[jkushuee]

I feel like the ai code generation companies such as cursor and Windsurf have completely ignored the world of embedded software development. Is there anybody in this ecosystem who has been able to successfully utilize AI tools to to develop embedded software.

If yes I would like to see specific examples of how it has been useful as well as what tools were they using please. TIA.

PS: Feel free to mention any AI tools that are helping in hardware development overall

 

[Delta Prime]

If yes I would like to see specific examples of how it has been useful as well as what tools were they using please. TIA.

yes I know 25.810^2 specific useful examples & the associated platform tools; trained neural networks. by the way, 25.810 squared equals 666 examples so you gonna have to be very specific in your question in order to provide you an in-depth answer.
Also… if the number 666 represents evil; then 25.810 is the root of all evil.

 

[jkushuee]

Well the idea is that embedded software development requires IDEs that are very outdated. IDEs like Eclipse and vscode still rule the developer community and the ai copilot that are available for such tools do not have any hardware context. So, how do embedded software developers utilise AI to improve their productivity in absence of any hardware aware IDE that can enable ai based code generation or code editing

 

[jj_parkar95]

AI is beginning to help in embedded development, mainly by reducing repetitive work rather than replacing low-level engineering. Tools like GitHub Copilot are used for HAL setup, peripheral initialization, ISR templates, and test scaffolding, similar to how developers rely on ready-made resources like a jjsploit blox fruit script 2026 to save time instead of starting from scratch.

 

[olivia_49]

I feel like the ai code generation companies such as cursor and Windsurf have completely ignored the world of embedded software development. Is there anybody in this ecosystem who has been able to successfully utilize AI tools to to develop embedded software.

If yes I would like to see specific examples of how it has been useful as well as what tools were they using please. TIA.

PS: Feel free to mention any AI tools that are helping in hardware development overall

You’re right, most AI tools ignore embedded realities. Some engineers still use AI effectively for driver scaffolding, RTOS design, and debugging hardware issues. It helps as a reasoning assistant, not a full code generator.

 

[danadak]

I am using it for IOT work. I am not using their tools yet, just write a simple doc with expectations
and design goals, and then proceed with simple mod chats. ChatGPT so far but plan on using
Claude. ESP8266, ESP32, Networking, and simple embedded interface to sensors and the like.

 

[bidrohini]

AI is already useful in embedded development, particularly for generating peripheral drivers, state machines, unit tests, documentation, compiling errors etc. Cursor or GitHub Copilot can work effectively with PlatformIO projects for Arduino, ESP32 and STM32.

The limitation is hardware awareness: AI may generate compiling code with incorrect pins, registers, timing or electrical assumptions. I treat it as a productivity assistant, then verify everything against the datasheet and test it on real hardware .... especially interrupts, DMA, RTOS and safety-critical code.

 

[thaohuyenvovan]

I use AI quite a bit for embedded work now, mostly for checking ideas or getting through unfamiliar code faster.

It’s useful, but I still don’t trust it blindly. With hardware-related stuff especially, I always check the datasheet because AI can be confidently wrong.