DEMO / RECORDING
Overview & Result
TypeSafe AI 创始人 Diogo Almeida在发布Jev之前的一次演讲，他应该在openai就意识到模型对齐人类偏好，在自动化任务上是不合理的优化方向。所以这次访谈把他的自动化理念做了很好的阐述。而Jev的对齐方向是RLCD。感兴趣的可以再深入我文章末尾的一篇解读（什么是 RLCD？Jev 背后的秘密）链
How Jev fits in the loop
- Ingest runtime state, user inputs, and environment context into a typed Jev evaluation contract.
- Jev evaluates candidate branches or safety gates in single-digit milliseconds with deterministic probability outputs.
- Downstream agent loop immediately routes execution to specialized tools or frontier models without stalling in generative loops.
How to reproduce
- Review original technical breakdown and architecture thread by @alacheng at https://x.com/alacheng/status/2102234174493200648.
- Configure Jev SDK client with strict schema constraints matching this domain's state transitions.
- Benchmark end-to-end latency and error rate before and after inserting Jev as the decision layer.
Why this build matters
Replaces expensive, high-latency frontier LLM calls with microsecond typed decisions, cutting inference costs by up to 90% while ensuring strict state machine determinism.
Limitations
- Decision schema requires explicit predefined candidates; not suitable for unbounded freeform prose generation.
- Third-party API rate limits and upstream network latency bound total end-to-end responsiveness.