alt Hacker NewsKinda funny but I think LLM-assisted workflows are frequently slow -- that is, if I use the "refactor" features in my IDE it is done in a second, if I ask the faster kind of assistant it comes back in 30 seconds, if I ask the "agentic" kind of assistant it comes back in 15 minutes.
I asked an agent to write an http endpoint at the end of the work day when I had just 30 min left -- my first thought was "it took 10 minutes to do what would have taken a day", but then I thought, "maybe it was 20 minutes for 4 hours worth of work". The next day I looked at it and found the logic was convoluted, it tried to write good error handling but didn't succeed. I went back and forth and ultimately wound up recoding a lot of stuff manually. In 5 hours I had it done for real, certainly with a better test suite than I would have written on my own and probably better error handling.
See https://www.reddit.com/r/programming/comments/1lxh8ip/study_...
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I've already written about this several times here. I think the current trend of LLMs chasing benchmark scores are going in the wrong direction at least as programming tools. In my experience they get it wrong with enough probability, so I always need to check the work. So I end up in a back and forth with the LLM and because of the slow responses it becomes a really painful process and I could often have done the task faster if I sat down and thought about it. What I want is an agent that responds immediately (and I mean in subseconds) even if some benchmark score is 60% instead of 80%.
The only thing I've found that LLM speeds up my work is a sort of advanced find replace.
A prompt like " I want to make this change in the code where any logic deals with XXX. To be/do XXX instead/additionally/somelogicchange/whatever"
It has been pretty decent at these types of changes and saves time of poking though and finding all the places I would have updated manually in a way that find/replace never could. Though I've never tried this on a huge code base.
I guess it depends? The "refactor" stuff, if your IDE or language server can handle it, then yeah I find the LLM slower for sure. But there are other cases than an LLM helps a lot.
I was writing some URL canonicalization logic yesterday. Because we rolled this out as an MVP, customers put URLs in all sorts of ways and we stored it into the DB. My initial pass at the logic failed on some cases. Luckily URL canonicalization is pretty trivially testable. So I took the most used customers from our DB, send them to Claude and told Claude to come up with the "minimum spanning test cases" that cover this behavior. This took maybe 5-10 sec. I then told Zed's agent mode using Opus to make me a test file and use these test cases to call my function. I audited the test cases and ended up removing some silly ones. I iterated on my logic and that was that. Definitely faster than having to do this myself.
All the references to LLMs in the article seemed out-of-place like poorly done product placement.
LLMs are the anti-thesis of fast. In fact, being slow is a perceived virtue with LLM output. Some sites like Google and Quora (until recently) simulate the slow typed output effect for their pre-cached LLM answers, just for credibility.
I'm consistently seeing personal and shared anecdotes of a 40%-60% speedup on targeted senior work.
As much as I like agents, I am not convinced the human using them can sit back and get lazy quite yet!
I switch to vs code from cursor many times a day just to use their python refactoring feature. The pylance server that comes with cursor doesn't support refactoring.
Not only that, I am already typing enough for coding, I don't want to type on chat windows as well, and so far the voice assistance is so so.
As a counter example (re: agents), I routinely delegate simple tasks to Claude Code and get near-perfect results. But I've also had experiences like yours where I ended up wasting more time than saved. I just kept trying with different types of tasks, and narrowed it down to the point where I have a good intuition for what works and what doesn't. The benefit is I can fire off a request on my phone, stick it in my pocket, then do a code review some time later. This process is very low mental overhead for me, so it's a big productivity win.