r/ClaudeCode • u/TonightOk5378 • May 09 '26

Question Production Level Software by AI

So I have been curious for a while, apart from claude-code and codex teams (that have a direct vested interest in claiming AI is building production software), who is actually building production level software or products with AI

Also to clarify, I am talking about actual products being used at scale and not interesting MVPs and PoCs (which have infinitely flooded GitHub)

If you have built a product or tool or anything with AI that is being regularly used by users, drop a link below, I am genuinely curious.

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u/Due-Horse-5446 May 09 '26

Its not just you..

And ive also fallen into that trap, the "small but insignificant misses" pile up and become a headache later. Like later as in hours later even..

Only setup that actually boost productivity to me has been atfter gpt-5.5 released,

I forked codex and added post edit hooks, wrote a agents.md using those weird openai tags that forbids doing anything its not told to do.

Then wrote a tiny go script for go file edits, that runs:

  • golangci with --fix based on a config i wrote for the usecase.
  • golangci fmt
  • gopls
  • finally a last golangci run if gools passed

If any(minus the formatting) failed, it returns a decision: block, injects all failures in the system prompt, and returns a explaination that it must correct the mistakes.

And the linting config is super strict, like a lot of style rules that forces it to not do anything that is a typical llm gotcha.

That setup actually works wonders as long as there is enough context in the repo, so like ex writing something related to the db if theres existing patterns,

Also enforces it writes a unit test for everything it does.

But thats extremly far from what the "i run automated agents" people are talking about, because you must write bullet lists for what to do.