855 projects, posts and guides about Jev, the System One model from TypeSafe AI. Each entry links to its source and shows the cost and speed its author reported.
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 cheaper (w/ output tokens free)
• Frontier composable intelligence optimized for decisions
AFAICT the shortest path to AI-based economic revolution
This is actually insane. This uses @typesafeai Jev model, as a plugin in Claude to review all the un-nesseasary tool calls, and it takes 1s to run!
Like, literally, 1 second to take my Claude session from nearly 1M to ... 86K tokens! 😮
Ask your claude to install it and be amazed
Use this prompt
```
Install, and configure :
https://github.com/tamaratran/fast-jev-compaction
```
A browser shooter where the opponent is Jev, first to five kills.
GEGarrett Emrick
42
Harry Tandy
@HarryTandy
TypeSafe founder Diogo Almeida:
"I want to automate the easy work before the hard work"
In this 2-hour interview, he explains how Jev uses choices, scores, and yes/no probabilities to route work inside agent loops
The guide below has 3 builds: a skill router, a codebase linter, and a retrieval reranker
Watch the interview, then copy the builds below
A Rust dataset sifter that keeps clean rows verbatim and drops the rest.
APAkash Priyadarshi
Ricky Grannis-Vu
@RickyGrannisVu
We rewrote the oldest primitive in programming. The if statement takes a sentence now, and Jev decides.
That nested boolean mess eleven rules deep, four AND/ORs, one comment nobody understands anymore? Replace all of it with "if this expense is allowed under the expense policy."
Judgment Mode, live now.
1/ Jev, a decision model by @typesafeai, sparked a burst of projects and discussion. We tested it using Ori Eval against popular LLMs on OpenRouter at judging.
Jev was >5x faster than the next fastest model, and even its slowest requests beat every other model's median.
Jev gives you a probability. You set two lines on it: above the top one it's a yes, below the bottom one it's a no, anything in the gap runs a third branch. It's just a normal branch, so you can handle uncertainty flexibly.
An Astra planner with Jev as the controller, playing Minecraft.
Rrmalde
588
Milind S
@milindlabs
Aaaaaand this is now open-source here:
A tiny AI pointer companion for your Mac driven by JEV or Gemini Live
- Bring your own keys
- Local OmniParser running on CoreML
- Jev drives the pointer
- Ctrl + K to type a task
Voice mode next if people want it!
https://github.com/milind-soni/tiptour-macos
A MuJoCo workbench for robot decisions, with Jev in the loop.
ABa bo
304
saturn
@SatOnchain
this paper is f*cking gold.
someone made handbook on "how jev can be used as classifiers for evals on scale"
anyone who solve this has chance to make millions.
Bookmark and read full handbook.
Reads a WeChat thread and scores emotion, intent and reply quality.
FFerryCorleone
308
st1ne
@SolSt1ne
Jev Founder, Diogo Almeida, just released an independent working note on building a Jev harness for coding agents
Not affiliated with the Jev team, just a builder mapping the loop
Section 1 - the split: why harnesses already make these calls, just badly, with regex parsing prose replies
Section 2 - five calls to move: files, model, safety, done, context, each one a typed Score, Choice or Noul instead of free text
Section 3 - what it saves: ~400x cheaper per decision vs a cached frontier model, 0.2s median per call vs seconds of LLM latency
$605 per 1,000 decisions on cold frontier calls down to $0.17 on Jev
Bookmark it and read it tonight
Then go rebuild your own agent loop
A chatbot built out of a model that only answers typed questions.
KPKyle Pena
97
The newest Jev builds, by the day they were added
Same directory, different order: the entries added most recently, rather than the curated order the home page opens in. The date on a card is the day it was added here, not the day its author published it — this directory is newer than most of the work in it.