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Zig Creator Calls Spade a Spade, Anthropic Blows Smoke
(raymyers.org)
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this post was submitted on 13 Jul 2026
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Programming
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We are at an infection point with software. Similar to AWS was about fifteen-twenty years ago, or git. If you ignore it, you're behind the curve. Now's the time to experiment, figure out the good and bad. Not all orgs are going face first. Some of us are learning along with it.
Where it shines for me? Really small changes in a complex system. I can't store all the context all the time. Business requirements, security ones, aesthetic ones. Where it shines is if you suss out small changes thoroughly, it's a great text generating engine.
All of that said, the side effects of data centers and pump and dump stocks, are absolutely horrid. Hopefully on the other side of it we come to something more sane.
From my experience, AI-assisted development is not good at complex systems. If a feature or fix requires a lot of changes in different places, or if the business logic is complex and difficult to understand, then the AI usually, in my experience at least, doesn't do a good job with it. And because the system is large/complex, you have to have a correct understanding yourself of how the system works if you want to know if the AI changes will actually work as expected, and what edge cases it addresses and omits.
Absolutely. The great thing is you can ask ton of questions quickly to build your own knowledge quickly. It makes you faster not by doing the understanding for you. It can write tests to prove things pretty quickly. It can help find connections. Not fool proof ever, but it speeds up searches in your code base.
You can learn how to use AI coding tools in a week at most, and there's no telling if next week they'll be a new harness or loop or whatever that becomes the new trend, making everything you've learned so far obsolete. Nobody's being left behind. AWS also isn't hard to learn if you've done the similar infrastructure stuff yourself. And git isn't hard to learn if you've used other version control systems.
And that's the point. You don't have to consume everything all the time w/ AI/LLMs. But if you don't pay attn, 1) You'll likely make mistakes on things which didn't work out, like zero-shot prompting, or which models do better on which languages and 2) you'll have to play catch up.
On git? Did you know git would have won over HG, or Fossil? What about using git submodules, or bisect? You can do the research now that I wrote it out, but would you have known about them before hand? What about all the hook features?
And git can be hard, esp if people around you don't know it as well as you do, or people above you know it better than you do. Which again is a problem of people getting in way too late.