Comment by TeMPOraL

When you zoom in, even this kind of work isn't uniform - a lot of it is still shaving yaks, boring chores, and tasks that are hard dependencies for the work that is truly cognitively demanding, but themselves are easy(ish) annoyances. It's those subtasks - and the extra burden of mentally keeping track of them - that sets the limit of what even the most skilled, productive engineer can do. Offloading some of that to AI lets one free some mental capacity for work that actually benefits from that.

Yeah, I'm not a dev but I can see why this is true, because it's also the argument I use in my job as an academic. Some people say "but your work is intellectually complex, how can you trust LLMs to do research, etc.?", which of course, I don't. But 80% of the job is not actually incrementally complex, it's routine stuff. These days I'm writing the final report of a project and half of the text is being generated by Gemini, when I write the data management plan (which is even more useless) probably 90% will be generated by Gemini. This frees a lot of time that I can devote to the actual research. And the same when I use it to polish a grant proposal, generate me some code for a chart in a paper, reformat a LaTeX table, brainstorm some initial ideas, come up with an exercise for an exam, etc.

Yes, things that get resolved very quickly with AI include fixing Linting errors, reorganizing CI pipelines, documenting agreed on requirements, building well documented commits, cleaning up temporary files used to validate dev work, building README.md's in key locations to describe important code aspects, implementing difficult but well known code, e.g. I got a trie security model implemented very quickly.

Tons of dev work is not exciting, I have already launched a solo dev startup that was acquired, and the 'fun' part of that coding was minimal. Too much was the scaffolding, CRUD endpoints, web forms, build scripts, endpoint documentation, and the true innovative stuff was such a small part of the whole project. Of the 14 months of work, only 1 month was truly innovative.

> Offloading some of that to AI lets one free some mental capacity for work that actually benefits from that.

Maybe, but I don't feel (of course, I could be wrong) that doing boring tasks take away any mental capacity; they feel more like fidgeting while I think. If a tool could do the boring things it may free my time to do other boring work that allows me to think - like doing the dishes - provided I don't have to carefully review the code.

Another issue (that I asked about yesterday [1]) is that seemingly boring tasks may end up being more subtle once you start coding them, and while I don't care too much about the quality of the code in the early iterations of the project, I have to be able to trust that whatever does the coding for me will come back and report any difficulties I hadn't anticipated.

> Reviewing such code is, thus, easier (and less demoralizing) than writing it.

That might well be true, but since writing it doesn't cost me much to begin with, the benefit might not be large. Don't get me wrong, I would still take it, but only if I could fully trust the agent to tell me what subtleties it encountered.

> there's too much unavoidable but trivial bullshit involved in software these days (build scripts, Dockerfies, IaaS). Preventing deep context switching on those is a big time saver.

If work is truly trivial, I'd like it to be automated by something that I can trust to do trivial work well and/or tell me when things aren't as trivial and I should pay attention to some detail I overlooked.

We can generally trust machines to either work reliably or fail with some clear indication. People might not be fully reliable, but we can generally trust them to report back with important questions they have or information they've learnt while doing the job. From the reports I've seen about using coding agents, they work like neither. You can neither trust them to succeed or fail reliably, nor can you trust them to come back with pertinent questions or information. Without either kind of trust, I don't think that "offloading" work to them would truly feel like offloading. I'm sure some people can work with that, but I think I'll wait until I can trust the agents.

[1]: https://news.ycombinator.com/item?id=44526048

Yeah, I don't fuck with Docker jank and cloud jank and shit. I don't fuck with dynamic linking. I don't fuck with lagged-ass electron apps. I don't fuck with package managers that need a SAT solver but don't have one. That's all going to be a hard no from me dawg.

When I said that after you've done all the other stuff, I was including cutting all the ridiculous bullshit that's been foisted on an entire generation of hackers to buy yachts for Bezos and shit.

I build clean libraries from source with correct `pkg-info` and then anything will build against it. I have well-maintained Debian and NixOS configurations that run on non-virtualized hardware. I use an `emacs` configuration that is built-to-specifications, and best-in-class open builds for other important editors.

I don't even know why someone would want a model spewing more of that garbage onto the road in front of them until you're running a tight, optimized stack to begin with, then the model emulates to some degree the things it sees, and they're also good.