Jev plays Doom
A game loop that asks a model what to do roughly ten times a second.
by TypeSafe AI
- Rate
- ~10 queries/s
- Cost
- ~$7/hour
A directory of Jev projects
Jev is the first System One model from TypeSafe AI: it gives up writing text and returns typed decisions with calibrated probabilities, in well under a second. This is the running list of what that has been used for, with the cost and latency each author reported.
State
“Hi, I’ve been trying to connect my Stripe account for 3 days and it keeps failing. I’m losing sales. Please help ASAP.”
Confidence 0.60 · answered in milliseconds
Example from the TypeSafe quickstart.
Seven shapes of problem, from a 300 ms trading loop to a corpus of a thousand papers.
15 projects · updated Sep 18, 2026
A game loop that asks a model what to do roughly ten times a second.
by TypeSafe AI
Pick one link out of thousands, then do it again until you arrive.
by TypeSafe AI
Browser Use’s agent, with the next-action decision moved to Jev.
by Browser Use
A booking flow driven end to end in about seven seconds.
by Gregor Zunic
Browser tasks at about a tenth of a cent each.
by Kyle Jeong
Computer use on macOS, one typed decision per step.
by Andrew Levin
Buy or sell, decided inside a 300 ms block.
by Jarrod Watts
A tactical judgment loop flying on hardware.
by Roman Slack
A full inbox sorted in one pass.
by Ryan Vogel
Eleven experiments, 1,709 judgments, under a cent in total.
by Mike Taylor
A thousand papers sorted by topic, then published as a site.
by 1kpapers
Legal moves as a Choice, scored against reasoning models.
by Maxim Saplin
A back catalogue scored to find what actually travels.
by Ian Nuttall
61 questions about a draft, answered in about a second.
by Rob Hallam
Every hook, format, offer and call to action, in forty seconds.
by Matthew Berman
The posts these entries come from, quoted as published.
Jarrod Watts
@jarrodwatts
I built a trading bot with Jev! Jev decides if it should “buy” or “sell”, given the price feed of an asset pair, and executes real trades. It uses Monad to place the orders on Kuru’s on-chain order book in every 300ms block.
Ian Nuttall
@iannuttall
I gave Jev 3,282 of my X posts across 100M views and asked it to find what actually works for growth. 4,252,330 tokens $0.1282 for the full 8m 34s run! Each post got 8 questions about the topic, hook, tone, whether it teaches something, etc.
Rob Hallam
@robj3d3
Jev + SuperX = virality solved ✅ Every post gets 61 questions in ~1s for $0.0004 🤯 > fitted on 9,481 real posts from 207 creators > picks the viral post 2 in 3 times > never rewards reply bait So: write, score, rewrite, stop when it peaks. Free, no signup. try it below ↓
Matthew Berman
@TheMattBerman
jev is INSANE. in 40 seconds it broke down 724 live ads from 37 brands. every hook. every format. offer. cta. awareness stage. landing page mismatch. used 9 cents of tokens. (will be avail in @stealads + mcp)
Worth reading before you wire Jev into anything.
The launch post: what the model class is, the evals, and the caveats TypeSafe put on them.
typesafe.ai
The three question types — Choice, Score and Noul — in one support-ticket example.
docs.typesafe.ai
Accuracy, cost and time per case across four automation workflows, model by model.
evals.typesafe.ai
Worked examples for support routing, refund decisions and risk escalation.
developers.cloudflare.com
LangChain on model routing and gating dangerous tool calls behind a typed decision.
langchain.com
Flavio Copes on triage, RAG filtering, citation checks and confidence gates.
flaviocopes.com
Community list of projects, wrappers and examples.
github.com
Where the sceptical reading of the benchmarks lives.
news.ycombinator.com
Send me a DM on X with a link. If it shows something the list does not cover yet, it goes up with your name on it.