Wprowadzenie do Jev
Diogo Almeida przedstawia Jev, model strukturalnych decyzji TypeSafe. Obejrzyj film prezentacyjny i eksploruj oryginalny wątek, aby poznać podejście modelu, przykłady i zgłoszone wyniki.
A FIELD GUIDE TO JEV / VOL. 01
To, co najlepsze w Jev: prawdziwe projekty, praktyczne poradniki i pomysły z sieci.
Diogo Almeida przedstawia Jev, model strukturalnych decyzji TypeSafe. Obejrzyj film prezentacyjny i eksploruj oryginalny wątek, aby poznać podejście modelu, przykłady i zgłoszone wyniki.
Oświadczenie o oficjalnym uruchomieniu TypeSafe przedstawia laboratorium i kieruje programistów do Jev. Zawiera film prezentacyjny Diogo Almeidy i oryginalne wstępne wprowadzenie.
TypeSafe ogłasza publiczny dostęp do Jev bez listy oczekiwania. Oficjalny konsolę jest punktem wyjścia do testowania typowanych decyzji w własnych aplikacjach.
TypeSafe wyróżnia podejście Jev do wyjściowych typów: aplikacje dostarczają stan i pytania, a następnie działają na prawdopodobieństwach, wyborach lub ocenach. Powiązane oświadczenie obejmuje integrację API Venice.
Start with the Launch Post. Explore four official signals.
1198 materiałów
AI-assisted summaries and translations. Check original sources for context and performance claims.
A community post describes using Jev to analyze news for stock investment opportunities.
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Hunch is a GitHub tool for code review that applies rules written in plain English to analyze and improve code quality.
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Jev enables users to create various applications using its architecture, as explained in a YouTube guide.

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Using Jev to create Clay workflows instantly, leveraging its capabilities for rapid development.
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A podcast segment discussing Jevons paradox and its connection to TypeSafe AI's funding.

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A community post details a Pac-Man game where every move is determined by Jev, offering strategic insights.
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A curated list of public projects, integrations, and discussions built on Jev — TypeSafe AI's System One model for typed decisions.
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A developer project demonstrates Jev's rapid response to browser tasks, with decisions made in approximately 100 milliseconds.
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A community post explores Jev's decision-making in ethical scenarios, comparing different approaches.
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A 4-minute video explaining what Jev is and its limitations.
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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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A community post suggesting Jev can be hired as a QA tester through @typesafeai.
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Game where Jev competes against LLMs in Pong.
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A tool that analyzes Tetris board positions and selects optimal placements in under half a second.
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Oficjalna umiejętność agenta dla Claude Code, Codex i kompatybilnych agentów: podstawy, wzorce i sposób strukturyzowania ocen.
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WXT browser extension: Jev-powered page clutter removal with reusable template rules.
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Fast Rust CLI for TypeSafe Jev: typed decisions, offline linting before you pay.
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Explains Jev's advantages over older LLMs in decision-making and building.
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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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A resource explaining Jev Engineering methodology for AI agent development.
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Minimal grammY Telegram anti-spam bot powered by TypeSafe Jev.
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A project using Jev to enable fast voice-controlled interactions with a Mac computer.
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Jevals is a local testing environment for evaluating Jev requests and improving results through primitive operations.
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A Brave extension that scores posts for logical fallacies in real time, highlighting well-reasoned content with a green flag.
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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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Jev from @typesafeai plays Balatro, making quick decisions on cards and gameplay within 200-500ms.
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An agent project that enforces policies by judging Claude Code tool calls.
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A tool using Jev to make copy-paste interactions smarter by deciding content based on context.
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Context-pruning proxy for Claude Code and Codex: Jev judges which history is still needed, measured not claimed. POC here now, heading soon into https://github.com/compozy/compozy.
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Fast structured Android control loops with TypeSafe Jev and Mobile MCP.
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A method for expressing emotions through sound-based communication.
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A Go client for the TypeSafe API, aimed at developer tools and applications.
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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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A collection of research papers and open reproductions supporting System One models.
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A GitHub project that uses Jev to triage and route posts from the live Bluesky firehose with human oversight.
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Demonstration of Jev's capability for rapid variable generation in development workflows.
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Analyzes 100,000 X posts in 20.4 seconds using 14 yes/no questions per post for viral potential assessment.
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Jev's effectiveness in performing intent-based search within Gmail.
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A Codex plugin that uses Jev to streamline and reduce excessive tool outputs.
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A community project embedding three Jev-powered bots into a first-person shooter game.
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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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A project comparing Jev's performance against chat models in analyzing Fed press conferences.
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Retriever AI evaluates Jev's performance on real browser tasks, identifying strengths and areas for improvement in integration with larger models.

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Evidence-backed index of real-world Jev (TypeSafe AI System One) use cases: repos, patterns, benchmarks, and measured results.
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A Chrome extension using Jev to detect and skip YouTube sponsor segments in real-time.
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Integration of Jev into a game for fast and cost-effective performance.
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A game where Jev makes decisions to keep a city on a whale alive, integrated with GPT-6 Astra and H3 Max.
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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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A tool that scores video ad shots in 1.5 seconds using Maxfusion and Jev, processing over 450 ads in under three minutes.
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Jev is used to predict human moves in a rock-paper-scissors game.
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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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A practical guide explaining the use of TypeSafe’s System One model, providing technical insights for developers.
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Classifies tax documents using an LLM pipeline for efficient processing.
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Jev classifies 500 emails quickly and inexpensively, demonstrating its efficiency in processing tasks.
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A real-time computer assistant using Jev and local Whisper to process voice input, classify actions, and interact with the screen through a Swift app for accessibility.
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Jido agents use Jev to make moves in Tic Tac Toe, demonstrating Jev's application in game-playing agents.
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A guide on using Jev to route between models and block risky tool calls.
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A resource explaining Jev's functions, costs, and evaluation metrics as TypeSafe's System One model.
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A skill for writing and improving programs that call Jev, TypeSafe's System One model.
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Camera-only autonomous drone in MuJoCo with a small judgment model (TypeSafe Jev) in the loop at 2.5Hz.
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Integrates Jev into apps for smart autofill features improving user experience.
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A macOS tool for identifying safe ports to stop, developed as a GitHub project.
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A game integrating Jev to display real-time decision probabilities during gameplay.
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An AI-driven hedge fund utilizing Jev for fast and cost-effective trading decisions.
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Directory of Jev-based projects including repositories, SDKs, and benchmarks.
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A developer project for the games shelf, where Jev improvises piano with proper questions.
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A Jev powered LinkedIn recruiting agent. Watch it browse relevant profiles, save links, and review evidence against your hiring brief.
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Tool for systematic reviewers to extract information from research articles efficiently.
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TypeSafe ogłasza publiczny dostęp do Jev bez listy oczekiwania. Oficjalny konsolę jest punktem wyjścia do testowania typowanych decyzji w własnych aplikacjach.
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An always-on assistant built with Jev that operates without a wake word, using probability to distinguish user intent.
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Testing Jev as a search reranker shows limited improvement over vector retrieval, with mixed results depending on evaluation methods.
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A YouTube guide discussing Jev's functionality, pricing, and performance comparisons with Astra, including benchmarking and parallel decision analysis.

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