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JevHarness

A Python framework where an authoring LLM writes a task-specific Jev harness, then optionally evolves it using reward reflection and GEPA over full trajectories.

LLM-authored task-specific Jev harnesses with optional full-trajectory reward reflection and GEPA evolution.

GitHub stars
251
Forks
14
Primary language
Python
Last pushed
Updated Sep 2026

Repo stats from the GitHub API, cached Sep 2026.Homepage

Category
Tools & Integrations
Format
—
Published by
Community
Author
TianyuCodings
Added
2026-09-25
Last verified
2026-09-25

Highlights

  • On a Pokemon task the selection eval win rate improved from 25% to 75% after five reflection rounds.
  • The selected harness averaged 568 ms per full decision and 269 ms per Jev request across 12 games.
  • Supports choice, score, and noul questions with multiple questions per request and concurrent graph nodes.
  • Optional GEPA integration selects parents from an instance frontier and records rejected proposals' ancestry.

Quickstart

bash
git clone https://github.com/TianyuCodings/JevHarness.git
cd JevHarness
node website/build.mjs
node website/preview.mjs --port 8768

Watch out

Needs an AI Gateway or TypeSafe key, Python 3.11 or newer, and a macOS native sandbox for functional Python nodes. The reported gain is on the selection eval set, not unseen games, and the repo ships no license.

Reactions & coverage

Posts, threads, and videos about this entry from around the web.

X: A usage router for Grok Bot

Jev + GrokBot is the best AI agent system I’ve built in my life It just made my setup CHEAPER and FASTER than what 95% of people are running... setup takes literally 7 minutes: prompt → GrokBot → Jev decision → GrokBot execution → result step 1 → open @typesafeai , Show more

codila
codila
@0xCodila

Jev is the "Internet" moment for the AI industry It tells your agents and LLMs what to do next, in milliseconds and at almost zero cost If you set it up correctly, you will have the AI engineer’s stack for 2028 In this article, I show you how x.com/i/article/2077…

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X: The compaction plugin, in Chinese

连 JEV 的联合创始人 @CompleteSkeptic 都亲自下场转发点赞:这是 JEV 正确的打开方式! 大家在 Claude Code 里写长代码,最恶心的就是上下文一满,系统就卡住 10 秒去写总结小作文 开发者 @tamarajtran 刚刚开源了这个插件:利用 JEV Show more

tamara
tamara
@tamarajtran

found the perfect use case for @typesafeai Jev: instant compaction in 2026, why is compaction still a summarization prompt? Jev can make it instant by scoring every tool call and dropping what’s irrelevant

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X: A prompt box that fills itself in

X: jev-browser in Cline

We built a plugin that gives Jev a browser in Cline, and have been blown away by the results. 1. Install it in our new desktop app: Customize > Marketplace > Plugins > search 'jev-browser' 2. Create a Vercel AI Gateway API key, then save it to Show more

Diogo Almeida
Diogo Almeida
TypeSafe AI
@CompleteSkeptic

After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x

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From the community

Posts from builders shipping with Jev right now.

Follow @typesafeai

A playable 16-judgment demo

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Tested TypeSafe’s Jev (no-text, probability-only model) as an AI agent safety monitor. Checking each action first worked well caught most attacks with almost no false blocks, and much faster than Gemini.

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Diogo Almeida
Diogo Almeida
TypeSafe AI
@CompleteSkeptic

After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x

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Cua's small System One models

A 706K-parameter form filler

cua open sourced a 706k param model that fills a whole form in one 50ms pass the llm agent doing the same form took 23 turns and 39.6 seconds the specialists are going to eat the generalists from the bottom

Cua
Cua
@trycua

1/ Introducing CUA-S1: a family of System One Models, small, specialized, and built for computer use. Today we're open-sourcing CUA-S1-FORMS, the first in the family: github.com/trycua/cua

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Navigating Neo4j with Jev

Jev 这个 waitlist 还是很给力的,昨天申请,今天就能用上。 给已经拿到 API、但还不知道怎么玩的人整理了一份 Awesome Jev,目前我能确认到的 Jev 项目基本都在这里: 1. jev-ultrafast Browser Use 做的高速浏览器 Agent。Jev Show more

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思维怪怪
思维怪怪
@0xLogicrw

前 OpenAI 研究员 Diogo Almeida 创办的 TypeSafe AI 推出新模型 Jev。它有点像一个能读懂自然语言的超级分类器,不生成文本,只返回选项、分数和概率,专门给软件做判断。 普通大模型需要一个 token 一个 token 往外生成,Jev 则可以并行给出多个结果。TypeSafe 还用新的 RLCD

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