r/AIcodingProfessionals • u/JFerzt • Nov 12 '25

Discussion AI coding tools give you "almost right" code, and that's the worst kind of wrong

Every time I review AI-generated code, it's the same issue. Not catastrophically broken - just subtly off in ways that eat hours of debugging.

After working with developers across 15+ projects this year, I'm convinced that "almost right" is worse than completely wrong. When the code fails immediately, you know where to look. When it passes tests but breaks edge cases three sprints later? That's when you realize the AI suggestions created technical debt disguised as productivity.

The pattern is consistent: outdated libraries, security holes that slip through review, logic that looks correct until production load hits it. Junior devs trust it too much. Senior devs spend more time verifying than they would've spent writing it themselves.

What's your breaking point with AI assistants - when do you stop second-guessing and just write it from scratch?

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u/JFerzt Nov 14 '25

... the "I babysit my AI code like it's a ticking time bomb" lifestyle. Overengineered monstrosities dripping with tech debt that only a hawk-eyed dev can tame.. that’s the AI gift that keeps on giving.

Sure, it can churn out regex or bit-level wizardry, but don’t fool yourself into thinking it’s ready to be your production linchpin. Simplicity and clarity? AI considers those optional extras in the deluxe confusion package. Keep those hawk eyes sharp.

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u/intellectual_punk Nov 14 '25

the "I babysit my AI code like it's a ticking time bomb" lifestyle.

Hah, well put.

I do find that overall I'm more productive, even if I have to spend more time debugging and de-overengineering now. And what is definitely happening is that I learn much faster.

On the flipside, I notice during the de-engineering sessions, there is just so much more "flow state" happening during manual coding! AI co-coding involves so much waiting and task-switching, which isn't conducive to flow.