Jev 런치 포스트
Diogo Almeida가 TypeSafe의 구조화된 판단 모델 Jev를 소개합니다. 런치 영상과 원문 스레드에서 접근 방식, 활용 사례, 제작자가 발표한 성능을 확인하세요.
A FIELD GUIDE TO JEV / VOL. 01
인터넷 곳곳의 Jev 프로젝트, 실용적인 가이드와 놀라운 아이디어를 한곳에서.
Diogo Almeida가 TypeSafe의 구조화된 판단 모델 Jev를 소개합니다. 런치 영상과 원문 스레드에서 접근 방식, 활용 사례, 제작자가 발표한 성능을 확인하세요.
TypeSafe가 스텔스 모드를 마치고 Jev를 공개했습니다. Diogo Almeida의 런치 영상과 소개 스레드로 이어지는 공식 발표입니다.
TypeSafe가 대기 목록 없는 Jev 공개 접근을 발표했습니다. 공식 콘솔에서 앱에 사용할 구조화된 판단을 시작할 수 있습니다.
TypeSafe가 Jev의 구조화된 출력을 소개합니다. 앱의 상태와 질문을 전달하면 확률·선택지·점수로 응답하며, 연결된 발표에서 Venice API 통합도 확인할 수 있습니다.
Launch Post부터 시작하세요. 공식 원문 4편을 살펴볼 수 있어요.
1,198 개 자료
요약·번역에 AI를 활용합니다. 원문과 성능 주장은 출처에서 확인하세요.
A plugin using Jev's scoring capability to remove unnecessary terminal garbage and redundant logs, improving agent performance.
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Semantic GitHub PR labels using Jev's typed decisions, with conceptual scope instead of line counts.
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A process using Jev to filter and select assets, then generate ad creatives with DeepSeek and Higgsfield.
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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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A voice-controlled interface for Figma utilizing Jev, demonstrating low-cost AI integration for design tools.
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Tool for systematic reviewers to extract information from research articles efficiently.
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Everyday Stocks Status with Jev.
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A local Jev model for processing tasks with potential for improved speed.
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An MLP trained on Qwen 4B that functions similarly to Jev, offering a typesafe alternative.
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Jev 기반 쿼리 플래너로, Postgres 성능을 최적화하여 조인 순서 벤치마크에서 12%의 속도 향상을 달성했습니다.
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A tool that monitors user interactions and intervenes only when it detects confusion or difficulty, using Jev to determine appropriate responses.
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Jev는 보안 파이프라인의 효율성을 향상시키며, 더 낮은 비용과 더 빠른 처리를 제공하면서도 더 작은 모델보다 높은 정확도를 유지합니다.
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An experimental game where Jev AI generates multiple timelines to keep Mario alive through decision branching.
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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 system enabling rapid agent deployment on digital canvases without relying on slow LLM processes.
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A tool that uses Jev to detect AI-generated content on websites by analyzing specific indicators.
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Jev is discussed with examples of Choice, Noul, and Score in a Python project.
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A community project exploring Jev's potential to evaluate agent progress beyond basic trace data.
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A setup where Jev selects between different AI models for specific tasks, streamlining model usage in a single terminal.

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A community post suggests Jev accelerates computer use, claiming 100x faster processing than standard LLMs.
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Jev evaluates the pacing of a frontier-AI essay written by @DarioAmodei.
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Jev processes 1,000 emails for category, priority, spam, and reply predictions.

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Integrates Jev into apps for smart autofill features improving user experience.
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Jev analyzes session replays to identify issues and generate bug fix PRs at low cost.
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A community post describes an A/B test using Jev to analyze 4,000 demographic profiles, demonstrating its speed in processing and evaluating content.
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A demonstration of Jev's capability to quickly categorize a large volume of Hacker News posts.
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Real-time Discord moderation bot: Jev evaluates messages and metadata in parallel to catch phishing, spam, and social engineering with a progressive escalation ladder.
JEVLAB ARTSource-linked curation
공식 TypeScript AI SDK(ai / ai-sdk)의 타입 안전한 Elixir 포트로, 단일 LLM 통합, 스트리밍 텍스트 및 구조화된 출력, 도구 호출, 에이전트 워크플로우를 제공합니다. Jev는 현재 주력 모델이며, 첫 번째 System One 모델입니다.
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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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Typed, confidence-aware agent skill routing with TypeSafe Jev.
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Minimal grammY Telegram anti-spam bot powered by TypeSafe Jev.
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askjev.ai. A community post describing a platform where users can ask questions to Jev, which provides judgments rather than direct answers.
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Jev predicts upcoming shell commands by analyzing historical command data.
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A speech analysis tool that evaluates 30-second speeches for pauses, filler words, and confidence, providing feedback for improvement.
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A community post describing a robot arm controlled by Jev, using cameras and decision-making at two decisions per second.
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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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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 offering a Chrome extension to blur low-value LinkedIn posts, collected for the creative shelf.
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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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Jev-assisted file retrieval and request caching for faster Pi workflows.
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Jev generates 100 images from sources like NASA and The Met based on a single prompt.
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A project where Jev attempts to defeat the Pokémon League in Pokémon Gold, using basic controls to navigate and win.
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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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TypeSafe가 스텔스 모드를 마치고 Jev를 공개했습니다. Diogo Almeida의 런치 영상과 소개 스레드로 이어지는 공식 발표입니다.
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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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A tool that provides quick actions based on clipboard content, specifically for macOS.
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A guide explaining how to integrate Jev with Pydantic AI agents for type-safe operations.
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클라우드 코드, 코드크스 및 호환 에이전트를 위한 공식적인 에이전트 기술: 기본 구성 요소, 패턴 및 평가 구조 방법.
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Jev successfully played and won a match in the game Clash Royale.
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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 tags X posts in real time with labels like 'breaking,' 'golden nugget,' or 'slop'.
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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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Detects low-quality content in real-time as users scroll.
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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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TypeSafe AI의 System One 모델인 Jev를 사용하여 구축된 프로젝트의 정리된, 소스 기반 목록입니다.
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Using Jev to create Clay workflows instantly, leveraging its capabilities for rapid development.
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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 community post exploring Jev's behavior in a game of Catan, where multiple Jevs struggle with negotiation.
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A project exploring pixel-level image generation through parallel decision-making processes.
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Jev rapidly analyzed news articles to suggest relevant stories for brands at a low cost.
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A free AI tool built on Jev that quickly scans text for low-quality content, processing around 10,000 words in 2 seconds.
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A community experiment using Jev to analyze social media posts and determine effective content strategies.
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A developer project for the games shelf, where Jev improvises piano with proper questions.
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Aaron Levin: 155x cheaper than Opus 5, about 20x faster, and it generalizes across operating systems.
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Jev identifies and manages marketing messages in Android notifications without content deletion.
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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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Jev differs from LLMs by evaluating predefined decisions directly, enabling parallel processing of independent questions.
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A developer created an instant calorie tracking app using Jev for quick responses.
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A community post demonstrating Jev playing Flappy Apex, achieving a high score autonomously through Appduct and Fable.
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Jev plays Tetris by making real-time decisions to move blocks.
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A 26-sheet construction plan set was classified in 2.9 seconds using Jev with an LLM pipeline, costing $0.0052 and matching GPT-4.1 and GPT-6 Astra performance.
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Observe the accessibility tree, Jev chooses the next action, Stagehand executes.
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