Jev lansman yazısı
Diogo Almeida, TypeSafe'ın yapılandırılmış karar modeli Jev'i tanıtıyor. Lansman filmini izleyin ve modelin yaklaşımını, örneklerini ve yazarın bildirdiği performansını keşfedin.
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Recent activityA FIELD GUIDE TO JEV / VOL. 01
Jev’in en iyileri: gerçek projeler, pratik rehberler ve internetten fikirler.
Diogo Almeida, TypeSafe'ın yapılandırılmış karar modeli Jev'i tanıtıyor. Lansman filmini izleyin ve modelin yaklaşımını, örneklerini ve yazarın bildirdiği performansını keşfedin.
TypeSafe'ın resmi lansman duyurusu, laboratuvarı tanıtır ve geliştiricileri Jev'e yönlendirir. Diogo Almeida'nın lansman filmi ve orijinal girişimi içerir.
TypeSafe, Jev'e açık erişimi duyurdu. Resmi konsol, uygulamanızda türden kararlar denemek için başlangıç noktasıdır.
TypeSafe, Jev'in türden çıktı yaklaşımını vurgular: uygulamalar durum ve sorular sağlar, ardından olasılıklar, seçimler veya puanlara göre hareket eder. Bağlantılı duyuruda Venice API entegrasyonu da yer alır.
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.
Claude Code eklentisi, kompaktlama özeti yerine Jev kararlarını kullanır: her araç çağrısı ve sonucu tek bir hızlı istekle puanlanır, eski olanlar atılır veya kesilir, her şey korunurken aynı kalır.
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Tarayıcı kullanımında ultra hızlı agent: Jev, işlemi ve DOM elementini tek bir istekle seçer; küçük bir LLM, yazma gerektiğinde metin yazmak için kullanılır.
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A developer project offering semantic code search for coding agents, benchmarked on SWE-bench Lite.
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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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Agent makes rapid shopping decisions using Ego Lite and Jev. Completes 20 product evaluations in under 4 seconds.
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Bir adımda yaklaşık 0,0002 dolarla bilgisayar kullanımı: ekranı OCR'leyin, bir sonraki eylemi TypeSafe ile sınıflandırın, tıklayın. macOS.
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Standalone Android agent for Mobilerun where Jev makes every decision, with a live React studio and an Uber demo.
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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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Jev-Tool-Runner is a GitHub project where Jev selects developer tools and Codex generates code based on those selections.
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An agent system that makes one Jev decision per computational step.
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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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A community post discussing Jev's use in enforcing coding rules that linters cannot handle.
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A resource explaining Jev Engineering methodology for AI agent development.
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Fast structured Android control loops with TypeSafe Jev and Mobile MCP.
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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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Jev analyzes outreach messages to identify signals that lead to booked demos, improving campaign performance.
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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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Typesafe's jev as a "fuzzy linter". give your code an ocular patdown.
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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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A community project enabling hands-free web navigation by having Jev handle browser actions while Claude manages conversation.
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Marcel Pociot's browser extension that collapses posts based on a Jev judgment.
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A massively parallel browser-based adversarial testing suite for evaluating releases, costing pennies.
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A community post describing 500 real-time agents operating in a 3D environment with notable performance metrics.
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A community project exploring Jev's potential to evaluate agent progress beyond basic trace data.
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Context curator for Pi agent using Jev technology.
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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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A plugin using Jev's scoring capability to remove unnecessary terminal garbage and redundant logs, improving agent performance.
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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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A developer project for the agents shelf featuring a local MCP gateway with Jev tool discovery and a dashboard.
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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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An agent using headless Chromium to quickly navigate the web, demonstrated by browsing Wikipedia links efficiently.
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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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A focus group experiment using Jev to make scroll or stop decisions on ads.
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A skill for writing and improving programs that call Jev, TypeSafe's System One model.
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Official TypeSafe reference: Skill suggestion.
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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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Fast Rust CLI for TypeSafe Jev: typed decisions, offline linting before you pay.
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A moderation system for Mastra agents that processes inputs in a single file.
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A deterministic model routing system for coding agents with a skill for Codex.
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A project using Jev to enable fast voice-controlled interactions with a Mac computer.
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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 calibrated context sieve for Claude Code: every tool result is judged by a System One model before it enters context.
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A developer project using Jev for plain-language MCP tool calls without an LLM.
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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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Jev automates browser tasks by selecting actions from a dynamic action space.
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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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Jev achieved 100% task success on the WebMCP benchmark with significantly lower model costs compared to other systems, using a combination of tool selection and argument generation.
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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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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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A small agent using Jev compaction to manage searchable memory efficiently.
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A system enabling rapid agent deployment on digital canvases without relying on slow LLM processes.
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Enables instant compaction by scoring and filtering tool calls efficiently.
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A Chrome extension enabling agents to browse and interact with websites, utilizing Jev for decision-making.
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Proof of concept MCP for Typesafe's new Jev AI model.
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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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MCP server that puts TypeSafe Jev on the coding loop in Cursor, Codex, and any MCP client.
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A resource explaining Jev's functions, costs, and evaluation metrics as TypeSafe's System One model.
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Tutorial covers API setup and building prototypes with Jev and LLMs.

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An agent project aimed at reducing token usage for coding agents via an MCP server.
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Jev automates the filling of prompt boxes by selecting appropriate agents, models, or computers for specific tasks.
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Runtime constraints for the pi coding agent: checks every side-effecting tool call against what you said, before it runs. Powered by TypeSafe Jev.
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Typed, confidence-aware agent skill routing with TypeSafe Jev.
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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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An agent project that enforces policies by judging Claude Code tool calls.
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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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Reduces SEO and GEO fix costs by 90% through faster data analysis and automation.
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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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Explains Jev's role in automating decision-making processes and enabling new business models through efficient task sorting and classification.
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Reduces context usage by 30-55% through Jev-based compaction for OMP agents.
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Framework for running end-to-end tests with agents using Jev.
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A community post describes a plugin that manages agent context by analyzing and pruning unnecessary data, available in Spanish.
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