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Into the Impossible With Brian Keating · Ideas & Essays · October 2026
Brian Keating suggested we are simply lucky that AI models happen to think in English. Mollick replies that when agents talk to each other they drift toward a compressed machine language, and that keeping them in readable English is a deliberate trade-off between being able to watch them and making them efficient.
…we created a model of the world because human language models the world. Otherwise, how could we describe quantum physics unless we could describe it with like? Language. And I find that a somewhat satisfying answer, but it's still hard to answer the questions about consciousness or anything else.
…Hawaiian, which has 13 letters, and there's Cyrillic, which has 32 letters, and there's English. Not all languages are the same. There's binary code. And there may be languages that these entities can communicate in that we don't understand. And we are just lucky for now that they use English.
That's actually a big worry of AI Researcher: because if you've ever used, especially Claude Fable 5 has gotten better at this. If you've ever watched it talk to other AI agents, it talks in a language called Claudish, which is a variation of what's called Neuralese, which is, yes, of course, the AIs will come with a better language for talking to other AI agents. And a huge amount of effort in fighting inside the labs is that's more efficient, but we lose observability. We can't see what the AI is doing. So the AIs are trained to use English in this kind of case because it lets us have some observability into what they're thinking rather than non-English. It's not a lucky thing. It is an actual design decision that the labs are under pressure. The AI labs are under pressure to relax because the AIs will be much more efficient if they didn't use English.
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With the scaling laws that you mentioned, the only pushback I have is that they're just empirical. You know, they're phenomenological. They're not immutable laws of nature like F equals MA. So again, what observation would convince you that scaling is going to hit some fundamental limit? I mean…
It's so great because you always give two questions in each question. So I'll try and pull those apart. Question one is about scaling, saturated. Scaling's already saturated multiple times. There's multiple scaling laws. I talk about a couple of them in the book, but the truth is we keep hitting…