>If you're enough of an expert to critically judge the output, you're probably just as well off doing the reasoning yourself.
Thought requires energy. A lot of it. Humans are for more efficient in this regard than LLMs, but then a bicycle is also much more efficient than a race car. I've found that even when they are hilariously wrong about something, simply the directionality of the line of reasoning can be enough to usefully accelerate my own thought.
Look, I've been experimenting with this for the past year, and this is definitely the happy path.
The unhappy path, which I've also experienced, is that the model outputs something plausible but false but that aligns with an area where my thinking was already confused and sends me down the wrong path.
I've had to calibrate my level of suspicion, and so far using these things more effectively has always been in the direction that more suspicion is better.
There's been a couple times in the last week where I'm working on something complex and I deliberately don't use an LLM since I'm now actively afraid they'll increase my level of confusion.
There are phases in every developer’s growth, where you transition from asking coworkers or classmates, to asking on stack overflow, to reading stack overflow, to reading docs and man pages and mailing lists and source code.
I think like you, I worry that LLMs will handicap this trajectory for people newer in the field, because GPT-4/Sonnet/Whatever are an exceptionally good classmate/coworker. So good that you might try to delay progressing along that trajectory.
But LLMs have all the flaws of a classmate: they aren’t authoritative, their opinions are strongly stated but often based on flimsy assumptions that you aren’t qualified to refute or verify, and so on.
I know intellectually that the kids will be alright, but it’ll be interesting to see how we get there. I suspect that as time goes on people will simply increase their discount rate on LLM responses, like you have, until they get dissatisfied with that value and just decide to get good at reading docs.
Thought requires energy. A lot of it. Humans are for more efficient in this regard than LLMs, but then a bicycle is also much more efficient than a race car. I've found that even when they are hilariously wrong about something, simply the directionality of the line of reasoning can be enough to usefully accelerate my own thought.