Comment by viraptor

> Which is fine if you trust the LLM to write great code, and great tests for the code, but fundamentally you have to have 100% trust, 99.9% is not going to be enough in any serious industry, would it ?

This is lacking a lot of nuance. There are many types of code. There are many situations where I'm analysing something one-off and if I get 33% success ratio, but can easily verify the result, I'm happy - still saved me time and money. They're are situations where I'm generating graphs from some dataset and I don't have to trust anything - I know what the result should look like, I just need the agent to drive matplotlib. There are low stakes dashboards which I'm happy to generate and develop entirely via agents - they'll embed the updated screenshots in PRs that I can yolo-merge - worst case is that someone complains about something not working next time they visit. Then there's lots of experimenting which was never stopped to hit production anyway.

Finally after all of that you get code that's actually part of deployable features. Of course the trust is nowhere near 100%, but if you have a healthy testing process (e2e, validating different browsers, or whatever is appropriate for your environment), then what's your trust in human developer+review? Because mine is nowhere near 100% either.

In practice there are places where I extremely don't care about the code and never wanted it anyway, places where I'll read the code to check the design or just in case, and places which agents are not allowed to touch (medical billing rules for example).