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#vibecode

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A lot of people #VibeCode—writing code without structure or strategy—which can lead to problems. Personally, I treat AI as a collaborative teammate. When you’re at a small company, AI isn’t just a tool—it’s a teammate you manage. That’s a big difference from letting it run wild

Hi,

I saw this on a #b3d #addon I bought recently:

def cursor_to_world_02BA0_34CA6():
py.ops.view3d.snap_cursor_to_center()

All the methods on the code are named with hex numbers at the end.

Does anyone knows where this comes from? Is from a code editor?

It could be the code is #vibecode generated by an ai (I hope not)

This is where llm-assisted coding is at now (#llm #llms #chatgpt #vibecode)

I was having a bug yesterday where I suspected another program is messing with the files my agent is trying to edit. I barely know ebpf, tried a few tools to track reads/writes, then decided to roll my own. Most of this was built on entire autopilot while yapping on stream or at the coffee shop this morning.

I also generated a full in depth 8 module course to teach me what is actually going on.

It has a realtime web ui, database storage, all kinds of filters, a full documentation, it looks pretty, it worked pretty much right off the bat despite being totally non trivial in its design, and it took me basically 20-30 minutes of actual mental effort and yet I already learned a lot about kernel and ebpf. It’s not just a crud webapp.

The latest version of #ChatGpt #4o is very shit at coding.
I can see why #vibecode folk are frustrated and #luddites rejoice.

Eg;
Context "forgets" key spec points of the session, even ones that are critical to ops.

You have to jam everything with special checkpoint directives and hammer specs in, least they get forgotten.

It's terrible (and I have used earlier versions and #Claude)

In my opinion, what is happening because of the high compute burn, #OpenAi optimised the session manager. It burns less compute but is also more shit. The balance must be restored.