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I've been thinking a bit about under what conditions humans need to understand the systems they're building. Chatted with GPT-6.1 Sol high, and I thought we reached a good argument for the human-AI collaboration to get better results. www.geoffreylitt.com/2026/07/02/...

The crux of my question was: if AI models get better, why have humans in the loop at all? Under what conditions does it make sense? There was a co-exploration of various arguments and counter-arguments. over the course of 7 turns from each of us. Some broad strokes:

1. The modern world is full of human affordances, so having a human as a collaborator can make some context and requirements more accessible than is available to an AI alone.

3. Human-agent collaboration can throw off and reveal unspoken context that is important to getting a better outcome. Often times, you don't know what you don't know, and it's through exploration of the state-space and design space can you actually know.

Those were some highlights. Some of ideas are mine, some the ideas are the AI's. And when I pointed out that this thread would be an example of human-AI collaboration, if it felt like this was a good argument to the originally posed question.

Strangely, it said, it couldn't know the counterfactual of whether it could have come up with a better argument. But we can! I forked the convo, and rewound it back to the start, but then told GPT-6-astra max to argue with itself, consult w/ Opus 5.5 for another opinion, to see what it came up with.