Technology

This is basically what I discovered as well. I have found that Ai writes code that is complex and "works" (at least most of the time) but it is heavily over engineered and often contains design choices that make expanding functionality effectively impossible without a full refactor.

When I tried having the Ai fix a test failure the Ai would either fix the code, fix the test, or change the test and the code breaking everything else in the chain.

I no longer use vibe coding because it is just faster/better for me to write the code.

But for tiny scripts it is very good.

Yeah, fully agree with all that.

I've got some godawful spaghetti code I don't understand fully, and it's pretty good at deciphering that and the bizarre labyrinth of code paths leading around it. But it's absolutely no guarantee of working code, and in any project larger than a simple crud app, you are going to still need programmers who know about things like memory and databases.

It often needs pointing at a solution you want, because as you pointed out, it's fond of dumb band-aids. Like yesterday when it was trying to hook into mouse wheel events and create separate threads, when all it needed was an event on the dataset I was using to load a sub-dataset.

Claude can do some medium complicated sites from scratch relatively quickly. The problem is I've seen so many of these at work, not just from non-engineers, but from peers too, that they're easy to spot. AI sites/apps are going to be the new geocities.

But when you want to move beyond the basic thing that impresses the c suites for some reason, it hits a pretty big wall in speed to output and needs a lot more hand holding.

I fear that the c suites don't really care about quality, just speed and saving money. So while I'm a much better developer than Claude (which is imo the best at the moment), I don't think that makes my job secure. I have to use the AI, and it's getting silly/scary religious here about it. We have to talk about how we used AI and how it's making things better. And to make things worse, I don't see a company that's not drinking the Flavor Aid.

It can be useful, and used right, you can do a lot of things faster. But the expectations from the top don't align with the reality of the product, and us developers are being blamed for the gap.

This is pretty spot on from my experience as well. Also, the gap in quality from the Opus models and say GPT is vast.

100% agree on ui code. Really awful output there regardless of model.

Man, I disagree with all of this. The frontier models are actually good, and basically everyone in my F500 company has been using it. The codebases i work on are super-legacy java, where it does great despite us having like 75 different patterns for each task, and a massive front-end web repo where it thrives because we've been extremely strict in typing and patterns leading up to this. It even does pretty well across repo boundaries, despite having significantly lower context for those situations.

I genuinely will never understand the people saying they suck. Are the worth the price? I have no idea, I've never used them for personal project. But they are at least as good as a dev with 3-5 years of experience, at this point. Our career is boned.