[mewpmewp2]

Having worked at a company with thousands of microservices, I feel like most of it is just a bunch of boilerplate riddled with tons of ridiculous business logic, security and otherwise bugs. It seems like people were historically more concerned about Java inheritance and spreading everything around different files and directory hierarchies, while ignoring common sense business requirements completely. With each service being on separate older version, many being very difficult to start up locally, I don't see how LLMs could do worse than that, and that is a profitable, working business.

Funnily enough AI is the one discovering all those glaring issues now, and everyone is overwhelmed with getting it fixed. You could allow AI to attempt fixing it, but even though all of it was human written it is still hard to review, and even locally spin up or test because no one any more knows the true business requirements as people have rotated etc, so it's a nightmare.

The code on the first sight looks good, but what could be a simple config map, is spread out abstraction that is impossible to understand. Think just massive amounts of boilerplate to make a proxy call to another microservice etc.

[zingar]

The 1500 line react component that my unsupervised agentic coding side project produced says that it can get worse than we have now.

[mewpmewp2]

I swear I see far worse from humans for working businesses, and in much worse ways than just duplication of code. At least AI tends to be smarter about React intricacies even if it does create huge files. For my personal projects however I have straight token limits per file, whether it is backend or frontend so AI can't do that many lines of code. And I have specifically token limits so it would avoid hacking with formatting. And for React specifically I force it to put hooks in separate files and component files to be presentational only with max 1 hook usage.

[Izkata]

> At least AI tends to be smarter about React intricacies even if it does create huge files.

Oh no it's not. You just haven't seen where it goes when barely supervised by someone new to React. I've seen a level of spaghetti code with excessive useEffect and useMemo, reinventing two-way binding, I didn't even know was possible in React.

Spent months detangling weeks of AI-generated work earlier this year. Eventually got to the point we were actually fixing bugs by accident that previously neither they nor the tool could figure out.

[mewpmewp2]

I feel like I've seen people frequently doing the mistake of keeping way too many things in state that could and should be computed, but instead they would useEffect to read to dependencies change to update the state. And frequent useEffect infinite loops. I guess it depends heavily on how you would set up the initial prompts I suppose, but yeah if someone is new to React, maybe AI will do that you are right.

But also I see people constantly baking in more and more stuff into a single component and more and more useEffects and convoluted stuff, without no one ever daring or deciding to split up the file, because it doesn't seem like part of the ticket. And it never will.

At least to AI I can set guardrails and rules/logic to follow, to keep files small, but many people working on many random things one small ticket a time, where no one is there doing the refactor, things will also get crazy.

At least I feel I can use AI with guardrails to keep the codebase in a better shape than 100s of people working on the same monorepo.

[theshrike79]

24000 line central function in a mobile game that did 6 figure revenue monthly.

Made by an actual human, before OpenAI was a household name.

I'm 99% sure any SOTA LLM could've refactored that in a day to something actually manageable. It could've done it on a weekend.

[fn-mote]

The difference is, if you tell the LLM that the component is too big and ask it to use some strategies to break it up, it will.

Humans? Also maybe, but I always suspect the humans actually don’t know a better way. The LLM does, just that pathway wasn’t activated.

[palmotea]

> Funnily enough AI is the one discovering all those glaring issues now, and everyone is overwhelmed with getting it fixed. You could allow AI to attempt fixing it, but even though all of it was human written it is still hard to review, and even locally spin up or test because no one any more knows the true business requirements as people have rotated etc, so it's a nightmare.

No. It's just screwed up priorities. Those "glaring issues" were always a problem for the people maintaining those apps. It's just that no one gave a shit about those people or cared to make their job easier or them more successful (see the challenge or prioritizing tech debt remediation), but those same people are some reason willing to whatever it takes to make the machines successful.

There's a lot of contempt for humanity in the business world. It probably stems for a contempt for labor and a fetishization of capital.