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If we don’t fully trust AI output, why do we still ship it without checking everything?

1 of Michael's comment in this thread · View thread on Reddit ↗

u/Double_Try1322 wrote (the comment Michael replied to):

I keep noticing something in teams using AI tools for code and debugging. People say they don’t fully trust the output, but in practice they also don’t always verify it deeply. A quick glance, run the tests, merge, move on. I’m not judging it, I get why it happens. Deadlines, co

u/michaelnovati replied ·
This is off topic for the sub but I have an expert answer anyways. First off, we do need to check AI. Humans make more mistakes and their code needs to be checked. But AI itself can do the checking and there are strategies to start with that produce fewer mistakes. The async nature of AI,.that you can run effectively infinite agents in parallel asynchronously, means that if you can manage them well, they can replace a lot of work humans would do. But the exact problem you point out is actually why bootcamps are toast and junior jobs are in trouble and seniors are flourishing... the taste and judgment needed to sign off on AI code and to manage AI requires a huge amount of experience that cannot be rushed or faked just because of your capacities or potential. Building systems not that are objectively correct or false, but building them to surface signals needed to make a judgment call efficiently. People who have this are massively more productive with AI. People who don't are ones who say things like AI is a scam, AI slows people down but makes them think they are more productive, AI hallucinates, etc...