Played around with @typesafeai Jev today, mostly to
Replaced the LLM tool-calling step in a voice agent with Jev to decide actions on partial utterances before the user finishes.
The original post
Played around with @typesafeai Jev today, mostly to understand what it does for tool calling.
Instead of an LLM deciding what to do, I substituted that part with Jev.
My learning is that we will be able to make the agent act before the user finishes the sentence. So far, we've used different LLM combinations (non-thinking + thinking ) plus state machine setups to get the right experience for the end user.
TLDR is to understand more about how voice agents can run decisions on partials instead of waiting for the end of the turn, with lower costs.
Engagement when collected
Numbers are a snapshot taken from X when the case was added to the library (schema v1, collected 2026-09-19); they will not match today.
Where this case fits
Filed under agents & workflows, video, animation & media. In the pattern Jev is built for, the model answers a bounded question per step — and ordinary code acts on the answer, because the answer is already a value rather than a paragraph. Other posts in the same family are on the agents & workflows page.
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Last updated: 2026-09-22 · sources & corrections · every card links to its author's original post