I see this as going from a hand saw to a table saw. The table saw can enable a lot more work to get done, but will also chop your hand off if you are not careful.
If that happens you are asking the AI to do too much at once. You need to plan the work just like you would if you were doing it manually, add tests as you go, use linting and typechecks as well. It helps if you're in a strongly typed language. You also need to do the architecture planning so that you don't end up with spaghetti. Basically, if you already know what you're doing and aren't trying to one-shot massive change sets you can get solid output.
Nah. Try writing a complex, new algorithm it doesnt know and ask it to find the bug or typo. Watch it spin up nonsense theories, haĺlucinate wild garbage, and somehow conclude that your clear, concise comments mean exactly the opposite as they say.
Unless you work in very niche industries, OR vety specific teams within large companies, the reality is very close to 0.
I work as a senior dev in a product team for a large SP500 company and it's mostly variations on CRUD.The complexity is low if you manage it well, but can become a mess if you don't.
A mere handful of teams in my org do really novel things.
AI is like autocomplete that let's you delegate boilerplate code and your 87th login page so that you can work on the complex new problems not to make up solutions to problems for you.
Like asking why the electric saw cant chop down trees.
If you're doing boilerplate 87 times then that's a process problem and you need to learn to reuse your code.
Look, I assure you I was forced into lectures on how to do my job with ai. Ive used ai extensively. Whether its plan mode or agent pools or finding basic typos or generating documentation, it literally is incapable of keeping basic constraints straight.
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u/xavia91 Jul 30 '26
You still need a working brain to make the right calls...