Lol this person talks about easing into LLMs again two weeks after quitting cold turkey. The addiction is real. I laugh because I’m in the same situation, and see no way out other than to switch professions and/or take up programming as a hobby in which I purposefully subject myself to hard mode. I’m too productive with it in my profession to scale back and do things by hand — the cat is out of the bag and I’ve set a race pace at work that I can’t reasonably retract from without raising eyebrows. So I agree with the author’s referenced post that finding ways to still utilize it while maintaining a mental map of the code base and limiting its blast radius is a good middle ground, but damn it requires a lot of discipline.
Two things LLM coding agents are still bad at
131–140 of 382 posts
Re: Two things LLM coding agents are still bad at
#132Earlier quoted context omitted.
In these cases I explicitly tell the llm to make as few changes as possible and I also run a diff. And then I reiterate with a new prompt if too many things changed.
You can always run a diff. But how good are people at reading diffs? Not very. It's the kind of thing you would probably want a computer to do. But now we've got the computer generating the diffs (which it's bad at) and humans verifying them (which they're also bad at).
Yeah, pick one for you to do, the other for the LLMs to do, ideally pick the one you're better at, otherwise 50/50 you'll actually become faster.
Re: Two things LLM coding agents are still bad at
#133On 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…
I was hoping that LLMs being able to access strict tools, like Gemini using Python libraries, would finally give reliable results. So today I asked Gemini to simplify a mathematical expression with sympy. It did and explained to me how some part of the expression could be simplified wonderfully as a product of two factors. But it was all a lie. Even though I explicitly asked it to use sympy in order to avoid such hal…
The obvious point has to be made: Generating formal proofs might be a partial fix for this. By contrast, coding is too informal for this to be as effective for it.
Re: Two things LLM coding agents are still bad at
#134Lol this person talks about easing into LLMs again two weeks after quitting cold turkey. The addiction is real. I laugh because I’m in the same situation, and see no way out other than to switch professions and/or take up programming as a hobby in which I purposefully subject myself to hard mode . I’m too productive with it in my profession to scale back and do things by hand — the cat is out of the bag and I’ve set…
> I’ve set a race pace at work that I can’t reasonably retract from without raising eyebrows
Why do this to yourself? Do you get paid more if you work faster?
Re: Two things LLM coding agents are still bad at
#135The other day, I needed Claude Code to write some code for me. It involved messing with the TPM of a virtual machine. For that, it was supposed to create a directory called `tpm_dir`. It constantly got it wrong and wrote `tmp_dir` instead and tried to fix its mistake over and over again, leading to lots of weird loops. It completely went off the rails, it was bizarre.
Re: Two things LLM coding agents are still bad at
#136Recently, I asked Codex CLI to refactor some HTML files. It didn't literally copy and pasted snippets here and there as I would have done myself, it rewrote them from memory, removing comments in the process. There was a section with 40 successive links with complex URLs. A few days later, just before deployment to production, I wanted to double check all 40 links. First one worked. Second one worked. Third one worke…
Not code, but I once pasted an event announcement and asked for just spelling and grammar check. LLM suggested a new version with minor tweak which I copy pasted back.
Just before sending I noticed that it had moved the event date by one day. Luckily I caught it but it taught me that you never should blindly trust LLM output even with super simple tasks, no relevant context size, clear and simple one sentence prompt.
LLM's do the most amazing things but they also sometimes screw up the simplest of tasks in the most unexpected ways.
Re: Two things LLM coding agents are still bad at
#137I sometimes give LLM random "easy" questions. My assessment is still that they all need the fine print "bla bla can be incorrect"
You should either already know the answer or have a way to verify the answer. If neither, the matter must be inconsequential like just a child like curiosity. For example, I wonder how many moons Jupiter has... It could be 58, it could be 85 but either answer won't alter any of what I do today.
I suspect some people (who need to read the full report) dump thousand page long reports into LLM, read the first ten words of the response and pretend they know what the report says and that is scary.
Re: Two things LLM coding agents are still bad at
#138Lol this person talks about easing into LLMs again two weeks after quitting cold turkey. The addiction is real. I laugh because I’m in the same situation, and see no way out other than to switch professions and/or take up programming as a hobby in which I purposefully subject myself to hard mode . I’m too productive with it in my profession to scale back and do things by hand — the cat is out of the bag and I’ve set…
> I’ve set a race pace at work that I can’t reasonably retract from without raising eyebrows Why do this to yourself? Do you get paid more if you work faster?
It started as a mix of self-imposed pressure and actually enjoying marking tasks as complete. Now I feel resistant to relaxing things. And no, I definitely don’t get paid more.
Re: Two things LLM coding agents are still bad at
#139Earlier quoted context omitted.
i find the chirpy affirmative tone of claude to be rage inducing
This. The biggest reason I went with OpenAI this month...
My "favorite" is when it makes a mistake and then tries gaslight you into thinking it was your mistake and then confidently presents another incorrect solution.
All while having the tone of an over caffeinated intern who has only ever read medium articles.
Re: Two things LLM coding agents are still bad at
#140Agreed 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. "Loo…
I wonder if a large context model could be employed here via tool call. One of the great things Gemini chat can do is ingest a whole GitHub repo. Perhaps "before implementing a new utility or helper function, ask the not-invented-here tool if it's been done already in the codebase" Of course, now I have to check if someone has done this already.
Claude can use use tools to do that, and some different code indexer MCPs work, but that depends on the LLM doing the coding to make the right searches to find the code. If you are in a project where your helper functions or shared libs are scattered everywhere it’s a lot harder.
Just like with humans it definitely works better if you follow good naming conventions and file patterns. And even then I tend to make sure to just include the important files in the context or clue the LLM in during the prompt.
It also depends on what language you use. A LOT. During the day I use LLMs with dotnet and it’s pretty rough compared to when I’m using rails on my side projects. Dotnet requires a lot more prompting and hand holding, both due to its complexity but also due to how much more verbose it is.