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You seem to be saying that as if it’s a good thing, but that’s terrifying.

The article says they “get the right answer 80% of the time”. That’s abysmal when you don’t know what you’re doing. Software which is 20% bugs is software you can’t rely on. Depending on what it does, it can be actively harmful.

Being a “magician (…) among mere mortals” is not a positive. We live in an interconnected society where the actions of others affect us. It would be nice if you can trust what other people are doing when they’re dealing with your water supply, electricity, food production, hospitals…




That's why I included that 80% accuracy estimate: to hint that these tools are massively less useful if you don't know what you're doing with them.

If you have years of expertise already they give you wings.


> Software which is 20% bugs is software you can’t rely on.

No one is saying to take the output and immediately ship it. It still needs to be finished and tested. What's important is what is ultimately delivered; less important is what steps brought you to that point.

That said I suspect good testing will become more highly-valued as AI use increases. Maybe there's a form of TDD that can develop, with the human mostly writing tests and AI prompts?


> No one is saying to take the output and immediately ship it.

On the contrary, that is exactly what is happening: https://news.ycombinator.com/item?id=35384604


Yes, good productivity will be amplified and so will bad. There's people on my team that are super productive but cut corners, don't code in as a maintainable way etc. I usually get a slow senior dude to gate their PR until it passes. But it might just be less hassle to let the senior dudette to get more productive with an AI. We'll see...


It's possible that all this research in programming language safety, specification, static analysis that most of us have been safely ignoring for the past... well, forever... will finally become a staple requirement, instead of programming itself.




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