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Benchmarks, design decisions and how-tos: building AI agents in Synsema, and deploying them with a permission manifest, sealed secrets and an audit trail. Every post is also Markdown: add .md to its URL.
4 results for jev
Routing, tagging, eligibility and moderation are the highest-volume AI work most products do, and the cheapest to get wrong. A System One model answers them with a calibrated probability — and the economics are not close.
Half the work we hand to an LLM is not writing, it is deciding: route this, flag that, is this a refund request. A System One model answers those with a calibrated distribution, and a language that has both slots lets each model do the half it is good at.
A model that returns calibrated probabilities instead of text changes the operational questions, not just the code. What to wire, what to gate, what to audit, and what happens on the day the provider is down.
Jev is TypeSafe's System One model: it answers with typed, calibrated probabilities instead of text. In Synsema it is a language primitive — `require judge`, one block, one call, three verbs — with honest degradation when it is not there.