Building a Codebase Classifier with Jev
A developer shares building a codebase classifier with Jev, suggesting it may solve overengineered code from agents, and asks what to test next.
Jev vs GPT-5.6 Luna as Operator in Pipecat Speech Pipeline
Jon Taylor recorded a detailed walkthrough comparing Jev and GPT-5.6 Luna as the operator element in a Pipecat speech interface pipeline: Jev achieves 92.6% command accuracy and 296 ms median latency, versus GPT-5.6 Luna's 81.3% and 1,008 ms.
.@jonptaylor recorded a detailed walkthough of Jev vs GPT-5.6 Luna as the "operator" element of a Pipecat speech interface pipeline. GPT-5.6 Luna: - 81.3% command accuracy - 1,008 ms median latency Jev - 92.6% command accuracy - 296 ms median latency A few notes
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