DEMO / RECORDING
Overview & result
Jev classified 1,315 X posts for about $0.086 in estimated model cost 😂 seeing everyone's Jev demos made me want to build something for my own content research. i'd collected a lot of posts, but figuring out what they had in common still meant opening them one by one and taking notes. so i built a dashboard around Jev. it labels each post across 8 dimensions, including topic, hook and writing style. now i can filter by topic and hook, compare engagement, and open the original posts to see the examples behind each pattern. my archive is a lot easier to learn from now.
How Jev fits in the loop
- Ingest real-time application state and relevant contextual parameters
- Format the decision problem as a bounded Choice or Noul schema
- Query Jev to receive a typed probability distribution over the options
- Execute downstream actions or route tasks according to the winning choice
How to reproduce
- Inspect the original showcase and source material at https://x.com/yuhasbeentaken/status/2101231502038339798
- Verify the bounded prompt and input candidate schema configured for Jev
- Benchmark decision latency and classification accuracy against baseline models
Why this build matters
Demonstrates a real-world, cost-effective implementation of Jev in a specialized agent workflow scenario, replacing expensive generative calls with fast typed decisions.
Limitations
- Task accuracy is bounded by the precision of the defined candidate choices
- Third-party external dependencies and network latency may affect total workflow duration