DEMO / RECORDING
Overview & Result
I gave Jev 3,282 of my X posts across 100M views and asked it to find what actually works for growth. 4,252,330 tokens $0.1282 for the full 8m 34s run! Each post got 8 questions about the topic, hook, tone, whether it teaches something, etc. How-to posts got 150 median likes vs the average median of 44. AI and coding was a 1.9x multiplier topic compared and SEO, despite recent posts, was right at base median 1.0x - surprisingly. The recommended topic + angle + voice formula was: AI coding + teach something + provocative
How Jev fits in the loop
- Extract observation from agent environment.
- Jev evaluates state and outputs typed choice or probability.
- Agent runtime carries out selected action.
How to reproduce
- Inspect author post and reproduction notes.
- Deploy agent loop and bind Jev decision endpoints.
- Run test inputs and observe latency and accuracy.
Why this build matters
Demonstrates practical production-level utility of Jev inside specialized agent workflows.
Limitations
- Community observed build; metrics are author-reported.
- Requires third-party dependencies as described in source.