โพสต์เปิดตัว Jev
Diogo Almeida แนะนำ Jev โมเดลการตัดสินใจที่มีโครงสร้างของ TypeSafe ดูภาพยนตร์เปิดตัวและสำรวจสายการสนทนาต้นฉบับเพื่อดูแนวทาง ตัวอย่าง และประสิทธิภาพที่ผู้เขียนรายงาน
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Recent activityA FIELD GUIDE TO JEV / VOL. 01
รวมโปรเจกต์จริง คู่มือใช้งาน และไอเดีย Jev จากทั่วอินเทอร์เน็ต
Diogo Almeida แนะนำ Jev โมเดลการตัดสินใจที่มีโครงสร้างของ TypeSafe ดูภาพยนตร์เปิดตัวและสำรวจสายการสนทนาต้นฉบับเพื่อดูแนวทาง ตัวอย่าง และประสิทธิภาพที่ผู้เขียนรายงาน
ประกาศเปิดตัวอย่างเป็นทางการของ TypeSafe แนะนำห้องทดลองและชี้ให้ผู้สร้างไปยัง Jev มีภาพยนตร์เปิดตัวของ Diogo Almeida และการแนะนำตัวอย่างแรก
TypeSafe ประกาศการเข้าถึงสาธารณะของ Jev โดยไม่มีรายชื่อรอ คอนโซลทางการคือจุดเริ่มต้นในการลองใช้การตัดสินใจแบบมีประเภทในแอปพลิเคชันของคุณเอง
TypeSafe ชี้ให้เห็นถึงแนวทางการออกผลแบบมีประเภทของ Jev: แอปพลิเคชันให้สถานะและคำถาม แล้วดำเนินการตามความน่าจะเป็น ตัวเลือก หรือคะแนน ประกาศที่เชื่อมโยงยังครอบคลุมการผสานรวม API Venice
Start with the Launch Post. Explore four official signals.
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AI-assisted summaries and translations. Check original sources for context and performance claims.
เอเจนต์ที่เร็วมากสำหรับการใช้งานเบราว์เซอร์: Jev เลือกการดำเนินการและองค์ประกอบ DOM ในหนึ่งการร้องขอ; โมเดลขนาดเล็กเขียนข้อความเฉพาะเมื่อจำเป็นต้องพิมพ์
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ปลั๊กอิน Claude ที่แทนการสรุปการบีบอัดด้วยการตัดสินใจของ Jev: ทุกการเรียกใช้เครื่องมือและผลลัพธ์จะถูกประเมินในหนึ่งการร้องขอที่รวดเร็ว ข้อมูลเก่าจะถูกลบหรือตัดทอน ทุกอย่างที่เก็บไว้จะคงรูปแบบเดิม
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Browser automation where an LLM plans and Jev (Typesafe System One) decides. Library, CLI and MCP server.
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A developer project for the agents shelf featuring a local MCP gateway with Jev tool discovery and a dashboard.
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A moderation system for Mastra agents that processes inputs in a single file.
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Typesafe's jev as a "fuzzy linter". give your code an ocular patdown.
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A developer project for agent classification and selective reading using an agent plugin and MCP tool.
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Jev handles seven SEO and GEO workflows, including competitor page analysis, citation likelihood, and content optimization.
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Browser use for coding agents, 3-5x faster than browser-use. MCP server + CLI; TypeSafe Jev decides every step in ~300 ms.
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An experiment using Jev to interpret voice commands and trigger tool actions before the user finishes speaking.
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A project using Jev to enable fast voice-controlled interactions with a Mac computer.
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Official TypeSafe reference: Skill suggestion.
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Proof of concept MCP for Typesafe's new Jev AI model.
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One grounded Jev/Playwright core: typed SDK, persistent CLI, and MCP server with native browser operations and deterministic assertions.
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Agent Skill: send closed coding-agent judgments to TypeSafe Jev.
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Jev-Tool-Runner is a GitHub project where Jev selects developer tools and Codex generates code based on those selections.
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A Chrome extension enabling agents to browse and interact with websites, utilizing Jev for decision-making.
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A deterministic model routing system for coding agents with a skill for Codex.
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A YouTube guide explaining Jev's functionality, including browser use, classification, and code review without an LLM.

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An experimental local-first plugin for coding agents that uses Jev to provide quality feedback during development.
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A system using Jev to interact with computer interfaces without screenshots, relying on local CoreML models and OCR.
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Route to the cheapest model in claude code for your task using jev-router.
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Jev-browser enables agents to perform web tasks by automatically opening websites and making click decisions based on screen content.
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A community post about improving a Slack agent's speed using Jev for faster skill and tool classification.
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การใช้คอมพิวเตอร์ในราคาประมาณ 0.0002 ต่อขั้นตอน: สแกนหน้าจอ จัดประเภทการกระทำถัดไปด้วย TypeSafe คลิก macOS
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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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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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A developer project where Jev assists in browsing by selecting actions, with an LLM planning and citing sources.
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A developer project for agent-native routing that selects models based on task complexity.
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Fast Rust CLI for TypeSafe Jev: typed decisions, offline linting before you pay.
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Jev automates browser tasks by selecting actions from a dynamic action space.
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An agent system that makes one Jev decision per computational step.
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MCP server and agent skill for the TypeSafe AI System One API (Jev): decompose a judgment into Choice / Score / Noul questions, lint them, measure on labelled data, and put calibrated thresholds in code.
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An open-source model for form-filling tasks with low latency.
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A Codex plugin that uses Jev to streamline and reduce excessive tool outputs.
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A YouTube guide explores using Jev within an agentic coding loop, focusing on cost efficiency for development tasks.

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Non-autoregressive decision engine on ModernBERT (151M) with calibrated uncertainty (RLCD), TypeSafe AI Jev benchmark audit, and in-browser WebGPU playground.
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An agent using headless Chromium to quickly navigate the web, demonstrated by browsing Wikipedia links efficiently.
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A content marketing tool that analyzes 12.8M viral videos to generate data-backed social media scripts.
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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 developer project that uses Jev as a sensor to control access to agent tools, enhancing security and functionality.
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Context curator for Pi agent using Jev technology.
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A focus group experiment using Jev to make scroll or stop decisions on ads.
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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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Tutorial covers API setup and building prototypes with Jev and LLMs.

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A resource explaining Jev's functions, costs, and evaluation metrics as TypeSafe's System One model.
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Detects low-quality content in real-time as users scroll.
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Jev controls both hands and fingers to play piano in real-time based on visual input.
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A collection of 19 open-source projects using Jev technology for various applications including AI agents and game interactions.
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Agent automates second-hand product search and decision-making. Processes 26 listings per minute with fast evaluation times.
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100% free ₹0 agent-first SEO & GEO CLI suite and MCP server in Rust replacing Semrush and OpenSEO via DuckDuckGo and TypeSafe Jev System One.
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Jev-assisted file retrieval and request caching for faster Pi workflows.
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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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A small agent using Jev compaction to manage searchable memory efficiently.
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Data extraction for systematic reviews, quoted from the papers. Ask a trial report and its supplements your extraction form or a RoB 2, ROBINS-I, QUADAS-2 or TIDieR template; Jev points at the lines, every answer is a verbatim quote with its page, you check it and export the table. Files stay in your browser.
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Claude Code plugin: trim long Bash output with TypeSafe Jev before the model sees it.
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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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An agent that plays Tetris with rapid decision-making capabilities. Shows potential for real-time game automation.
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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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Agent-ergonomic CLI for TypeSafe's Jev: fast calibrated judgments (pick, rate, check, rank, triage, guard) from the shell.
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An agent project that enforces policies by judging Claude Code tool calls.
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Jev was integrated with Claude Code to address context compaction challenges in agent workflows, showing promising results.
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A community post about humor management on a social platform.
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A system enabling rapid agent deployment on digital canvases without relying on slow LLM processes.
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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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Control a real browser by voice. Jev (TypeSafe System One) decides intent + target in ~300 ms per spoken word; Playwright acts — often before you finish the sentence.
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Write Cucumber tests with just the .feature file. No step definitions — Jev (TypeSafe AI) resolves each Gherkin step and Playwright runs it.
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Daf-jev: composable Python toolkit for TypeSafe's Jev (System One) decision API — question builders, confidence gates, evaluator, calibration, CLI, MCP server, agent skill.
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5–10x faster browser operations: Jev clicks, Codex thinks and verifies. Built at EZCollegeApp.
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An agent project aimed at reducing token usage for coding agents via an MCP server.
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Fast structured Android control loops with TypeSafe Jev and Mobile MCP.
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A community project describes an agent system that uses Jev to route requests to appropriate models.
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