Harness: I made Jev control the player, has access to WASD, space, click, and mouse movements. Astra is the planner that sends instructions to Jev async. Learning: Each time the agent would fail, Astra would add skills as mjs files, that it can draw upon in different scenarios, Show more
CommunityCookbooks & Demos
Jev Plays
Four board games against Jev where the model picks the move and code keeps the rules: tic-tac-toe, Connect Four, Battleship, and Wordle.
- Category
- Cookbooks & Demos
- Format
- Playground
- Published by
- Community
- Author
- —
- Added
- 2026-09-25
- Last verified
- 2026-09-25
Highlights
- Connect Four offers at most seven legal columns plus three side judgments on the same state.
- Battleship turns the grid into text and asks one Choice over up to 64 open cells, drawn as a probability heat map.
- Wordle offers up to 60 candidates annotated with average words left, and never sees your guesses.
- Each turn shows milliseconds, confidence, and token counts, and illegal moves are withheld by the rules.
Watch out
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Reactions & coverage
Posts, threads, and videos about this entry from around the web.
X: Jev plus Astra beats the Ender Dragon for under a dollar
X: Jev plays Pokémon Showdown
1/8 Saw Jev from @typesafeai on my feed, so I made it play Pokemon Showdown. Codex built the harness. It was damn fast. Its choices were a mixed bag. Full match, video 1/2. This is a saved replay with decision data, latency and added reading pauses.
X: Jev plays Puyo Puyo with real-time board questions
Jev にぷよぷよをさせてみた。 - 実行エンジンは github.com/puyoai/puyoai 。ゲームはリアルタイムで進行 - 盤面とそれぞれのポジションにおいたあとの結果を与え、①今どのフェーズか ②フェーズごとに、戦略からどの結果がベストか の1+3つの質問をして、選択肢を選ぶ 画像は Random Show more
X: Jev plays Smash Bros. against itself
jev is insane 🤯 here is jev playing smash bros against itself he is controlling all 4 different characters. and literally deciding whats the best move to play against itself all within a fraction of a second i used over 22 million tokens to play this match and it only cost Show more
More like this
An autonomous Pac-Man recreation steered by Jev: before each junction the game sends the maze, actors, and legal directions as structured data, and Jev returns one direction with a probability per option.
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Two browser games against a live Jev opponent: a first-person quick-scope arena and a neon survival challenge, where Jev picks tactics and authored code handles movement and physics.
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A playable Tetris where you can drop pieces yourself or let the TypeSafe Choice primitive pick every move.
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From the community
Posts from builders shipping with Jev right now.
Computer use at 155× cheaper than Opus 5
i built computer use using @typesafeai ! it is 155x cheaper than opus 5, ~20x faster, and generalizes across OS's more on how it works in the vid & thread below:
@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
Foreman keeps coding agents on task
I just open sourced Foreman: a software factory foreman built with @typesafeai's Jev. Coding agents work the factory floor. Foreman watches them, continuously assessing progress, completeness, tests, drift, and verification, and intervenes when needed. GitHub: Show more
Unclutter: an ad and slop blocker that runs on Jev
introducing Unclutter: a smart ad + slop blocker with Jev 🤓 it auto cleans up pages from slop elements: ⬖ ads ⬖ cookie banners ⬖ upsells ⬖ bs dialogs BYOK. open source + free, download below 👇
An open-source BS meter for debates and investor calls
🚨 Open Source Jev BS meter you can use this to analyze any debate / investor call / interview / sales pitch / podcast video fact check live , for example this dario interview cost 60 Jev calls / 111K tokens / $0.0047 github.com/ChetasLua/jevm…
🚨 I gave the Trump vs Kamala debate a live BS meter using Jev every sentence, both candidates, 5 yes/no questions each 1,191 Jev calls / 1.18M tokens / 415 ms median total cost : $0.0497 same questions for both, clips picked by one fixed rule, not a fact-check
A Jev-shaped model on Cerebras and Qwen
Built an alternative version of @typesafeai but on @cerebras with Qwen 3.8 27b. Similar quality, similar performance, but vastly different cost. TypeSafe was way cheaper, and did beat Qwen on performance. Closest we can get using LLMs I think. Source: github.com/iammrduncan/ty…
@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
Jev benchmarked on two public safety corpora
1/ Benchmarked TypeSafe's Jev on two public safety corpora. It doesn't generate text, it returns calibrated probabilities you threshold in code. 96.5% on prompt injection, all 662 messages in deepset/prompt-injections. No tuning. 325ms p50.
@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