Understand Jev (the only video you need)

The page documents no stop condition, iteration cap, spend limit or backoff. The copy says an autonomous triage loop is built but says nothing about how it ends, and per-call costs still accumulate across a long queue, so that bound is the first thing you would have to add yourself. Ask for it before copying the pattern.

The copy says the video compares Jev with classical ML but records no result: no accuracy, latency or cost figure for either side. Classical models are also the cheaper and faster baseline wherever labels are clean, so the interesting question is how the harness handled the messy items, and the page does not describe that.

Noul sits at 4:14, Choice at 6:48, Score at 8:43 and parallel evaluation at 10:14, and the source lives in the zazencodes-season-3 repository under a Python demo folder. The page does not document a pinned model version, dependency pins, or whether the demo uses the Python SDK or raw HTTP, so check the code before trusting the timings.

Parallel evaluation gets its own chapter, but the page records no latency comparison between a one-question call and a many-question call. The only published batched-versus-single measurement is TypeSafe's own cookbook, which is vendor-run and pins an older version. Reproduce it at your own question count before relying on it.

ZazenCodes published it, with source in the zazencodes-season-3 repository under a Python demo folder.

Noul at 4:14, Choice at 6:48, Score at 8:43, and parallel evaluation at 10:14, per the entry's recording of the description.

Its community and newsletter, which the entry flags as an editorial caveat on the walkthrough.