owenthereal

I maintain jq (jqlang). I tend to like tools that are simple, composable, and transparent.

Recently, I started exploring AI agents, but got frustrated with the state of the ecosystem. Most tutorials and frameworks (LangChain, AutoGPT, etc.) felt like black boxes that added unnecessary layers of abstraction. Debugging a "ReasoningEngine" when it hallucinated was a nightmare.

I wanted to see if I could build a production-grade coding agent from first principles, using nothing but standard Python libraries.

I turned that experiment into a book: https://buildyourowncodingagent.com

The philosophy is "Zero Magic." We build an agent called "Nanocode" using:

- Pure Python (no frameworks, no SDKs) - requests for the LLM API (Claude/DeepSeek/Ollama) - subprocess for executing code and reading stdout/stderr - No Vector DBs (just simple file search) - A simple while loop for orchestration

The final result is in 500 lines of code. It can read/write files, run tests, fix its own bugs (using the error output), and run entirely locally if you use Ollama.

I've put up sample chapters on the site. I wrote this for engineers who want to understand the architecture of tools like Cursor or Claude Code without the marketing fluff.

Happy to answer any questions about the architecture, the "no-framework" approach, or why I think vector DBs are overkill for coding agents.