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I'm not OK with it, but I have no choice besides maybe quitting my job. I've also tried to understand the code that AI writes, but it's often insane and untang

by altern8 17d ago

I'm not OK with it, but I have no choice besides maybe quitting my job. I've also tried to understand the code that AI writes, but it's often insane and untangling it would slow me down so much that it would nullify the gains in speed that AI brings. To me, either companies realize they're spending a lot more money to ship crappier code and AI becomes a niche, or we'll just stop looking at code. I don't think there's any other option because I don't see AI getting better at it. It seems to actually be getting worse and more annoying to use.

mortalapeman 17d ago
My company recently had to cut back our usage to effectively nothing and I get to code by hand again. I'm going to appreciate it while I can. The AI just wasn't providing enough value for us
bitwizeshift 17d ago
There is an in between here that developers seem to keep forgetting: Design the software architecture yourself — do some whiteboarding, figure out your abstractions and your UML, then write that in your prompt for the LLM to implement through a plan. Velocity stays high. Cognitive overhead remains low. You know enough of your architecture from the “unit” level to see how the pieces work meaning you can still work fast and understand it without hating the quality it produces. This has worked wonders for my company; I’ve managed to personally write tools that are barely distinguishable from what I’d write by hand, and I’m confident enough to discuss its architecture from top to bottom. If the LLM ever produces a unit with a poor implementation, I just rewrite that unit. Basically: do the “engineering” part of software engineering instead of throwing LLMs at the wall until code sticks. It doesn’t take much time to come up with a good design, compared to repeatedly iterating on a bad design and maintaining it for years to come. LLMs suck at design, and that’s why they lead to this bad code. But if a human spends an hour to build nice SOLID abstractions, and tell the LLM each responsibility — they are pretty good at using and wiring these parts together.
deterministic 16d ago
> I've also tried to understand the code that AI writes, but it's often insane and untangling it would slow me down I hear that a lot, but it is very different from my experience using Claude Code every day. The code it generates is pretty much what I would have written myself. My colleagues have always said my code is easy to read and understand, so hopefully it is not just because my code is insane too :) So I wonder: how are you using LLMs?

by altern8 17d ago

mortalapeman 17d ago

My company recently had to cut back our usage to effectively nothing and I get to code by hand again. I'm going to appreciate it while I can. The AI just wasn't providing enough value for us

bitwizeshift 17d ago

There is an in between here that developers seem to keep forgetting: Design the software architecture yourself — do some whiteboarding, figure out your abstractions and your UML, then write that in your prompt for the LLM to implement through a plan. Velocity stays high. Cognitive overhead remains low. You know enough of your architecture from the “unit” level to see how the pieces work meaning you can still work fast and understand it without hating the quality it produces. This has worked wonders for my company; I’ve managed to personally write tools that are barely distinguishable from what I’d write by hand, and I’m confident enough to discuss its architecture from top to bottom. If the LLM ever produces a unit with a poor implementation, I just rewrite that unit. Basically: do the “engineering” part of software engineering instead of throwing LLMs at the wall until code sticks. It doesn’t take much time to come up with a good design, compared to repeatedly iterating on a bad design and maintaining it for years to come. LLMs suck at design, and that’s why they lead to this bad code. But if a human spends an hour to build nice SOLID abstractions, and tell the LLM each responsibility — they are pretty good at using and wiring these parts together.

deterministic 16d ago

> I've also tried to understand the code that AI writes, but it's often insane and untangling it would slow me down I hear that a lot, but it is very different from my experience using Claude Code every day. The code it generates is pretty much what I would have written myself. My colleagues have always said my code is easy to read and understand, so hopefully it is not just because my code is insane too :) So I wonder: how are you using LLMs?