Claude Code: An Agentic cleanroom analysis

Summary

From 2.5 million tokens of minified code to architectural insights—a human-AI collaboration <aside> 💡 This entire report was generated by Claude Opus 4, with the help of almost all of the major flagship models. If you want the most interesting read, start with Novel Components: The Innovations That Define Claude Code. If you want the most fun read, start with An LLM's Perspective: What It's Actually Like to Receive These Instructions. However, the 4000 word write-up on the process of writing this report was manually written with no AI assistance. If you’d like to read that first, go to How to agentically deconstruct CC . </aside> <aside> ✉️ A Note from Hrishi This project started with simple curiosity. I wanted to understand Claude Code, which to me is the best Agentic coding tool (even though the competition is close). Initially, I thought it would be straightforward—just an LLM and a few tools in a loop. I was wrong. It turned out to be far more complex, with tons of novel components I hadn't expected. The only available code was the compiled, minified version on npm—about 2.5 million dense tokens. To tackle this, I worked with multiple AI subagents operating on different pieces of the code (with other scripts written to extract prompts and annotate pieces). I manually ferried questions and insights back and forth, reviewed outputs to check for hallucinations, double-checked results, and carefully separated actual Claude Code from stale imported dependencies that weren't tree-shaken (shook? not sure). The process involved: Five batches of four rounds with completely new subagents (mostly Gemini 2.5 Pro) Splitting the code into four parts for parallel analysis Generating about 300K tokens worth of intermediate analysis Writing multiple scripts using Cursor to extract strings, chunk and annotate code Condensing everything into a comprehensive report What's remarkable is that this only took a day. Before LLMs, this kind of analysis would have taken months—if it was p...