CASE / dav3-genThu Sep 24

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DDav3 (ร,G)@urdav3
์์ด์ ํธ ์๋ํJEV
๐ค GIVE AI AGENTS A FASTER BRANCHING LAYER
๐ค GIVE AI AGENTS A FASTER BRANCHING LAYER
Autonomous agents continually face small but important choices:
Should this task be accepted?
Which tool should run next?
Does this action exceed the risk threshold?
Which workflow branch fits the current state?
Using a general-purpose generative model for every decision can introduce extra latency, cost, and output-parsing complexity.
Jev provides an alternative.
The first System One model from @typesafeai returns typed decisions with probability and confidence in approximately 70โ500ms.
Its parallel support for Choice, Score, and Noul questions makes it a natural fit for agent branching and policy-based execution.
Jev does not generate explanatory text. It provides structured signals that another system or agent can act upon immediately.
This creates a useful division of labor: generative models handle creation and deep reasoning, while Jev manages fast operational decisions.
Now live on the https://t.co/UQWvo7ebXA API.
https://t.co/a4n3d483VW
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