Jev, explained like you’re five
WTF is Jev by @typesafeai? Here’s the tl;dr ELI5: Think AI multiple choice, not AI essay writing. It doesn’t chat. It makes decisions your software can act on: “Spam or not?” “Which tool should this agent use?” “Does this need a human?” The exciting part: roughly 200x faster and 400x cheaper than frontier LLMs in TypeSafe’s own workflow benchmarks, with responses in a fraction of a second. Why that’s powerful: imagine an app or agent making hundreds of little judgment calls without hundreds of expensive, slow conversations with an LLM. Keep the big model for the hard thinking and writing. Use Jev for the rapid-fire decisions in between. Excited to dig in.

Matt Van Horn
@mvanhorn
WTF is Jev by @typesafeai? Here’s the tl;dr ELI5: Think AI multiple choice, not AI essay writing. It doesn’t chat. It makes decisions your software can act on: “Spam or not?” “Which tool should this agent use?” “Does this need a human?” The exciting part: roughly 200x faster and 400x cheaper than frontier LLMs in TypeSafe’s own workflow benchmarks, with responses in a fraction of a second. Why that’s powerful: imagine an app or agent making hundreds of little judgment calls without hundreds of expensive, slow conversations with an LLM. Keep the big model for the hard thinking and writing. Use Jev for the rapid-fire decisions in between. Excited to dig in.
Evaluate input state and return typed decision for Jev, explained like you’re five.
Jev sits between the incoming context and the next system action. Rather than generating lengthy, slow natural language that requires brittle regex parsing, Jev returns non-autoregressive, calibrated probabilities that downstream code can immediately execute.