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LLMs can be exhausting

tomjohnell.com

91–100 of 232 posts

Re: LLMs can be exhausting

#91

Earlier quoted context omitted.

I always wonder where HNers worked or work; we do ERP and troubleshooting on legacy systems for medium to large corps; PRs by humans were always pretty random and barely looked at as well, even though the human wrote it (copy/pasted from SO and changed it somewhat); if you ask what it does they cannot tell you. This is not an exception, this is the norm as far as I can see outside HN. People who talk a lot, don't und…

I would hope that most people who are technically competent enough to be on HN are technically competent enough to quit orgs with coding standards that bad. Or, they're masochists who have taken on the chamllenge of working to fix them

Neither of those. The pay is great and if all leadership cares about is making the whole company "AI Native" and pushing bullshit diffs, I'll play ball.

Re: LLMs can be exhausting

#93
post #62

[flagged]

Actually I find verification pretty lightweight, because I tend to decompose tasks intended for AI to a level where I already know the "shape" of the code in my head, as well as what the test cases should look like. So reviewing the generated code and tests for me is pretty quick because it's almost like reading a book I've already read before, and if something is wrong it jumps out quickly.

That said I have a different theory for why AI coding can be exhausting: the part where we translate concrete ideas into code, where the flow state usually occurs, is actually somewhat meditative and relaxing. But with that offloaded to AI, we're left mostly alternating between the cognitively intense idea-generation / problem-solving phases, and the quick dopamine hits of seeing things work: https://news.ycombinator.com/item?id=46938038

Re: LLMs can be exhausting

#95

Does anyone else see this as dystopian? Someone is unironically writing about how exhausted they are and up at night thinking about how they can be a better good-boy at prompting the LLM and reminding us how we shouldn't cope by blaming the AI or its supposed limitations (context size, etc). This is not a dig at the author. It just seems crazy that this is an unironic post. It's like we are gleefully running to the "…

Yup, and we arr wasting our weekends worried about keeping pace in an imagined red queen's race. Another similar post today.

https://news.ycombinator.com/item?id=47388646

Re: LLMs can be exhausting

#96
post #3

I find LLMs so much more exhausting than manual coding. It’s interesting. I think you quickly bump into how much a single human can feasibly keep track of pretty fast with modern LLMs. I assume until LLMs are 100% better than humans in all cases, as long as I have to be in the loop there will be a pretty hard upper bound on what I can do and it seems like we’ve roughly hit that limit. Funny enough, I get this feeling…

> I find LLMs so much more exhausting than manual coding

I do as well, so totally know what you're talking about. There's part of me that thinks it will become less exhausting with time and practice.

In high school and college I worked at this Italian place that did dine in, togo, and delivery orders. I got hired as a delivery driver and loved it. A couple years in there was a spell where they had really high turnover so the owners asked me to be a waiter for a little while. The first couple months I found the small talk and the need to always be "on" absolutely exhausting, but overtime I found my routine and it became less exhausting. I definitely loved being a delivery driver far more, but eventually I did hit a point where I didn't feel completely drained after every shift of waiting tables.

I can't help but think coding with LLMs will follow a similar pattern. I don't think I'll ever like it more than writing the code myself, but I have to believe at some point I'll have done it enough that it doesn't feel completely draining.

Re: LLMs can be exhausting

#98
I think the fatigue is specifically about opacity. When you review agent output, you're not just checking correctness—you're trying to reconstruct what state the agent was in when it made each call. That reconstruction is the expensive part. If you already know the agent's tool pattern and drift trajectory while it ran, review shifts from guessing to confirming. Still work, but a different kind.

Re: LLMs can be exhausting

#99
I wonder if the same people using "agentic AI" are the same that spend days setting up the "perfect" work environment with four screens.

I find LLMs are great for building ideas, improving understanding and basic prototyping. This is more useful at the start of the project lifecycle, however when getting toward release it's much more about refactoring and dealing with large numbers of files and resources, making very specific changes e.g. from user feedback.

For those of us with decades of muscle memory who can fix a bug in 30 seconds with a few Vim commands, LLMs are very likely to be slower in most coding tasks, excepting prototyping and obscure bug spotting.

Re: LLMs can be exhausting

#100
post #3

I find LLMs so much more exhausting than manual coding. It’s interesting. I think you quickly bump into how much a single human can feasibly keep track of pretty fast with modern LLMs. I assume until LLMs are 100% better than humans in all cases, as long as I have to be in the loop there will be a pretty hard upper bound on what I can do and it seems like we’ve roughly hit that limit. Funny enough, I get this feeling…

Theory of Bounded Rationality applies. Tech tools scale systemic capability limits. 3 inch chimp brain limits dont change. The story writes itself.
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