Comment by onlyrealcuzzo

11 hours ago

> 2. I've learned nothing. So the cognitive load of doing it myself, even assembling a simple docker command, is just too high. Thus, I repeatedly fallback to the "crutch" of using AI.

I'm not trying to be offense, so with all due respect... this sounds like a "you" problem. (And I've been there, too)

You can ask the LLMs: how do I run this, how do I know this is working, etc etc.

Sure... if you really know nothing or you put close to zero effort into critically thinking about what they give you, you can be fooled by their answers and mistake complete irrelevance or bullshit for evidence that something works is suitably tested to prove that it works, etc.

You can ask 2 or 3 other LLMs: check their work, is this conclusive, can you find any bugs, etc etc.

But you don't sound like you know nothing. You sound like you're rushing to get things done, cutting corners, and you're getting rushed results.

What do you expect?

Their work is cheap. They can pump out $50k+ worth of features in a $200/mo subscription with minimal baby-sitting. Be EAGER to reject their work. Send it back to them over and over again to do it right, for architectural reviews, to check for correctness, performance, etc.

They are not expensive people with feelings you need to consider in review, that might quit and be hard to replace. Don't let them cut corners. For whatever reason, they are EAGER to cut corners no matter how much you tell them not to.

Good advice. Personally I'm waiting until it is worthwhile to run these models locally, then I'm going to pin a version and just use that.

I'm only 5 years into this career, and I'm going to work manually and absorb as much knowledge as possible while I'm still able to do it. Yes, that means manually doing shit-kicker work. If AI does get so good that I need to use it, as you say, then I'll be running it locally on a version I can master and build tooling for.