JEVThe best of Jev. Real projects, practical guides and ideas from across the internet.
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THE OFFICIAL SIGNAL 4 HIGHLIGHTS
Diogo Almeida@CompleteSkepticLAUNCH POSTDiogo Almeida introduces Jev, a structured decision model from TypeSafe. This resource provides an overview of the model's core approach, practical examples, and performance metrics as reported by the author.
TypeSafe AI@typesafeaiOFFICIALTypeSafe officially launches its research lab and introduces Jev to the developer community. This announcement features a launch film by Diogo Almeida and provides foundational context for the project's mission and future direction.
TypeSafe AI@typesafeaiOFFICIALTypeSafe has removed the waitlist for Jev, allowing public access to the platform. Developers can use the official console to integrate and test typed decision-making capabilities within their own software applications.
JEVLAB ARTTypeSafe AI@typesafeaiOFFICIALTypeSafe highlights Jev’s typed-output approach, where applications provide state and questions to receive structured probabilities, choices, or scores. The announcement also details the integration of the Venice API for developers.
JEVLAB ARTAI-assisted summaries and translations. Check original sources for context and performance claims.
kitze 🛠️ tinkerer.clubJev Calc is a notebook-style interface that integrates Jev processing to handle complex mathematical operations. This tool demonstrates how natural language inputs can be parsed and computed within a structured document environment.
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Kun ChenThis agent plugin utilizes Jev to identify optimal moments for session compaction. It aims to assist developers in managing context more efficiently by providing automated guidance on when to consolidate session data.
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vogelThis experiment showcases an automated system designed to classify and manage large volumes of incoming messages. It demonstrates the potential for streamlining inbox organization by processing 1,500 emails to test classification effectiveness.
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x.comThis community post provides a simplified overview of Jev, describing it as an AI agent designed for decision-making tasks. The author claims it offers faster and more cost-effective performance compared to standard frontier large language models.
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JEVLAB ARTThis repository provides a live trading implementation for the Hyperliquid platform using Jev. It demonstrates how to integrate automated trading logic with the exchange's API to execute market operations in real-time.
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JEVLAB ARTJev-AV is a security tool that analyzes executables, scripts, and documents by extracting structural features like entropy and hashes. It utilizes Jev to evaluate these files for potential malicious activity in real-time.
EnglishThis project demonstrates a method for OMP agents to reduce context usage. The creator claims that utilizing Jev-based compaction can decrease memory requirements by 30-55 percent during operation.
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JEVLAB ARTThis project demonstrates Jev managing urban traffic flow within a simulated environment. It provides a practical look at how the model handles real-time decision-making tasks in a structured city grid.
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Robert YangThis tool demonstrates how Jev applies semantic formatting to spreadsheet data. It provides automated structural suggestions and outlines potential integration pathways for external platforms to enhance data organization workflows.
EnglishBannerbear introduces an automated field mapping feature designed to streamline the alignment of data sources with design templates. This tool aims to simplify workflows by enabling users to connect disparate data fields with a single click.
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tamaraThis project demonstrates a method for instant compaction within Claude by implementing a scoring and filtering system for tool calls. It aims to improve efficiency by selectively managing the data processed during agent interactions.
EnglishThis community post explores the potential of using Jev via TypeSafe AI for quality assurance tasks. It demonstrates a conceptual workflow for automated software testing processes using the platform's capabilities.
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JEVLAB ARTThis tool enables developers to build and version judgment functions for Jev. It supports calling these functions via HTTP or MCP, while ensuring vendor keys remain local to the user's machine for enhanced security.
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x.comThis resource provides a clear overview of Jev, framing it as a specialized decision-making tool. It outlines the practical use cases and inherent limitations of the system to help users understand its intended role in AI workflows.
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JEVLAB ARTCanny provides a mechanism to prevent AI coding agents from prematurely declaring tasks complete. It utilizes deterministic hooks and an append-only ledger to ensure evidence-based verification of work, operating with zero runtime dependencies.
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生ビールThis project demonstrates a local Jev model configuration designed for task processing. The creator suggests this approach may offer potential improvements in execution speed compared to cloud-based alternatives for specific local workflows.
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JEVLAB ARTThis guide by Fazt introduces Jev for implementing type-safe decision-making processes. It provides practical examples demonstrating how to structure logic within applications to ensure consistent and reliable data handling.
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JEVLAB ARTJev Social demonstrates an automated research tool that performs bounded browser operations on social media platforms. It captures evidence from Instagram, TikTok, and LinkedIn to generate cited reports based on the retrieved data.
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JEVLAB ARTThis repository provides a public demonstration of Jev and TypeSafe AI integration for X. It serves as an experimental tool for developers to explore how these frameworks interact within a social media context.
EnglishJEVLAB ARTThis repository provides visual data comparing the performance of TypeSafe Jev against 110 other models on Thai standardized examinations. It serves as a comparative visualization tool for evaluating model accuracy within specific regional academic testing benchmarks.
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JEVLAB ARTThis project evaluates Jev against standard chat models by analyzing Federal Reserve press conference transcripts. It demonstrates how the model interprets monetary policy sentiment to classify central bank communication as hawkish or dovish.
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JEVLAB ARTThis tool utilizes typeful Jev and zero-sync architecture to facilitate the retrieval and synchronization of large repositories. It is designed to assist developers in streamlining the issue triage process through automated data handling.
EnglishJEVLAB ARTThis developer project demonstrates a filtering mechanism for Jev that processes tool results before they reach the model. It aims to enhance the operational efficiency of agent-based systems by streamlining data input.
EnglishThis Jev-powered system automates document processing by analyzing PDFs page by page. It demonstrates a decision-making workflow that identifies which specific pages require OCR, aiming to optimize resource usage during document digitization tasks.
EnglishThis guide demonstrates integrating Jev into an agentic coding workflow. The creator claims this setup achieves high cost efficiency for automated development tasks compared to standard agentic loops.
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JEVLAB ARTThis project demonstrates the application of the Typesafe AI Jev model to automate gameplay in the classic Chrome T-Rex runner. It serves as a practical experiment in integrating AI agents with browser-based game environments.
EnglishThis project demonstrates a text generation system built on Jev. It utilizes a classifier within an autoregressive loop to produce output one character at a time, showcasing a granular approach to language modeling.
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JEVLAB ARTThis project demonstrates a workflow using Jev to triage and route live Bluesky firehose data. It provides a framework for integrating automated processing with human oversight for content management.
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JEVLAB ARTThis Claude Code plugin utilizes TypeSafe Jev to automatically truncate lengthy Bash command outputs. It aims to optimize context windows by ensuring models only process relevant data before analysis begins.
EnglishJEVLAB ARTThis Python CLI tool demonstrates an experimental approach to semantic line searching using TypeSafe Jev and OpenRouter. It provides a lightweight interface for querying data without requiring complex runtime dependencies.
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JEVLAB ARTJev is introduced as a specialized System One model designed exclusively for decision-making tasks. The creators claim it achieves significant speed and cost improvements compared to small frontier LLMs, though these performance metrics remain independent observations.
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appcypherThis experimental game demonstrates how Jev AI can generate multiple branching timelines to prevent character death. The project explores real-time decision-making processes within a classic gaming framework to maintain continuous gameplay.
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JEVLAB ARTThis project demonstrates a compact Jev-inspired model designed to run locally on a MacBook. It serves as a practical example of lightweight model deployment for developers interested in portable AI execution.
EnglishTypeSafe AIThis documentation defines the Questions interface within the TypeSafe AI SDK. It demonstrates how to structure questions as an indexable object, where each entry is keyed by a unique name to facilitate organized retrieval of associated answers.
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JEVLAB ARTThis project demonstrates the application of TypeSafe Jev noul judgment primitives to analyze the collusion.wiki corpus. It explores authorship classification by comparing human and agent-generated content using Qwen3.8-Flash-Next models in head-to-head and local configurations.
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JEVLAB ARTInterlock demonstrates a security framework using Jev as a sensor to gate access to agent tools. This project explores methods for enhancing operational control and functional safety within autonomous agent environments.
EnglishJEVLAB ARTThis GitHub tool integrates Jev into your development workflow by requiring its approval before merging pull requests. It demonstrates a method for automating code review gates using Jev-based validation to ensure repository standards.
EnglishJEVLAB ARTThis tool provides recommendations for installed skills within the TypeSafe Jev environment. It features a Python CLI, a Codex skill integration, and bilingual documentation to assist users in managing their skill sets effectively.
EnglishThis tool demonstrates a Gomoku implementation using Jev. It utilizes local tactical analysis to reduce 225 potential moves to 40 candidates, from which the system selects an optimal play based on tiered strategic options.
EnglishJEVLAB ARTjevegis provides a unified API for implementing guardrails in LLM applications. It is designed to detect prompt injections, jailbreaks, data leaks, and unsafe content, leveraging the TypeSafe Jev framework to enhance security for language model interactions.
EnglishThis project showcases a Rubik's Cube prototype that utilizes Jev AI to perform self-solving maneuvers. The creator demonstrates an approach modeled after human problem-solving techniques instead of relying on traditional optimal mathematical algorithms.
EnglishJEVLAB ARTThis tool enables automated auditing of git diffs against defined YAML coding standards. It utilizes the Jev model to provide consistency checks directly through a command-line interface or integrated AI agent workflows.
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JEVLAB ARTThis experiment demonstrates Jev selecting legal moves during a chess match. The creator compares its performance against established reasoning models to evaluate decision-making capabilities within the constraints of the game.
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JEVLAB ARTThis project features a real-time Tetris implementation where Jev-based agents compete against other AI models. It demonstrates game logic integration and multi-agent interaction within a competitive environment.
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JEVLAB ARTpg-jev is a PostgreSQL extension that enables natural language querying of database tables. It integrates Jev technology to allow users to interact with their relational data using plain English prompts.
EnglishJEVLAB ARTzcode-jev provides a typed judgment layer designed for coding agents. It acts as a gatekeeper between product requirement documents and deployment, offering a provider-agnostic framework for Jev-ready development workflows.
EnglishJEVLAB ARTThis project demonstrates an implementation of Atari Pong using TypeSafe Jev. It functions by presenting a single typed choice question per frame to control gameplay without transmitting coordinate data to the model.
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Hugo DuprezThis resource showcases a technical approach to generating game environments dynamically during gameplay. It demonstrates how procedural systems can create playable levels in real time, offering developers a practical reference for implementing adaptive world-building mechanics in their own projects.
EnglishThis community reference explores how Jev interprets toxic content. It provides a brief look at the system's perception of negative sentiment, though it lacks deep technical analysis or comprehensive documentation regarding its underlying classification methods.
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JEVLAB ARTjevalyn provides a Rails-native interface for the TypeSafe Jev System One API. This tool enables developers to integrate typed, calibrated decision-making processes directly into their Ruby on Rails application control flows.
EnglishJEVLAB ARTThis repository provides an unofficial Go client library designed to interface with the TypeSafe System One API. It serves as a foundational tool for developers looking to integrate the Jev model into their Go-based applications.
EnglishJEVLAB ARTPiJev is a terminal-based coding agent that integrates Jev to manage repository file ranking, skill selection, and error triage. The project demonstrates a collaborative workflow where Jev coordinates tasks while a separate coding model generates the actual code.
EnglishThis resource explores how Jev agents can be utilized to enforce complex coding rules that traditional linters often fail to detect. It demonstrates a practical approach to maintaining codebase consistency through automated, context-aware editorial oversight.
EnglishJEVLAB ARTThis project provides six hook gates for Claude Code designed to identify rule violations, out-of-scope edits, and incomplete requests. It demonstrates a validation workflow where Jev evaluates agent outputs against a fixed checklist and specific evidence.
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ZachiThis PostgreSQL extension introduces a jev() function designed to facilitate natural language querying directly within database environments. The project demonstrates a method for bridging human-readable inputs with structured database operations to simplify data retrieval tasks.
EnglishJEVLAB ARTThis library provides an idiomatic, type-safe Elixir port of the TypeScript AI SDK. It enables unified LLM integrations, streaming text, structured outputs, and tool calling, while supporting agentic workflows using the Jev model.
EnglishJEVLAB ARTThis project evaluates the ability of Jev to predict successful A/B test outcomes for headlines. The creator reports that Jev correctly identified the winning headline in 64.5% of over 10,000 Upworthy experiments, with accuracy increasing when performance differences were more pronounced.
EnglishJEVLAB ARTThis project provides a Neon Function proxy designed for the Neon AI Gateway. It demonstrates how to implement TypeSafe Jev routing to manage AI service requests within a structured and reliable development environment.
EnglishJEVLAB ARTJev DSPy Lab provides tools for recording, replaying, and benchmarking TypeSafe AI decisions within DSPy pipelines. It enables developers to measure calibration, selective risk, latency, and modeled costs using deterministic offline analysis.
EnglishTypeSafe AIThis official documentation provides a comprehensive technical reference for the TypeSafe AI Python SDK. It outlines available classes, methods, and parameters designed to assist developers in integrating TypeSafe functionality into their applications.
JEVLAB ARTEnglishThis community-shared experiment demonstrates Jev performing real-time analysis of Solana blockchain data. The post highlights how the system processes on-chain information, though users should note this is an independent demonstration rather than a verified institutional tool.
EnglishTypeSafe AIThis official resource provides a chronological record of updates and modifications to the TypeSafe SDK. It serves as a primary reference for developers to track version history and identify specific changes implemented in the platform.
JEVLAB ARTEnglishJEVLAB ARTThis experiment features a browser-native Doom agent utilizing a Chocolate Doom WebAssembly runtime. It demonstrates structured spatial state management and composable AI controls, providing live decision telemetry for monitoring the agent's performance within the game environment.
EnglishTypeSafe AIThis guide outlines the three core question types in TypeSafe AI: Choice, Score, and Noul. It explains the specific data structures and return values associated with each primitive to help developers structure their AI interactions effectively.
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JEVLAB ARTThis resource outlines the core functions and evaluation metrics of Jev, presented as the System One model by TypeSafe. It provides an overview of how the system operates and the criteria used to assess its performance in agentic workflows.
EnglishJEVLAB ARTThis proof-of-concept demonstrates low-latency audio censorship by integrating Jev typed decisions with ffmpeg. It illustrates how structured decision-making can be applied to real-time media processing workflows.
EnglishJEVLAB ARTJevable serves as a curated directory for Jev-related projects and demonstrations. It provides users with organized categories and submission tools to help discover and share new developments within the Jev ecosystem.
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JEVLAB ARTThis tool integrates Zod with Jev to perform semantic validation on request bodies. It enables developers to convert meaning-based checks into calibrated probabilities, allowing for threshold-based logic within application code.
EnglishTypeSafe AIThis official reference documentation explains the Choice primitive within the TypeSafe AI framework. It outlines the structural implementation and intended usage patterns for developers integrating decision-making logic into their AI-driven applications.
JEVLAB ARTEnglishJEVLAB ARTThis position paper introduces the Deferred Crispification principle and the BSF-S1 architecture. It argues for integrating Hidden-Markov and fuzzy primitives into Jev and System-One decision models to improve TypeSafe AI framework capabilities.
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x.comThis presentation by Jev founder Diogo Almeida explores the platform's architecture. The creator claims the system achieves high operational speed and cost efficiency while maintaining accuracy, though these performance metrics remain independent of third-party verification.
EnglishJEVLAB ARTThis community-developed Java client provides an unofficial interface for the TypeSafe System One API. It demonstrates how developers can integrate TypeSafe services into Java-based applications using a structured client library approach.
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4 HIGHLIGHTS
Tools & apps
Agents & browsers
Decisions & routing
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Markets & experiments
Games & real time
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Research & data
