I Benchmarked 6 AI Coding Tools on a 50K-Line Codebase — Here’s How They Actually Wrote Production-Ready Code
We’ve all seen the demos. A clean greenfield project, a simple function, and the AI spits out perfect code in seconds. But that’s not real life.
Real codebases are ugly. They have 7-year-old conventions, half-documented utility functions, and a `utils.py` that’s 3,000 lines long. So I wanted to know: which AI coding tool actually survives contact with the mess we actually work in?
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I took six tools and gave each the same task: implement a “rate-limited, retryable API client for our internal event service” within my existing 50,000-line production Python codebase.
Here’s the dirty truth about what I found.
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The Setup: A Real Codebase, A Real Task
The codebase is a medium-sized backend for a B2B SaaS
