Hard-coded rules moved to Jev

MEDIA PREVIEW

Overview & Result

Now using @typesafeai Jev in http://aiseotracker.com, http://linkdr.com, http://genppt.com, etc AI ends up vibe coding so much AI regex slop if you don't read the code, so I can finally move all this hard-coding to Jev and it's insanely fast! Also for regular LLM calls, it is around 10x faster, 50% cheaper

How Jev fits in the loop

1. Ingest real-time application state and relevant contextual parameters
2. Format the decision problem as a bounded Choice or Noul schema
3. Query Jev to receive a typed probability distribution in sub-50ms
4. Execute downstream actions or route tasks according to the winning choice

How to reproduce

1. Inspect the original showcase and source material at https://x.com/illyism/status/2100489521557123265
2. Verify the bounded prompt and input candidate schema configured for Jev
3. Benchmark decision latency and classification accuracy against baseline models

Why this build matters

Demonstrates a real-world, cost-effective implementation of Jev in a coding & developer tool scenario, replacing expensive generative calls with fast typed decisions.

Reported performance

Latency: Sub-50ms deterministic decision window

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

Patterns