Claude Sonnet will ship in Xcode

3 days ago I saw another Claude praising submission on HN, and finally I signed up for it, to compare it with copilot.

I asked 2 things.

1. Create a boilerplate Zephyr project skeleton, for Pi Pico with st7789 spi display drivers configured. It generated garbage devicetree which didn't even compile. When I pointed it out, it apologized and generated another one that didn't compile. It configured also non-existent drivers, and for some reason it enabled monkey test support (but not test support).

2. I asked it to create 7x10 monochromatic pixelmaps, as C integer arrays, for numeric characters, 0-9. I also gave an example. It generated them, but number eight looked like zero. (There was no cross in ether 0 nor 8, so it wasn't that. Both were just a ring)

What am I doing wrong? Or is this really the state of the art?

I guess many find comfort in being able to task an ai with assignments that it cannot complete. Most sr developers I work with take this approach. It's not really a good way of assessing the usefulness of a tool though.

He asked what he was doing wrong?

too big of tasks. break them down and then proceed from there. have it build out task lists in a TASKS.md. review those tasks. do you agree? no? work with it to refine. implement one by one. have it add the tests. refactor after awhile as {{model}} doesn't like to do utility functions a lot. right now, about +50k lines in to a project that's vibecoded. i sit back and direct and it plays.

Imagine the CS 100 class where they ask you to make a PB&J. saying for it to make it, there's a lot of steps, but determine known the steps. implement each step. progress.

This is the way.

I run interviews at my company. We allow/encourage AI.

The number one failure method is people throwing all of the requirements in upfront. They get one good pass then fail.