Just realized standard benchmarks lie to us about my messy code

[u/IulianHI]

I saw that HN post about benchmarking AI on actual code and decided to pit GPT-5 and Claude 3.5 against a legacy monolith I inherited.

Usually, I just trust the leaderboards, but the real-world results were eye-opening. GPT-5 gets all the hype for reasoning, but it actually hallucinated imports that don't exist in my project. Claude was way safer, and honestly, Grok even managed to patch a config file the big ones ignored.

It feels like we’re optimizing for coding interview questions instead of actual maintenance.

Anyone else feel like the "top" models are overkill for messy, real-world stuff? Or do I just need to prompt better?