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OpenAI is well positioned to fast-follow Jev
The Hacker News thread on John Berryman's argument that OpenAI could copy the decision-model shape and fold it into existing agents.
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- JohnBerryman
- Last verified
- Sep 2026
Works forJev for Routing
Used inJev for Software & DevTools
Highlights
- 327 points and 229 comments on 22 September 2026.
- Commenters ask whether a built-in classifier would still spend tokens the way reasoning does.
- One reply treats Jev as easy to offer as another tool, or as a separate API, for batch tasks.
Watch out
The strategy claims are the essay and the comments. Point totals move. The essay is a separate entry.
Questions about this entry
Short answers drawn from the linked project or page.
It is disputed, and that dispute is the substance of the thread. One commenter calls Jev a trivial modification to an existing pipeline; others reply the real work was the post-training recipe, an inference stack that stays up, schemas, docs and go-to-market.
A commenter in the thread makes that argument, saying a zero-shot decision model is fundamentally different from a fixed-task classifier such as a safeguard model, since the latter cannot be retargeted per question. No cost or token comparison is offered.
One concrete engineering detail appears in the thread: reading a decision in a single pass breaks normal KV caching, so parallelisation has to be solved before it is viable as an API. Everything else in the discussion is argument rather than measurement.
No, and it surfaces a disagreement about measurement instead. One commenter points at a benchmark view where the model is not near the top and loses to open-weight clones; another points at a different benchmark view that has it at the top.
DeepMind's Variational Bayesian Last Layers, which never gained much traction but is described as a useful tool that people experienced in SVI and transformer pretraining independently rediscover.
328 points and 233 comments, making it one of the bigger Jev threads; the linked piece is on arcturus-labs.com and the argument runs through the comments rather than the article.
That an LLM is a zero-shot classifier with a large number of classes, and that fine-tuning its final layer for a task is possible but not publishable; they agreed ease of use is the newer part of Jev.
Reactions & coverage
Posts, threads, and videos about this entry from around the web.
Hacker News: Does OpenAI fast-follow Jev?
JohnBerryman302 points · 213 commentsOpenAI is well positioned to fast-follow JevRead the thread on Hacker NewsHacker News: Vercel on using Jev for defined decisions and GPT-6 Astra when the job also has to write or use tools.
flashbrew4 pointsTypeSafe AI Jev vs. GPT-6 AstraRead the thread on Hacker NewsYouTube: TJ Robertson on when a confidence score is enough and a full LLM is the wrong tool.
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