Maybe I have some ridiculously high standard, but whenever I used it, I wasn’t happy with what it generated.
I noticed that the time it did it + the time for me to review it and possibly fixed was at best the same amount of time it took me to write, at worst it was longer.
For hard problems that I stumbled on it was useless.
For simple problems it worked and produced good code, but it still took less time for me to write it than waiting for Claude to finish thinking.
Everyone swears that they can produce good code with LLM and it is others who are bad, and LLM is force multiplier to them. But from what I see the only time it can speed up their work is if they never review it or even take time to understand the actual problem they are trying to solve.
I don’t know you, but it doesn’t sound like a high standards issue to me, sounds like a lack of process. I’ve been a thorough reviewer before AI, at least thorough in the ways that mattered, not nitpicking formatting. And I’ll tell you an automated reviewer today can catch more things before I have time to confirm the first item I find. There are still false positives, but it’s still more thorough than I have time to be. Bc of that it really helps including a round of automated review before looping in a human, regardless of who/what wrote the code.
The main kind of review problems AI still struggles with are the project direction ones: “does it make sense to implement this/like this?”, “should this be a new package instead?”, and things involving tacit knowledge that often goes undocumented “last time we did this, someone had to access prod on a Sunday” - so that’s what I focus my reviews on. And the other area is if you’re writing UI code, whether it’s a web app or a game, it’ll also struggle to determine what “feels” good to use, so it’ll need a human earlier in the loop.
Maybe I have some ridiculously high standard, but whenever I used it, I wasn’t happy with what it generated.
I noticed that the time it did it + the time for me to review it and possibly fixed was at best the same amount of time it took me to write, at worst it was longer.
For hard problems that I stumbled on it was useless.
For simple problems it worked and produced good code, but it still took less time for me to write it than waiting for Claude to finish thinking.
Everyone swears that they can produce good code with LLM and it is others who are bad, and LLM is force multiplier to them. But from what I see the only time it can speed up their work is if they never review it or even take time to understand the actual problem they are trying to solve.
I don’t know you, but it doesn’t sound like a high standards issue to me, sounds like a lack of process. I’ve been a thorough reviewer before AI, at least thorough in the ways that mattered, not nitpicking formatting. And I’ll tell you an automated reviewer today can catch more things before I have time to confirm the first item I find. There are still false positives, but it’s still more thorough than I have time to be. Bc of that it really helps including a round of automated review before looping in a human, regardless of who/what wrote the code.
The main kind of review problems AI still struggles with are the project direction ones: “does it make sense to implement this/like this?”, “should this be a new package instead?”, and things involving tacit knowledge that often goes undocumented “last time we did this, someone had to access prod on a Sunday” - so that’s what I focus my reviews on. And the other area is if you’re writing UI code, whether it’s a web app or a game, it’ll also struggle to determine what “feels” good to use, so it’ll need a human earlier in the loop.