Jev: System One models for Prod, not God — with Diogo Almeida, CEO, TypeSafe AI
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latent.space
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Breaking an AI workflow into small decisions can make failures easier to locate and test. In this interview, the CEO of TypeSafe AI recommends giving Jev structured application data and asking explicit, separate questions. The surrounding code then combines the answers into actions.
His example is refusal handling: define the particular conditions that should trigger a refusal, choose thresholds using real examples, and retain failures as test cases. A missed condition can then become a specific question and regression test. He also acknowledges that confidence estimates can be wrong and some tasks remain beyond the model, making this an engineering approach to evaluating automation.
Terms in this piece · Glossary
AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
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