DEMO / RECORDING
Overview & Result
Matija Sosic (Founder of Wasp) broke down the core architectural value of Jev in a 45-second animated explainer. Traditional generative LLMs function as slow System Two engines emitting tokens sequentially; Jev acts as an ultra-fast System One reflex for agents, executing bounded routing, scoring, and classification with single-digit millisecond latency.
How Jev fits in the loop
- Distinguish unbounded text generation (System Two) from discrete choice selection (System One).
- Route agent environmental state directly to Jev to select actions without generative prompt overhead.
- Invoke heavy LLMs exclusively for open-ended synthesis and complex code writing.
How to reproduce
- Watch the 45-second explainer animation comparing generative LLM streaming with single-step Jev decisions.
- Inspect the architectural separation between token generation and bounded choice dispatch.
Why this build matters
Provides a clear, widely shared mental model explaining why bounded decision models eliminate agent latency and cost bottlenecks.
Limitations
- Conceptual video explainer without a standalone code package.