After AI wrote his whole Python package, he asks: how can we ever trust AI code in production?
Lukee67 · reddit · 2026-09-05
A developer describes an experiment using ChatGPT Sol to implement a deterministic NLP algorithm he designed for analyzing scientific literature. The AI handled implementation, boilerplate, collected an open-access corpus, and ran a full test suite — without him ever running code locally. The result was tidy, modular, and working.
But it raised a core doubt: how do you trust AI-written code meets specs and is bug-free? Letting AI test itself means trusting AI entirely. The only safe path seems to be reverse-engineering the output to verify compliance — especially for mission-critical software, to avoid client lawsuits.
His paradox: coding is easier than reverse engineering, so if you must audit the result anyway, why not write it yourself? The post sparked discussion on trust boundaries for AI coding.
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