The Jev launch post
Diogo Almeida introduces Jev, TypeSafe’s structured decision model. Watch the launch film and explore the original thread for the model’s approach, examples and author-reported performance.
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Recent activityA FIELD GUIDE TO JEV / VOL. 01
The best of Jev. Real projects, practical guides and ideas from across the internet.
Diogo Almeida introduces Jev, TypeSafe’s structured decision model. Watch the launch film and explore the original thread for the model’s approach, examples and author-reported performance.
TypeSafe’s official launch announcement introduces the lab and points builders to Jev. It includes Diogo Almeida’s launch film and original introduction.
TypeSafe announces public access to Jev without a waiting list. The official console is the starting point for trying typed decisions in your own application.
TypeSafe highlights Jev’s typed-output approach: applications provide state and questions, then act on probabilities, choices or scores. The linked announcement also covers the Venice API integration.
Start with the Launch Post. Explore four official signals.
1,198 resources
AI-assisted summaries and translations. Check original sources for context and performance claims.
A system tested on 1,500 emails for classification effectiveness. Demonstrates potential for automated email management.
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A tool that improves end-to-end testing efficiency, completing tasks faster and cheaper than other models.
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Jev plays Subway Surfers at superhuman speed and handles 50 games simultaneously for under a cent.
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Using Jev to create Clay workflows instantly, leveraging its capabilities for rapid development.
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A Minecraft Java player controlled by TypeSafe AI, with live decisions, Canadian flag building, and a side-by-side dashboard.
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SIEGE: 200 people vs one agent. A typed action gate (TypeSafe System One) that learns from every breach, evaluated by W&B Weave, hardened by a defender loop. Built at CoreWeave Hacks: Agent Loops 2026.
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Jev AI plays Tetris at high speed, completing 357 pieces and 134 lines in 2 minutes. Demonstrates rapid decision-making capabilities.
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Chrome extension that asks Jev whether the page you are on is selling something or reporting first-hand experience, and marks Google results with verdicts it already has or snippet-only estimates, leaving low-confidence ones undecided.
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Local A-share technical analysis using Jev Choice and Noul questions to assess direction and volatility across two horizons, with evidence for Buy/Hold/Sell assessments and no order execution.
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A stronger one-pass scorer over a variable list of text options: hashed n-gram encoder, rival-aware attention, gated head, temperature scaling, benchmarked against jevlike.
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Fazt presenta las decisiones estructuradas de Jev con ejemplos de Snake y clasificación de solicitudes de soporte.

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Jev predicts upcoming shell commands by analyzing historical command data.
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Camera-only autonomous drone in MuJoCo with a small judgment model (TypeSafe Jev) in the loop at 2.5Hz.
JEVLAB ARTSource-linked curation
A spatial reference explorer for creators. Local Jev query choices, metadata highlights and source-linked collections.
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Using Jev to test how well it predicts financial markets(just like most llms as of september 2026, it doesnt do that good).
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Browser automation with Jev (TypeSafe) as decision model.
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Video comparison against a structured-output LLM baseline.
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22 Jev models, one ball: a 3D football match where every player is its own Jev (TypeSafe AI System One) decision. Watch, or take over the number 9.
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A user tested the new Jev model and shared insights about its significance for System One models.

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Hand the browser work off: an MCP server where a decision model drives the page for your agent, so a flow costs one tool call instead of a turn per click. Ref-based element tables, code-checked assertions, zero-model macro replay. Speaks CDP to your Chrome.
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MCP server for TypeSafe Jev: typed classify, score, check, match and screen for any agent, with confidence on every answer.
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Official TypeSafe reference: Legal.
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TrustGate — indie media T&S gate via TypeSafe Jev.
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Agentcard integrates Jev and Kernel to enable secure and efficient online shopping by agents, avoiding token costs and safety issues.
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An optimized inference engine to turn LLMs into Jev-like machines: optimized for quick, lightweight, and accurate decision-making, classification, and scoring.
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Starchild uses Jev for real-time prompt classification, reducing costs by 20x and increasing speed by 6x with average processing time of 140ms.
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Talk to your Mac. Local whisper.cpp + one Jev (TypeSafe) call per command + macOS automation.
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A system that quickly captures user interface flows on demand, enabled by Jev's fast processing capabilities.
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Open-source BYOK arena for Jev and other AI judges. Find failures, compare quality, cost, and latency.
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Official TypeSafe reference: State.
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A developer project using Jev to play Pokémon Red by typing each turn.
JEVLAB ARTSource-linked curation
A browser-native Doom agent experiment with structured spatial state, composable AI controls, live decision telemetry, and a Chocolate Doom WebAssembly runtime.
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Framework for running end-to-end tests with agents using Jev.
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TypeSafe Jev controls original StarCraft shareware through keyboard and mouse with recorded action probabilities.
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Async Python client for TypeSafe Jev. Typed questions in, probabilities and choices out, no prose to parse.
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A community experiment demonstrating Jev's interaction with a video game.
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A tool that uses Jev to convert pointing and speech into drawing actions on a canvas.
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Autonomous System-One Triage Engine & Benchmark powered by TypeSafe AI (Jev). 75ms inference, $0 output tokens, and RLCD epistemic safety gates.
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Open-source LLM router that uses TypeSafe's Jev to pick a model, on top of LiteLLM.
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A self-hosted drop-in replacement for TypeSafe's jev, powered by GliFormer.
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Official TypeSafe reference: Pre-parsed value extraction.
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Typed, confidence-aware agent skill routing with TypeSafe Jev.
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An MLP trained on Qwen 4B that functions similarly to Jev, offering a typesafe alternative.
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Typesafe's jev as a "fuzzy linter". give your code an ocular patdown.
JEVLAB ARTSource-linked curation
弈瞬:双 Jev 五子棋九宫格输入实验台,逐手查看模型决策,支持真实对局回放与实时对战。
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Jev as an LLM prompt guardrail inside the agentgateway proxy, with tracing and cost tracking.
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A community post suggesting Jev can be hired as a QA tester through @typesafeai.
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A Chrome extension that brings TypeSafe's Jev to X.com to analyze posts as you browse.
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A community post describes Jev attempting to play Resident Evil, testing its ability to handle 3D environments, objectives, and combat scenarios.
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Openvons (open-Jev): 有限選択肢に確率で答える判断層 — テキスト / 画像 / 日本語音声コマンド.
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A developer project offering 110 interactive use cases, games, and scenarios with editable prompts.
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Scans a codebase for covert, deceptive, or data-stealing behavior with Jev, then reports suspicious files and line ranges before the user runs it.
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Evidence-backed use cases, patterns, and guidance for building with Jev, TypeSafe AI's System One model. Every claim is labeled and sourced.
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3D chess powered by TypeSafe AI (Jev). AI vs AI by default, or play either side. Multiple difficulty levels.
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Match user goals to MCP catalog (two-stage) via TypeSafe Jev.
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Demonstration of Jev's capability for rapid variable generation in development workflows.
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SQL with natural-language predicates, powered by TypeSafe's Jev. Filter, rank, classify and score rows by meaning — batched, cached and cost-guarded.
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Ephraim Duncan's demo where Jev decides which model should serve a request.
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A developer project that selects applicable rules for Claude, ensuring only relevant information is shown.
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A prose linter that sniffs out AI writing tells. Zero dependencies, countable rules plus one judgment model.
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A tool for tracking decisions made by Jev, using Arize's instrumentation for detailed analysis.
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Voice command integration for the Autumn billing dashboard to streamline tasks.
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One direct Jev question per row against 12–14 Jev-scored dimensions with locally fitted weights on three classification tasks: 5,477 test rows, 25,174 Jev calls, $1.43. Decomposition wins on Japanese NLI (0.9076 vs 0.8373) but flags about 25× more hard benign rows as attacks (37.2% vs 1.5%).
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Brood War in WASM exposed as an MCP server, with Jev playing and still losing to a Zerg rush.
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Matched-precision comparison against a private fine-tuned classifier.
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A SillyTavern extension that evaluates replies before they are displayed, collected for the creative shelf.
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Job Risk Analyzer: CLI and REST API that uses Jev to score an occupation's exposure to AI-driven layoffs and its resilience.
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Using the new model JEV to play the game tetris.
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Vercel's open agent framework, which ships Jev as the default evaluation model in its experimental evaluate path.
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Pre-install security gate for npm lifecycle scripts using TypeSafe System One.
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Unofficial go sdk for typesafe ai.
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A game project involving a penalty shootout against Jev using Render Workflows and Postgres.
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