A FIELD GUIDE TO JEV / VOL. 01
O melhor de Jev: projetos reais, guias práticos e ideias de toda a internet.
TypeSafe AI@typesafeaiOFFICIALTypeSafe highlights Jev’s typed-output approach: applications provide state and questions, then act on probabilities, choices or scores. The linked announcement also covers the Venice API integration.
x.comAnswers your code can useVer projeto ↗
Diogo Almeida@CompleteSkepticLAUNCH POSTDiogo Almeida introduces Jev, TypeSafe’s structured decision model. Watch the launch film and explore the original thread for the model’s approach, examples and author-reported performance.
TypeSafe AI@typesafeaiOFFICIALTypeSafe’s official launch announcement introduces the lab and points builders to Jev. It includes Diogo Almeida’s launch film and original introduction.
TypeSafe AI@typesafeaiOFFICIALTypeSafe announces public access to Jev without a waiting list. The official console is the starting point for trying typed decisions in your own application.
x.comJev opens to everyoneVer projeto ↗Four official signals. A fresh starting point on each visit.
1.198 recursos
AI-assisted summaries and translations. Check original sources for context and performance claims.
Leonardo Bissoli apresenta decisões estruturadas com Jev, incluindo confiança, limites e exemplos de uso em aplicações.
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Página do criador Leonardo Bissoli com seu vídeo, capítulos e referências sobre decisões estruturadas com Jev.
leonardobissoli.comJev: decisões estruturadas e casos de usoVer projeto ↗Source-linked curation
Kevin GrajedaClassificador que avalia a dificuldade de prompts em tempo real, permitindo modo rápido para prompts simples para melhorar a interação do usuário.
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Agente ultra-rápido para uso no navegador: Jev seleciona a operação e o elemento DOM em uma única solicitação; um pequeno LLM escreve texto apenas quando necessário.
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Chris TateExperimento que combina renderização JSON com Jev para criar interfaces de usuário geradas instantaneamente para renderização rápida de componentes e sistemas de design.
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metr0xSimulação em que o MOSS coleta lixo com base em instruções, visando melhorar a limpeza das ruas por meio de tomada de decisão automatizada.
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Higgsfield AI 🧩Demonstração mostrando o Jev selecionando os modelos de IA mais adequados para tarefas de geração de vídeo e imagem no Higgsfield.
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Contrato de solicitação e resposta para POST /v1/systemone.
docs.typesafe.aiSTATE → DECISION → CODEVer projeto ↗Source-linked curation
Demonstração interativa oficial sobre resposta especulativa: múltiplas perguntas em uma única chamada, com código selecionando respostas relevantes.
docs.typesafe.aiSTATE → DECISION → CODEVer projeto ↗Source-linked curation
Atualizações de produto e pesquisa.
x.com@typesafeai on XVer projeto ↗Source-linked curation
Servidor oficial da TypeSafe. Demonstrações de construtores estão no canal Show and Tell.
discord.ggDiscordVer projeto ↗Source-linked curation
Gregor ZunicDemo de busca de voo de Gregor Zunic com espaço de ação dinâmico do DOM.
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Fan-out especulativo, roteamento com confiança, pontuação composta e roteamento de intenção.
docs.typesafe.aiSTATE → DECISION → CODEVer projeto ↗Source-linked curation
Modos de falha conhecidos do modelo público atual, documentados pela TypeSafe.
docs.typesafe.aiSTATE → DECISION → CODEVer projeto ↗Source-linked curation
Faadil ShaikO Jev controla Super Mario Bros. usando inferência rápida e saídas estruturadas, demonstrando potencial para aplicações em tempo real.
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Caminho mais curto desde uma chave de API até uma decisão tipada.
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Introdução, primitivas, padrões, receitas, API HTTP e referências do SDK.
docs.typesafe.aiSTATE → DECISION → CODEVer projeto ↗Source-linked curation
Post de lançamento: arquitetura, treinamento RLCD, preços, demos de Doom e Wikiracing, FAQ.
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Nailthy TangExperimento de tentativa virtual em tempo real usando Jev para selecionar e mudar roupas com base na entrada do usuário e análise de transcrições.
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Plugin de código Claude que substitui o resumo de compactação por decisões Jev, avaliando todas as chamadas de ferramentas e resultados em uma única solicitação rápida, descartando ou truncando os obsoletos.
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Defesa da inteligência nativa de máquinas projetada para software, não para conversas.
typesafe.aiManifestoVer projeto ↗Source-linked curation
Receitas reprodutíveis: perguntas paralelas, reranking, guardrails, verificações de citação, extração, classificação hierárquica.
docs.typesafe.aiSTATE → DECISION → CODEVer projeto ↗Source-linked curation
Metodologia de avaliação e resultados por modelo para fluxos do System One.
evals.typesafe.aiWorkflow evalsVer projeto ↗Source-linked curation
Referência oficial da TypeSafe: Introdução.
docs.typesafe.aiSTATE → DECISION → CODEVer projeto ↗Source-linked curation
Choice, Score e Noul: os três tipos de perguntas e o que retornam.
docs.typesafe.aiSTATE → DECISION → CODEVer projeto ↗Source-linked curation
Cole um estado, adicione perguntas e veja respostas tipadas no navegador.
console.typesafe.aiPlaygroundVer projeto ↗Source-linked curation
Cliente oficial sincronizado e assíncrono em Python. pip install typesafe-sdk.
github.comtypesafe-ai/typesafe-sdk-pythonVer projeto ↗Source-linked curation
Um planejador de consultas baseado em Jev otimiza o desempenho do Postgres, obtendo um aumento de 12% na velocidade em benchmarks de ordem de junção através de ajustes.
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Substituição oficial do TypeSafeClient com suporte a APIs de LLM da OpenAI, Anthropic e compatíveis, para comparar Jev com modelos de chat.
github.comtypesafe-ai/system-one-adapter-pythonVer projeto ↗Source-linked curation
Public examples of Jev used for robot control, 3D modeling and adjacent control tasks, with sources and archived media.
github.comFrank-ZY-Dou/awesome-jevVer projeto ↗Source-linked curation
x.comJev enables flexible, type-safe classification as a fundamental programming primitive.
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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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A resource discussing a new model type that outperforms LLMs in specific areas, collected for the tools shelf.
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Raihan KhanA tool that analyzes public PR links to determine if they are safe to merge or need review, using Jev's capabilities.
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x.comA collection of 19 open-source projects using Jev technology for various applications including AI agents and game interactions.
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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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toksA community post describes using Jev with an LLM to play Doom, exploring multiple future outcomes.
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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.
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Integrates Jev into apps for smart autofill features improving user experience.
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SaeedA tool built on Jev that identifies programming languages, colors code, and checks lint rules.
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An AI-driven hedge fund utilizing Jev for fast and cost-effective trading decisions.
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tamaraEnables instant compaction by scoring and filtering tool calls efficiently.
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CJ (Coding Garden)A chat bot using Jev without a large language model, providing instant responses by integrating web search, Wikipedia, weather, and other tools.
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Marcel Pociot 🧪A macOS app that automatically organizes downloaded files using rules.
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Diogo AlmeidaDiogo Almeida introduces Jev, TypeSafe’s structured decision model. Watch the launch film and explore the original thread for the model’s approach, examples and author-reported performance.
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A GitHub project converting agent skills into Oxlint plugins that involve Jev.
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A community post about humor management on a social platform.
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Uses Jev for real-time voice commands to control a browser, processing speech to actions in 300ms with low cost.
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DuncanEphraim Duncan's demo where Jev decides which model should serve a request.
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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 developer project that selects applicable rules for Claude, ensuring only relevant information is shown.
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Jev conducts a sentiment-based stock market analysis for the Danish market in 2025, using diverse data sources with low cost.
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A guide on using Jev to route between models and block risky tool calls.
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Jev is used in mobile end-to-end testing with improved efficiency.
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Jevals is a local testing environment for evaluating Jev requests and improving results through primitive operations.
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Steve KrouseSteve Krouse's playable 16-judgment demo and video.
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生ビールA local Jev model for processing tasks with potential for improved speed.
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A community post presents a codebase complexity classifier using Jev, aiming to address overengineered code.
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Jev plays Connect Four on OmarchyLinux, demonstrating real-time decision loops with structured state.
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Paul WeiJev model demonstrates fast decision-making in a strategy game. Achieves high-speed gameplay with minimal visual feedback.
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A community post explores Jev's decision-making in ethical scenarios, comparing different approaches.
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Jev processes 1,000 emails for category, priority, spam, and reply predictions.
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Jev is used to predict human moves in a rock-paper-scissors game.
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Riley BrownJev classifies 500 emails quickly and inexpensively, demonstrating its efficiency in processing tasks.
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A livestream analyzing Jev's architecture for JSON-predicting models.
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A tested resource evaluating Jev's capabilities in browser automation and support tasks.
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Nader DabitJev powers a predictive launcher that anticipates user intent based on typing patterns.
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An experiment using Jev to transform simple English into elaborate prose in real-time during writing.
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Jev enables users to create various applications using its architecture, as explained in a YouTube guide.
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Rust CLI powered by Jev from TypeSafe.ai that ranks agent skills for the next step using live session context. Includes Claude Code hooks, structured JSON, abstention, and local feedback. Requires a TypeSafe API key.
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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 project uses Jev to detect AI-generated text, providing real-time sentence-by-sentence analysis.
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