It isn’t about valuing the final product. If you really cared about it, the code would not have stopped you doing it by hand.

In my experience, people like programming with agents because they are lazy or bad programmers (or both).

> In my experience, people like programming with agents because they are lazy or bad programmers (or both).

When you get a little older, you might find that you too have more commitments and desires than you have time to complete.

(see, I can be mean too!)

> Agents objectively code insanely fast and produce more and better code than I could have if I devoted all of my time to it.

Then you aren't a very good programmer, because LLMs produce worse code than the typical programmer does. They can produce more, certainly. But generating bad code faster isn't actually useful.

> But generating bad code faster isn't actually useful.

Tell that to every successful business.

Code that exists is very frequently better than code that doesn't.

Well - more importantly - with the absurd speed you can iterate insanely fast. It's amazing what you can do when you throw 1000 average programmers at a problem.

People who don't use coding agents really should stop making fools of themselves. It's painful to watch.

Hello??? You there? You can't say "you aren't a very good programmer" and just walk away.

Well, you can. But it's cowardly.

> because LLMs produce worse code than the typical

I'm not so sure that's true anymore.

But regardless - no one uses just one coding agent. It's a series of agents - a group to plan the work - coders to implement it - and then agents to review the work. Overall it comes out better than human code.

Here - let's test it - give me your GitHub and we can compare your code to theirs.

> Then you aren't a very good programmer

Ohh.... my sweet summer child...

"If you really cared about it, the code would not have stopped you doing it by hand." This is insane to me. So you have unlimited time?

You seem to be of the belief that all AI output is slop.

May I humbly suggest you might be mistaken?

It's trained on massive amounts of public code, so its output is (at best) average-- like the code it was trained on. My issue isn't really the output itself, but the mindset that accepts average output as good enough. People who make that choice will keep producing below-average software, and that's what the rest of us will have to live with.

You're being silly. With an appropriate dev pipeline it comes out quite nice. A team of agents to design and plan the implementation - a team of coders - and a team of reviewers after the fact.

Here, let's test it. Give me some of your code (GitHub is fine) and we can compare.