this post was submitted on 17 Sep 2026
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Everybody's Lost Their Minds (www.netmeister.org)
submitted 20 hours ago* (last edited 20 hours ago) by inari@piefed.zip to c/technology@lemmy.world
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[–] DarrinBrunner@lemmy.world 35 points 20 hours ago (2 children)

I suppose I should quote a part, since no one else will read the dreaded wAlL Of tEXt.

Is this short enough for you?

AI helps people find more vulnerabilities in existing code. To address those vulnerabilities, people use AI to generate patches. The resulting pull requests are then "reviewed" by AI. That is, the more AI is in the loop, the less we understand the code base. The mystical "human in the loop" often is nothing more than a rubber stamp.

So what happens when things go bump? Complex systems fail in complex ways, and debugging code is an order of magnitude harder than writing code. Debugging somebody else's code is harder still. Trying to debug large, complex, distributed systems consisting of components that are effectively opaque to your entire organization is going to be impossible.

[–] MalReynolds@slrpnk.net 11 points 15 hours ago (1 children)

You know what's harder than debugging? Maintenance, especially of someone else's code, keeping up to date with security exploits, revamping UX etc. which is why github is full of write only (as in never read, never changed) slop projects. That's a critical part of a software project with any lifespan.

And then there's integrating new functionality.

Without a solid architecture (which AI sucks at), strict code readability standards (ditto, but improving) and nuanced reviewing of potential additions to the codebase (ditto) what you get is a spagettified mess. It ends up costing more to maintain and improve than just starting fresh.

The promise of the AI bros was that by the time you needed to maintain or extend, you could just get the next version of Claude or whatever to do it, as it's capabilities would have improved. That was a lie, and LLMs have hit a logarithmic wall where throwing more compute and bigger training sets at it produces diminishing returns. No AGI for you (unless some genius finds a new architecture). Frameworks / harnesses are still improving, but there's only so far that can go.

The amount of technical debt that has been racked up by the last two years of AI coding is staggering to contemplate, and the industry will be dealing the fallout for years. Companies will collapse, and god help you if you've used it liberally in a codebase as large as an OS - looking at you Microslop.

[–] Yaky@slrpnk.net 6 points 14 hours ago* (last edited 14 hours ago) (1 children)

As someone said a long time ago (way before the LLM craze) "bad developers love new projects, they can write terrible code, take praise and zero responsibility, then toss it to the maintenance (actual) team who has to deal with it".

(Context: in at least 2 companies I worked at, it was a common practice to have a "development team", usually with knowledge of latest tools and frameworks, but very little knowledge of processes or industry, and an "application team" that maintains the software long-term, and deals with the processes and users directly)

[–] MalReynolds@slrpnk.net 4 points 13 hours ago (1 children)

Been there, burned the TShirt...

[–] atrielienz@lemmy.world 2 points 2 hours ago

Because it was infected or as a protest?

[–] spiffmeister@aussie.zone 2 points 16 hours ago

since no one else will read the dreaded wAlL Of tEXt.

It's okay I can just have an AI summarise it for me.