes Claude Code makes before committing ## Use Cases - **Bug fixing**: Describe the bug and let Claude trace through the code to find and fix it - **Feature development**: Describe what you want and Claude will implement it across your codebase - **Code review**: Ask Claude to review changes and suggest improvements - **Documentation**: Generate docs, comments, and README files - **Refactoring**: Rename variables, extract functions, reorganize code structure - **Testing**: Write unit tests, integration tests, and fix failing tests ## Conclusion Claude Code represents a new paradigm in AI-assisted development. By working directly in your terminal environment, it bridges the gap between AI capabilities and practical software engineering workflows. Give it a try and see how it transforms your development process. ## FAQ ### What is Claude Code? Claude Code is Anthropic's official command-line interface (CLI) that integrates the Claude AI directly into your terminal. It allows software engineers to leverage AI for various coding tasks, from writing and debugging to managing entire projects. ### What are the primary requirements for installing Claude Code? To install Claude Code, you need to have Node.js version 22 or higher installed on your machine. Once Node.js is ready, you can install it globally using `npm install -g @anthropic-ai/claude-code`. ### How does Claude Code interact with my development environment? Unlike traditional chat interfaces, Claude Code operates directly within your development environment. It has access to your file system, terminal, and Git history, enabling it to read your codebase, make changes, run tests, and even commit code using natural language commands. ### What key features does Claude Code offer for developers? Claude Code offers key features such as comprehensive codebase awareness, allowing it to understand your entire project through file and content search. It also supports multi-file editing, enabling complex refactoring and code modifications across multiple files. ## Recommended Gear If you're building your own setup, here's the hardware I recommend: - **[Logitech MX Keys S](https://www.amazon.it/s?k=Logitech+MX+Keys+S&linkCode=ll2&tag=spazitec0f-21)** — keyboard for productive coding sessions]]> Fri, 27 Mar 2026 00:00:00 GMT https://daniele-messi.com/en/blog/getting-started-with-claude-code/ Claude Code AI Developer Tools Tutorial Claude Code Hooks: The Complete Guide to Automation & Workflow in 2026 https://daniele-messi.com/en/blog/claude-code-hooks-the-complete-guide-to-automation-workflow-in-2026/ Unlock powerful Claude code automation by mastering Claude Code Hooks. This 2026 guide covers custom hooks, advanced workflows, and best practices for integrating AI. **Open Source**: This article is part of the [Astro Content Engine](https://github.com/danymexi/astro-content-engine) project — an open-source SEO content pipeline for Astro blogs. This comprehensive guide will demystify [Claude Code](https://docs.anthropic.com/en/docs/claude-code) Hooks, providing tech-savvy professionals with the knowledge and practical examples needed to implement them effectively. Whether you're looking to streamline data preprocessing, enhance output validation, or integrate Claude into complex multi-step workflows, understanding and utilizing these hooks is crucial for next-generation **Claude code automation**. We’ll cover everything from basic setup to advanced **Claude code custom hooks** and best practices for optimizing your AI-driven **Claude code workflow**. ## What Are Claude Code Hooks? At its core, a [Claude Code](https://docs.anthropic.com/en/docs/claude-code) Hook is a predefined point within an application's interaction lifecycle with Claude where you can inject custom code. Think of them as programmable gates or interception points that allow you to execute specific logic before, after, or during a particular event related to Claude's API calls or internal processing. These hooks provide immense flexibility, enabling developers to: * **Pre-process inputs:** Clean, validate, or enrich data before it reaches Claude. * **Post-process outputs:** Parse, validate, transform, or store Claude's responses. * **Handle errors:** Implement custom error logging or retry mechanisms. * **Integrate with external systems:** Trigger other services based on Claude's interactions. * **Monitor and log:** Capture detailed telemetry for analysis and auditing. The beauty of **Claude Code Hooks** lies in their ability to decouple custom logic from the core AI interaction, making your applications more modular, maintainable, and scalable. ## Setting Up Your First Claude Code Hook Implementing a basic Claude Code Hook typically involves registering a function or a class method to be executed at a specific trigger point. While the exact implementation details might vary slightly depending on the Claude SDK or framework you are using (e.g., Python, JavaScript, or a specialized AI orchestration platform), the conceptual flow remains consistent. Let's illustrate with a conceptual Python-like example, assuming an SDK that allows hook registration: ```python # Assuming an SDK or framework that supports hook registration from claude_sdk import ClaudeClient, HookManager # Initialize Claude client claude_client = ClaudeClient(api_key="YOUR_CLAUDE_API_KEY_2026") hook_manager = HookManager() # Define a simple pre-processing hook def simple_input_logger_hook(input_payload): """Logs the input text before sending to Claude.""" print(f"Hook: Incoming Claude request - Text length: {len(input_payload.get('text', ''))}") # You could modify input_payload here if needed return input_payload # Define a simple post-processing hook def simple_output_logger_hook(output_response): """Logs the output text received from Claude.""" print(f"Hook: Outgoing Claude response - First 50 chars: {output_response.get('text', '')[:50]}") # You could modify output_response here if needed return output_response # Register the hooks # The 'pre_request' and 'post_response' are common hook types hook_manager.register_hook('pre_request', simple_input_logger_hook) hook_manager.register_hook('post_response', simple_output_logger_hook) # Now, when you use the Claude client, these hooks will automatically run # Example interaction: try: response = claude_client.chat.completions.create( model="claude-3-opus-2026-03", messages=[{"role": "user", "content": "Explain quantum entanglement simply."}] ) print(f"Claude's response: {response.choices[0].message.content[:100]}...") except Exception as e: print(f"An error occurred: {e}") ``` In this example, `simple_input_logger_hook` runs just before the request is sent, and `simple_output_logger_hook` runs immediately after Claude's response is received. This foundational understanding is key to unlocking advanced **claude code automation**. ## Types of Claude Code Hooks While "pre-request" and "post-response" are the most common, modern Claude integration platforms often offer a richer set of hook types to cater to diverse **claude code workflow** needs. 1. **Pre-Request Hooks:** Executed before an API call to Claude is made. * **Use Cases:** Input validation, data sanitization, adding contextual information, dynamic [prompt engineering](/en/blog/mastering-prompt-engineering-claude-beyond-gpt-centric-strategies-for-2026/), token count estimation, A/B testing variations. 2. **Post-Response Hooks:** Executed immediately after receiving a response from Claude. * **Use Cases:** Output parsing, response validation, sentiment analysis of output, logging, caching, triggering follow-up actions, PII redaction. 3. **Error Hooks:** Triggered when an error occurs during the interaction with Claude (e.g., API rate limits, invalid requests, network issues). * **Use Cases:** Custom error logging, automatic retries with backoff, notifying administrators, fallback mechanisms. 4. **Custom Event Hooks:** These are more flexible and can be triggered by specific events within your application's logic, independent of a direct Claude API call. * **Use Cases:** Monitoring specific user interactions, periodically checking Claude's status, triggering complex multi-step processes after a certain condition is met. These are crucial for building sophisticated **claude code custom hooks**. ## Advanced Claude Code Automation with Hooks Let's dive into more practical scenarios where **claude code hooks** can significantly enhance your AI applications. ### 1. Data Validation and Transformation Hook Imagine you're building an application that processes user queries for a knowledge base. You want to ensure that certain sensitive keywords are flagged or removed, and that the query is always formatted consistently before Claude processes it. ```python # Advanced pre-request hook for data validation and transformation def validate_and_transform_query_hook(input_payload): """ Validates user query, removes sensitive info, and adds system context. """ user_query = input_payload.get('text', '') # 1. Basic validation: Ensure query is not empty if not user_query.strip(): raise ValueError("Query cannot be empty.") # 2. Sensitive keyword filtering (example) sensitive_keywords = ["confidential", "secret", "private data"] for keyword in sensitive_keywords: if keyword in user_query.lower(): print(f"Warning: Sensitive keyword '{keyword}' detected in query.") # Option 1: Raise an error # raise SecurityError("Query contains restricted terms.") # Option 2: Censor the keyword user_query = user_query.replace(keyword, "[REDACTED]") # 3. Add system context for better Claude understanding system_context = "The user is asking a question about our product documentation. Please provide concise and accurate answers based on publicly available information." # Modify the input_payload for Claude # This assumes the 'messages' structure for chat completions if 'messages' in input_payload: # Prepend a system message for context input_payload['messages'].insert(0, {"role": "system", "content": system_context}) # Update the user message if it was modified for msg in input_payload['messages']: if msg['role'] == 'user': msg['content'] = user_query break else: # For simpler text completion APIs, directly update the 'text' field input_payload['text'] = f"{system_context}\nUser Query: {user_query}" print("Hook: Query validated and transformed successfully.") return input_payload # Register this hook before making Claude calls # hook_manager.register_hook('pre_request', validate_and_transform_query_hook) ``` This hook demonstrates how you can implement robust input sanitization and context injection, crucial for maintaining data quality and enhancing Claude's performance within your **Claude code workflow**. ### 2. Integrating with External Systems Post-Response Consider a scenario where Claude generates a summary of a customer support transcript. You want to automatically push this summary to a CRM system or trigger a notification to a team lead. ```python import requests # For making HTTP requests import json # Post-response hook for external system integration def crm_integration_hook(output_response): """ Sends Claude's summary to a CRM system and triggers a notification. """ claude_text = output_response.get('text', output_response.get('content', '')) # Adapt to Claude's response structure if "summary" in claude_text.lower(): # Simple check if response contains a summary summary_data = { "source_ai": "Claude-3-Opus-2026", "summary_content": claude_text, "timestamp": "2026-07-20T14:30:00Z" # In a real app, use datetime.now().isoformat() } # 1. Push to CRM (conceptual API call) crm_api_url = "https://api.yourcrm.com/v1/summaries" crm_headers = {"Authorization": "Bearer YOUR_CRM_API_KEY", "Content-Type": "application/json"} try: crm_response = requests.post(crm_api_url, headers=crm_headers, data=json.dumps(summary_data)) crm_response.raise_for_status() # Raise an exception for HTTP errors print(f"Hook: Successfully sent summary to CRM. Status: {crm_response.status_code}") except requests.exceptions.RequestException as e: print(f"Hook Error: Failed to send summary to CRM: {e}") # Optionally, log to a separate error service or retry # 2. Trigger a notification (e.g., Slack, Email) notification_webhook_url = "https://hooks.slack.com/services/T00000000/B00000000/XXXXXXXXXXXXXXXXXXXXXXXX" notification_payload = { "text": f"New Claude summary available: {claude_text[:100]}...", "channel": "#ai-summaries" } try: slack_response = requests.post(notification_webhook_url, data=json.dumps(notification_payload)) slack_response.raise_for_status() print("Hook: Notification sent successfully.") except requests.exceptions.RequestException as e: print(f"Hook Error: Failed to send notification: {e}") return output_response # Register this hook # hook_manager.register_hook('post_response', crm_integration_hook) ``` This example showcases the power of **claude code custom hooks** in orchestrating complex **Claude code automation** by integrating AI outputs directly into your existing business systems. ## Best Practices for Claude Code Workflow To maximize the benefits of **claude code hooks** and ensure a robust **claude code workflow**, consider these best practices: * **Keep Hooks Lean:** Hooks should execute quickly. Avoid long-running or resource-intensive operations within a hook to prevent performance bottlenecks. If complex logic is needed, offload it to an asynchronous task queue. * **Error Handling:** Implement robust error handling within your hooks. A failing hook should ideally not crash the entire application. Use `try-except` blocks and proper logging. * **Idempotency:** If a hook modifies data or triggers external actions, consider making it idempotent where possible, especially for retry mechanisms. * **Logging and Monitoring:** Integrate comprehensive logging within your hooks. This is crucial for debugging, auditing, and understanding the flow of data. Monitor hook execution times and success rates. * **Security:** Be mindful of sensitive data. If hooks handle PII or confidential information, ensure proper encryption, access controls, and compliance with data privacy regulations (e.g., GDPR, CCPA 2026). * **Version Control:** Treat your hooks as critical application code. Store them in version control systems and follow standard development practices. * **Modularity:** Design hooks to be single-purpose and reusable. This improves maintainability and testability. ## Troubleshooting Common Issues * **Hook Not Firing:** Double-check your hook registration. Ensure the hook type matches the event you expect. * **Performance Degradation:** If your application slows down, review your hooks for any inefficient code or external calls. Profile their execution. * **Unexpected Data:** Log the input and output of your hooks to understand how data is being transformed. * **External API Failures:** Implement circuit breakers or exponential backoff for external API calls within hooks to prevent cascading failures. ## The Future of Claude Code Automation in 2027 and Beyond Looking ahead to 2027, we anticipate even more sophisticated frameworks for managing **Claude Code Hooks**. We'll likely see advanced visual workflow builders, AI-assisted hook generation, and tighter integration with enterprise orchestration tools. The ability to define complex, conditional logic within these hooks will continue to expand, making **Claude code automation** more accessible and powerful for developers and businesses alike. ## Conclusion **Claude Code Hooks** are a game-changer for anyone serious about building advanced, production-ready AI applications with Claude. They provide the necessary flexibility and control to tailor Claude's behavior, integrate with existing systems, and automate complex workflows. By adopting the principles and practices outlined in this guide, you can unlock a new level of efficiency, reliability, and innovation in your AI development efforts. Start experimenting with **Claude Code Custom Hooks** today and transform your **Claude code workflow** for the future. ## FAQ ### What are Claude Code Hooks? Claude Code Hooks are robust mechanisms designed to customize, extend, and automate interactions with AI models like Claude. They allow developers to build sophisticated and highly tailored AI applications by providing specific points for intervention. ### Why are Claude Code Hooks important in 2026? By 2026, Claude Code Hooks have become an indispensable tool for developers. They are crucial for creating sophisticated, resilient, and highly tailored AI applications that go beyond basic model integration, enabling next-generation Claude code automation. ### What specific functions do Claude Code Hooks enable? Claude Code Hooks enable developers to streamline various critical functions, including data preprocessing, enhancing output validation, and seamlessly integrating Claude into complex, multi-step workflows. This allows for more efficient and robust AI-driven processes. ## Recommended Gear If you're building your own setup, here's the hardware I recommend: - **[Logitech MX Keys S](https://www.amazon.it/s?k=Logitech+MX+Keys+S&linkCode=ll2&tag=spazitec0f-21)** — keyboard for productive coding sessions - [10 Claude Code Automations You Should Try Today](/en/blog/10-claude-code-automations-you-should-try/) - [Getting Started with Claude Code: The Ultimate Guide](/en/blog/getting-started-with-claude-code/)]]> Wed, 25 Mar 2026 00:00:00 GMT https://daniele-messi.com/en/blog/claude-code-hooks-the-complete-guide-to-automation-workflow-in-2026/ Claude AI Code Hooks AI Automation Workflow Optimization Developer Tools