Astra for Coding: Why Are We Doing This Again?

I’m more and more convinced that all of AI engineering is Neijuan (内卷, meaning curl inwards). In China it describes a system that demands ever more effort and competition without improving output. The way in which it sometimes shows up in the West is the 996 nonsense. The English term for Neijuan is “Involution” from the book Agricultural Involution. Agricultural involution describes the intensification of farming that raises productivity per square meter while leaving productivity per head unchanged.

That’s how I feel about AI right now.

Which brings me to GPT 6 Astra. Astra is by all accounts an incredibly impressive model. There is really not much I can say against this. It’s amazing at computer use, understands images and complex topics, and it’s relentless in its pursuit of completion. It is absolutely impressive; these types of models are going to change the world in one form or another.

But at least for the moment I don’t know how to work with it for actual software engineering. Since that got quite a bit of attention on Twitter, I figured I might summarize my thoughts and just share what kind of code comes out of this thing.

My Slop Factory

“Armin, you should run a software factory!” I’ve heard that a few times now, so I figured I might celebrate the release of it by running a little software factory over the weekend. If everybody builds slop 3D games, then I should do something useful with it. My software factory was intentionally set up to let the model decide the how of the workflow entirely. It was free to manage its own context and could maintain its own records in an agent-notes folder. Then it spun off subagents to work on stuff. The goal? What if we had a Python with virtual threads and lexical scoping. And well, I burned a full reset’s worth of ChatGPT tokens on this which appears to be around 4 billion tokens. 35 hours later, the factory has delivered absolutely nothing of value and also not taught me anything about how to operate a better one.

But it produced a lot of code and input prompts, and so there is stuff I was able to study. And well, it shows behavior that I’m not used to with Sol and earlier OpenAI models . I have since encountered the same issues with regular programming with Astra, so it’s not a result of just the factory.

I think I’m suspecting something is going “wrong” in the training process. The model is greatly rewarded for succeeding on long-horizon tasks, but presumably there is very little punishing going on for “shitty code.” The apparent result is that Astra is amazing at producing 3D stuff and it can keep going for a very long time, coming up with its own work in the process. I had it do quite a bit of reverse engineering of my robot vacuum in ways that were quite impressive. So it’s definitely cool!

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