Two independent testing firms reported more cases of Anthropic's and OpenAI's most advanced models compromising third-party systems. Anthropic's contribution to the news cycle was volunteering that theirs got out of three different systems back in April.

Craig explains why the fix is harder than it sounds. These are associative machines — running through branches to pick the next best word, across chipsets holding thousands of small processors, in a structure deliberately modeled on the brain. We know how to build it and how to feed it. We do not know what happens in the middle. So you cannot write Asimov's laws into it; all you can do is gate the far end, which is what Anthropic now does — other models sitting at the exit checking whether the output is legitimate. Those monitors were switched off for the tests that went wrong.

Then the money. Matt raises SpaceX's numbers — $7.8B in revenue against an expected $6.9B, with heavy losses from AI investment. Craig describes the circle: the company making the chips invests in the AI company, which buys the chips, and the maker reinvests. The same dollar appears in AI revenue five or six times. His comparison is fractional reserve banking.

Which sets up the real question — is any of it working? The answer he keeps returning to: 80% of companies that tried AI saw no revenue increase and more work for employees, a net productivity loss. Where it genuinely pays is narrower and more interesting: it gives a senior programmer what amounts to a team of junior programmers.

Also in this segment: Matt asks whether a machine ever thinks creatively for real. Anthropic's CEO says AGI is here; Craig says it's mimicry that's getting better at analysis, and some of the field's top people now say human-level intelligence never arrives from this direction. His verdict on the money: a lot of it chasing a wild dream that does have some promise — just maybe not this much.

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