Пост запуска Jev
Диогу Алмейда представляет Jev, структурированную модель принятия решений TypeSafe. Посмотрите фильм о запуске и изучите оригинальный тред для подхода модели, примеров и отчетов автора о производительности.
A FIELD GUIDE TO JEV / VOL. 01
Лучшее о Jev: реальные проекты, практические руководства и идеи со всего интернета.
Диогу Алмейда представляет Jev, структурированную модель принятия решений TypeSafe. Посмотрите фильм о запуске и изучите оригинальный тред для подхода модели, примеров и отчетов автора о производительности.
Официальное объявление запуска TypeSafe знакомит с лабораторией и направляет разработчиков к Jev. Включает фильм о запуске Диогу Алмейды и оригинальное введение.
TypeSafe объявляет о публичном доступе к Jev без списка ожидания. Официальный консоль — это отправная точка для тестирования типизированных решений в собственном приложении.
TypeSafe подчеркивает подход Jev с типизированным выводом: приложения предоставляют состояние и вопросы, затем действуют на основе вероятностей, выборов или оценок. Связанное объявление также касается интеграции API Venice.
Start with the Launch Post. Explore four official signals.
1 198 материалов
AI-assisted summaries and translations. Check original sources for context and performance claims.
Jev selects legal moves in a game of chess, compared to reasoning models.
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LaneBreak — support ticket priority+routing via TypeSafe Jev.
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Jev processes natural language with structured outputs and confidence levels, but it is not a traditional large language model.

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Play ten browser games from the screen with a 0.8B open model that returns a probability over the game's legal moves in one forward pass, no text generated.
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Compare GPT generated language with JEV structured Noul decisions on the same input.
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A Chrome extension that organizes bookmarks using user-defined rules for categorization.
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English full-duplex voice control for macOS with OpenAI Realtime, native Accessibility, and Jev.
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Jev differs from LLMs by evaluating predefined decisions directly, enabling parallel processing of independent questions.
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A local computer-use fast path for Codex and Waku, designed for developers.
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Скилл для агентов Letta: суждения по критериям через TypeSafe System One (Jev).
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A code search tool for agents to find behavior patterns instead of text strings.
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Shady Town: social-deduction party game for the living room TV, moderated by TypeSafe Jev.
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Ruby client for typesafe.ai.
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An experiment to enable Jev to perform dogfighting, with ongoing improvements.
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Pull request adding Jev to station-suggestion reranking in the TrainLCD transit app.
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Small game that tests how Jev handles unknown input.
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A tool using Jev to make copy-paste interactions smarter by deciding content based on context.
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Jev analyzes outreach messages to identify signals that lead to booked demos, improving campaign performance.
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A developer project that selects applicable rules for Claude, ensuring only relevant information is shown.
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A developer project that uses Jev as a sensor to control access to agent tools, enhancing security and functionality.
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Not every coding task needs your best model. Experimental Jev-powered model routing for Claude Code — V3 prototype runs today, V4 routes at the task boundary.
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Jev analyzes 724 live ads from 37 brands in 40 seconds, breaking down their elements and formats.
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Eval of Jev turning free-text player intent into typed server actions: 96% agreement, 317 ms median.
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A fire evacuation simulation where each person makes Jev-style decisions.
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Talk to your Mac. Local whisper.cpp + one Jev (TypeSafe) call per command + macOS automation.
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A demo showing how to make open source models behave like Jev using inference engineering and scoring endpoints for decision-making.
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Agent skill: design judgment-assisted systems with TypeSafe Jev (System One). Maps Choice/Score/Noul onto decision theory, reranking, and routing. Composition algebra, question design, validation gates. MIT.
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Jev successfully played and won a match in the game Clash Royale.
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Ruby client for decision models such as Typesafe Jev.
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A project using Jev for skill routing in an agent system, based on community development.
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Ephraim Duncan's demo where Jev decides which model should serve a request.
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An agent that plays Tetris with rapid decision-making capabilities. Shows potential for real-time game automation.
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Does a TypeSafe Jev rerank beat embedding search? Graded relevance eval (9,831 pairs, 164 zh/en queries) over the Agent Skills Hub catalog, with the judge-circularity bias measured.
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Jev plays Puyo Puyo. A community post describing an experiment where Jev makes decisions in a game by evaluating board states and strategies.
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A pi extension that exposes TypeSafe (Jev, System One) judgments as five pi tools, so a model can make narrow semantic judgments while your code and your users keep control of thresholds, weights, and actions.
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Official TypeSafe reference: JavaScript SDK.
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Jev controls a city's traffic in a simulation project.
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Reduces context usage by 30-55% through Jev-based compaction for OMP agents.
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Proposal for custom Jev-style models to optimize agent workflows. Could reduce computational costs in decision-making processes.
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Rust client for the TypeSafe System One API (Jev).
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A tool enhancing zsh autosuggestions with Jev-based ranking instead of prefix matching.
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Jev enables Grok Bot to control real Chrome for faster, automated tasks instead of slow look-and-click methods.
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Jev (TypeSafe System One) × ASReview SYNERGY abstract screening demo — Choice/Noul vs gold labels.
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Browser extension that reads the YouTube caption track and paints a per-segment sponsor probability on the seek bar before the intro ends, with no crowd database.
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An agent system that makes one Jev decision per computational step.
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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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Official TypeSafe reference: Double-checking citations.
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Links records under a plain-English match rule using Jev Noul pair judgments, with local candidate blocking and match resolution.
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Experimental decision protocol whose Jev adapter evaluates framed evidence with typed choices, while application code validates permissions and commits simulated demo actions.
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Minimal grammY Telegram anti-spam bot powered by TypeSafe Jev.
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A Stop hook that stops your coding agent from stopping too early. Plain-language rules, judged by jev.
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Tutorial covers API setup and building prototypes with Jev and LLMs.

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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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A community post describing a system that matches one candidate to 400 companies with a confidence score in 12 seconds.
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A community post exploring Jev's behavior in a game of Catan, where multiple Jevs struggle with negotiation.
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TypeScript experiments, evaluations, and latency benchmarks for TypeSafe's Jev model.
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A Chrome extension using Jev to detect and skip YouTube sponsor segments in real-time.
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Screen a folder of CVs with the TypeSafe Jev decision model: typed judgments, an editable policy, free re-scoring.
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Curated catalog of System One / Decision Models — contributions for modelsystem.one.
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A chatbot from typed Jev decisions: hierarchical speculative decoding over System One probabilities.
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Fast, cheap judgment for AI coding agents: semantic search, focused reads and list picking in ~2s. CLI + MCP server on TypeSafe Jev. Benchmarked on SWE-bench.
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A community guide outlining 10 steps to implement Jev for faster decision-making in AI agent systems.
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A research project on GitHub conducting nine experiments and 28 predictions with fixed parameters, focusing on Jev's performance metrics.
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Comment-moderation playground: paste a comment, Jev decides what to do with it.
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Probability-aware evaluation for typed decision models: calibration, selective risk, latency, and reproducible benchmarks.
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Hybrid browser harness: an LLM turns goals into verifiable subgoals, Jev chooses each action and DOM field, Playwright acts.
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CV diagnostics and job alignment with TypeSafe Jev, React and FastAPI.
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A community post describing an autonomous driving system using Jev to process real-time environmental data.
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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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Shift every LLM call to the cheapest model that can handle it. Routing decided by TypeSafe Jev in ~180 ms. No training data. Policy in plain YAML. TypeScript and Python.
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MCP server that puts TypeSafe Jev on the coding loop in Cursor, Codex, and any MCP client.
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Near-real-time scoring of TikTok and Instagram hooks against about 100 personas.
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