Still on improving our AI-based, embedded software workflow, this article applies the same AI-agent discipline to Zephyr. Using the same ESP Dualkey kit from M5Stack, specs, integration rules, plan→execute→commit→test, reusable modules, journals, and Git - without redefining the product.
A first-person account of building an ESP32-C5 Arduino temperature indicator with AI assistance, from generated code and confusing errors to serial debugging, wiring issues, and the moment the LED finally changed color.
ESP-IDF v6.0 introduces the Tools local MCP server, a feature that lets AI clients like Cursor and Claude Code control your projects – setting targets, building, flashing, and checking status. This article explains how it works and walks you through setup step by step.
AI assistants are most effective on ESP32 Rust firmware when you supply clear specs, pinned crates, reference implementations (often ESP-IDF C), and a tight verify loop. The article discusses good practices, pitfalls, discipline, and entropy. A brief explanation about the device is also included, along with the repository and all artifacts.
This article demonstrates how to implement gesture recognition using TensorFlow Lite Micro on Espressif SoCs. It covers the complete workflow from data collection and model training to model deployment, showcasing TensorFlow Lite Micro’s applications in edge AI.
This article introduces how to connect your AI agent to official, up-to-date Espressif documentation directly inside your AI applications — with installation steps, example prompts, and best practices.
This article demonstrates how to implement an independently controllable robotic arm project based on the ESP32-P4 high-performance MCU. It covers complete kinematics, visual detection, and remote control, showcasing the great potential of ESP32-P4 in industrial applications.
Learn how Wokwi simulation and AI-assisted debugging solved a subtle RGB565 color mapping bug when porting Raylib to ESP32, turning hours of hardware debugging into an efficient iterative workflow with automated visual testing.
The esp-video component provides a solution to build camera applications on the ESP32 chips. This article will introduce the esp-video component, how to use it, and will give an overview of the framework around it.
ESP RainMaker now supports the Model Context Protocol (MCP), enabling natural language interactions with your IoT devices via tools like Claude, Cursor, Gemini CLI, Windsurf, etc. This blog introduces the new stdio-based MCP server, outlines use cases, and hints at what’s next.
This article demonstrates how to implement a touchpad-based digit recognition system using ESP-DL on ESP32 series chips. It covers the complete workflow from data collection and preprocessing to model training, quantization, and deployment, showcasing ESP-DL’s capabilities in edge AI applications.
