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Two things LLM coding agents are still bad at

kix.dev

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Re: Two things LLM coding agents are still bad at

#11
Most developers are also bad at asking questions. They tend to assume too many things from the start.

In my 25 years of software development I could apply the second critique to over half of the developers I knew. That includes myself for about half of that career.

Re: Two things LLM coding agents are still bad at

#12
post #11

Most developers are also bad at asking questions. They tend to assume too many things from the start. In my 25 years of software development I could apply the second critique to over half of the developers I knew. That includes myself for about half of that career.

But, just like lots of people expect/want self-driving to outperform humans even on edge cases in order to trust them, they also want "AI" to outperform humans in order to trust it.

So: "humans are bad at this too" doesn't have much weight (for people with that mindset).

It makes sense to me, at least.

Re: Two things LLM coding agents are still bad at

#13
On a more important level, I found that they still do really badly at even a minorly complex task without extreme babysitting.

I wanted it to refactor a parser in a small project (2.5K lines total) because it'd gotten a bit too interconnected. It made a plan, which looked reasonable, so I told it to do this in stages, with checkpoints. It said it'd done so. I asked it "so is the old architecture also removed?" "No, it has not been removed." "Is the new structured used in place of the old one?" "No, it has not." After it did so, 80% of the test suite failed because nothing it'd written was actually right.

Did so three times with increasingly more babysitting, but it failed at the abstract task of "refactor this" no matter what with pretty much the same failure mode. I feel like I have to tell it exactly to make changes X and Y to class Z, remove class A etc etc, at which point I can't let it do stuff unsupervised, which is half of the reason for letting an LLM do this in the first place.

Re: Two things LLM coding agents are still bad at

#15
I just run into this issue with claude sonet 4.5, asked it to copy/paste some constants from one file to another, a bigger chunk of code, it instead "extracted" pieces and named them so. As a last resort, after going back and forth it agreed to do a file/copy by running a system command. I was surprised that of all the programming tasks, a copy/paste felt challenging for the agent.

Re: Two things LLM coding agents are still bad at

#16

On a more important level, I found that they still do really badly at even a minorly complex task without extreme babysitting. I wanted it to refactor a parser in a small project (2.5K lines total) because it'd gotten a bit too interconnected. It made a plan, which looked reasonable, so I told it to do this in stages, with checkpoints. It said it'd done so. I asked it "so is the old architecture also removed?" "No, i…

Interesting. What model and tool was used?

I have seen similar failure modes in Cursor and VSCode Copilot (using gpt5) where I have to babysit relatively small refactors.

Re: Two things LLM coding agents are still bad at

#17
post #12
post #11

Most developers are also bad at asking questions. They tend to assume too many things from the start. In my 25 years of software development I could apply the second critique to over half of the developers I knew. That includes myself for about half of that career.

But, just like lots of people expect/want self-driving to outperform humans even on edge cases in order to trust them, they also want "AI" to outperform humans in order to trust it. So: "humans are bad at this too" doesn't have much weight (for people with that mindset). It makes sense to me, at least.

If we had a knife that most of the time cuts a slice of bread like the bottom p50 of humans cutting a slice of bread with their hands, we wouldn't call the knife useful.

Ok, this example is probably too extreme, replace the knife with an industrial machine that cut bread vs a human with a knife. Nobody would buy that machine either if it worked like that.

Re: Two things LLM coding agents are still bad at

#18
Agreed with the points in that article, but IMHO the no 1 issue is that agents only see a fraction of the code repository. They don't know whether there is a helper function they could use, so they re-implement it. When contributing to UIs, they can't check the whole UI to identify common design patterns, so they re-invent it.

The most important task for the human using the agent is to provide the right context. "Look at this file for helper functions", "do it like that implementation", "read this doc to understand how to do it"... you can get very far with agents when you provide them with the right context.

(BTW another issue is that they have problems navigating the directory structure in a large mono repo. When the agents needs to run commands like 'npm test' in a sub-directory, they almost never get it right the first time)

Re: Two things LLM coding agents are still bad at

#19
post #16

On a more important level, I found that they still do really badly at even a minorly complex task without extreme babysitting. I wanted it to refactor a parser in a small project (2.5K lines total) because it'd gotten a bit too interconnected. It made a plan, which looked reasonable, so I told it to do this in stages, with checkpoints. It said it'd done so. I asked it "so is the old architecture also removed?" "No, i…

Interesting. What model and tool was used? I have seen similar failure modes in Cursor and VSCode Copilot (using gpt5) where I have to babysit relatively small refactors.

Claude code. Whichever model it started up automatically last weekend, I didn't explicitly check.

Re: Two things LLM coding agents are still bad at

#20
post #8

4/5 times when Claude is looking for a file, it starts by running bash(dir c:\test /b) First it gets an error because bash doesn’t understand \ Then it gets an error because /b doesn’t work And as LLMs don’t learn from their mistakes, it always spends at least half a dozen tries (e.g. bash(cmd.exe /c dir c:\test /b )) before it figures out how to list files If it was an actual coworker, we’d send it off to HR

I have a list of those things in CLAUDE.md -> it seems to help (unless it's context is full, but you should never let it get close really).
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