Notes and teardowns
Notes on evaluating reinforcement learning, agentic, and optimisation systems, and claim-by-claim teardowns of systems whose technical claims are public and checkable.
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Is the explainability in the product, or in the slide deck?
"We have explainability" is not a yes-or-no answer. What matters is where the explanation lives: inside the mechanism that makes the decision, or in a layer added afterwards — because the two fail in different ways.
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The demo is impressive. What would make it investable?
A demo is one point. What matters is how far you can move from it, what moving costs, and whether the point sits inside the region the system was built for.
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Does this team know why their system works, or only that it does?
An explanation that has only been illustrated looks exactly like one that has been verified. The question is not whether a team's account is true, but how much of it they have tried to falsify.
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What I look for when a startup shows me its best result
A result that is excellent on the headline metric and strangely poor somewhere else is more informative than a mediocre headline. The odd secondary number is usually where the specification failure is hiding.