this post was submitted on 20 Nov 2025
384 points (99.0% liked)
Technology
76962 readers
3248 users here now
This is a most excellent place for technology news and articles.
Our Rules
- Follow the lemmy.world rules.
- Only tech related news or articles.
- Be excellent to each other!
- Mod approved content bots can post up to 10 articles per day.
- Threads asking for personal tech support may be deleted.
- Politics threads may be removed.
- No memes allowed as posts, OK to post as comments.
- Only approved bots from the list below, this includes using AI responses and summaries. To ask if your bot can be added please contact a mod.
- Check for duplicates before posting, duplicates may be removed
- Accounts 7 days and younger will have their posts automatically removed.
Approved Bots
founded 2 years ago
MODERATORS
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
For example the tools for the really tedious stuff, like large codebase refactoring for style keeping, naming convention adherence, all kinds of code smells, whatever. Lots of those tools have gotten ML upgrades and are a lot smarter and more powerful than what I remember from a decade ago (intellisense, jetbrains helper functions, various opinionated linter toolchains, and so forth).
While I’ve only experimented a little with some the more explicitly generative LLM-based coding assistant plugins, I’ve been impressed (and a little spooked) at how good they often were at guessing what I’m doing way before I finished doing it.
I haven’t used the prompt-based LLMs at all, because I’m just not used to it, but I’ve watched nearby devs use them for stuff like manipulating a bunch of files in a repeated pattern, breaking up a spaghetti method into reusable functions, or giving a descriptive overview of some gnarly undocumented legacy code. They seem pretty damn useful.
I’ll integrate the prompt-based tools once I can host them locally.
In the work I have done with Claude over the past months, I have not learned to trust it for big things - if anything the opposite. It's a great tool, but - to anthropomorphize - it's "hallucination rate" is down there with my less trustworthy colleagues. Ask it to find all instances of X in this code base of 100 files of 1000 lines each... yeah, it seems to get bored or off-track quite a bit, misses obvious instances, finds a lot but misses too much to say it's really done a thorough review. If you can get it to develop a "deterministic process" for you (shell script or program) and test that program, then that you can trust more, but when the LLM is in the loop it just isn't all there all the time, and worse: it'll do some really cool and powerful things 19/20 times, then when you think you can trust it it will screw up an identical sounding task horribly.
I was just messing around with it and I had it doing a files organization and commit process for me, was working pretty good for a couple of weeks, then one day it just screwed up and irretrievably deleted a bunch of new work. Luckily it was just 5 minutes of its own work, but still... that's not a great result.