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> Even on personal projects, if I go through a few major features without reviewing the code, I always end up doing massive revisions that steal hours of my tim

> Even on personal projects, if I go through a few major features without reviewing the code, I always end up doing massive revisions that steal hours of my time and fill me with rage in the process. Where LLMs excel is in code-level bugs (as opposed to system bugs, design bugs, architecture bugs, integration bugs, etc). Talk with an LLM, ask them to rate both code and estimate dev experience based on that code, and you will see what they value: Code that passes all the tests is a 10/10, while a codebase designed with opaque data types, Parse-Don't-Validate for all data, isolated interfaces, a built-for-replacement-not-for-extension philosphy will get a 6/10 because an out of bounds error was found. IOW, they are very strongly tuned to value code that has no errors which can be picked up by linters or similar, while humans work the opposite way - we very highly value code that is easy to maintain, even if they do have a few errors picked up by the linter.

re-thc 5d ago
> Where LLMs excel is in code-level bugs (as opposed to system bugs, design bugs, architecture bugs, integration bugs, etc). Blame the benchmarks game. They're optimizing for that and that's what those things are measuring.
zem 5d ago
I have found that claude (opus 4.8 and 5) can do a very good job of implementing good architecture and system design if I can just steer it right. left to its own devices it does produce less than optimal code, but if I just spend a few minutes explaining how some pattern will improve the code, claude will go do it the right way, and can even have a pretty sensible discussion about the tradeoffs involved. so it does know about good code architecture and patterns, it just doesn't have the taste and initiative to use them without being told.
- lelanthran 5d ago
  > left to its own devices it does produce less than optimal code, but if I just spend a few minutes explaining how some pattern will improve the code, But that requires actually reading the output, which I am pretty certain only a rounding error of programmers are doing at this point.
  - sevenseacat 5d ago
    And the next time your agent comes across the same problem, it will likely use the same previous inefficient way again (despite all attempts to codify the instruction in AGENTS.md, CLAUDE.md, skills, whatever)
cseleborg 5d ago
> they are very strongly tuned to value code that has no errors which can be picked up by linters or similar, while humans work the opposite way This is a really valuable insight! It resonates well with my own experience revewing AI-authored code: I look hard at interfaces, architecture and performance, and merely glance over code that just "gets the job done", because if it works, I'm not worried about it. Now I can express that dichotomy much more clearly -- thank you!

re-thc 5d ago

> Where LLMs excel is in code-level bugs (as opposed to system bugs, design bugs, architecture bugs, integration bugs, etc). Blame the benchmarks game. They're optimizing for that and that's what those things are measuring.

zem 5d ago

I have found that claude (opus 4.8 and 5) can do a very good job of implementing good architecture and system design if I can just steer it right. left to its own devices it does produce less than optimal code, but if I just spend a few minutes explaining how some pattern will improve the code, claude will go do it the right way, and can even have a pretty sensible discussion about the tradeoffs involved. so it does know about good code architecture and patterns, it just doesn't have the taste and initiative to use them without being told.

lelanthran 5d ago
> left to its own devices it does produce less than optimal code, but if I just spend a few minutes explaining how some pattern will improve the code, But that requires actually reading the output, which I am pretty certain only a rounding error of programmers are doing at this point.
- sevenseacat 5d ago
  And the next time your agent comes across the same problem, it will likely use the same previous inefficient way again (despite all attempts to codify the instruction in AGENTS.md, CLAUDE.md, skills, whatever)

cseleborg 5d ago

> they are very strongly tuned to value code that has no errors which can be picked up by linters or similar, while humans work the opposite way This is a really valuable insight! It resonates well with my own experience revewing AI-authored code: I look hard at interfaces, architecture and performance, and merely glance over code that just "gets the job done", because if it works, I'm not worried about it. Now I can express that dichotomy much more clearly -- thank you!