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Efficient bug fixing with AI

06 Sep 2025

This morning, I was contacted by Victor Stewart, who has been contributing to picoquic for a long time. Victor is using the new Codex extension that OpenAI released last week. He was impressed with the results and the amazing gains in productivity.

I started from a very skeptical point of view. I saw initial attempts at using various AI systems to generate code, and they required a rather large amount of prompting to create rather simple code. I have read reports like Death by a thousand slops by Daniel Steinberg, who rails about sloppy bug reports generated by AI. So I asked Victor whether we could do a simple trial, such as fixing a bug.

Victor picked one of the pending bugs in the list of issues, issue #1937. I had analyzed that bug before, but it was not yet fixed. So we tried. While we were chatting over slack, Victor prompted Codex, and got a first reply with an explanation of the bug and a proposed fixed, more or less in real time. I asked whether it could generate a regression test, and sure enough it did just that. Another prompt to solve some formatting issues, and voila, we got a complete PR.

I was impressed. The fix itself is rather simple, but even for simple bugs like that we need to spend time analysing, finding the repro, writing a regression test, and writing a patch. We did all that in a few minutes over a chat. It would probably have required at least a couple hours of busy work. The Codex system requires a monthly subscription fee, and probably spending some time learning the tool and practicing. But when I see this kind of productivity gain, I am very tempted to just buy it!

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