this post was submitted on 15 Aug 2025
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[โ€“] AppleStrudel@reddthat.com 2 points 14 hours ago (1 children)

I've just spent 90 minutes a few days ago this week, going through 50 lines of functional code. Understanding it fully, giving suggestions of improvements, looking through the logs to confirm my colleague didn't miss anything, doing my own testing, etc, etc. AI is really good at quick and dirty prototyping, but it's benefits as a coding assistant that touches on your code go down very significantly once you need to understand it as well as if you've written it, and you can't put your name to anything that'll eventually see production if you don't fully understand what's going on.

As a neovim user that can hop around and can do "menial tasks" with a few quick strokes and a macro recording as fast as it'll take the AI to formulate a response, and with much more determinism than an AI ever could. I've found that it hasn't saved a whole lot of time like most tech CEOs are really hoping that it'll do.

All I'm saying is, that AI is a very powerful and helpful tool (the perfect rubber ducky infact ๐Ÿฆ†). But I haven't yet find it truly saving me any time when I am reviewing it's output to my standards, and that's the conclusion I got from a recent Standford finding that was presented for GitHub Copilot too, that AI seems to have sped up development time by around 15-20% on average once you've factored in the revisiting of recent code and rewriting of them. With the caveat that a non-insignificant number of people would actually end up becoming less efficient when using AI, especially for high complexity work.

[โ€“] Jayjader@jlai.lu 2 points 7 hours ago

Ok, thanks for clarifying. I think we're pretty much on the same page. I've not yet used it as a rubber ducky for debugging, but as a rubber ducky for feature planning, UI brainstorming , and similar "fuzzy specs" it's been great for realizing how much I need to be precise and explicit when writing down my plan/needs.