A FIELD GUIDE TO JEV / VOL. 01
The best of Jev. Real projects, practical guides and ideas from across the internet.
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 ARTStart with the Launch Post. Explore four official signals.
1,262 resources
AI-assisted summaries and translations. Check original sources for context and performance claims.
This project provides a skill for Letta agents to perform criteria-based evaluations using the TypeSafe System One framework. It demonstrates how to integrate Jev-based logic for structured decision-making processes within agentic workflows.
JEVLAB ART
EnglishSource-linked curation
This project demonstrates a playful application of Jev technology to generate randomized responses to user inquiries. It functions as a digital novelty tool, showcasing how Jev can be integrated into interactive, decision-making interfaces for casual entertainment purposes.
JEVLAB ARTEnglishSource-linked curation
This MCP server integrates TypeSafe Jev capabilities into agent workflows. It provides structured methods for classifying, scoring, and screening data, aiming to deliver verifiable confidence levels for each automated response generated by the system.
JEVLAB ARTEnglishSource-linked curation
This gaming project demonstrates a mechanism for toggling between manual control and AI-driven gameplay. It showcases how Jev can be integrated into interactive environments to facilitate real-time transitions between human input and automated agent decision-making.
JEVLAB ARTEnglishSource-linked curation
x.comThis community discussion explores the potential of Jev to function as a high-speed, cost-effective decision-making layer for AI agents. It proposes that integrating Jev could streamline agentic workflows by providing a lightweight control mechanism for complex task execution.
JEVLAB ARTEnglishSource-linked curation
Reproducible early-access evaluation of Jev on Korean understanding and medical text, with runtime and cost evidence.
JEVLAB ARTEnglishJev PASSFIT 77%CAT 100%
A developer project using Jev for plain-language MCP tool calls without an LLM.
JEVLAB ARTEnglishJev HOLDFIT 69%CAT 53%
This project demonstrates a Jev-powered agent designed to automate LinkedIn recruitment tasks. It showcases the agent browsing professional profiles, saving relevant links, and evaluating candidates based on specific hiring criteria provided by the user.
JEVLAB ARTEnglishSource-linked curation
This research project investigates the practical utility of Jev confidence scores during task execution. It provides a framework for developers to assess how these metrics correlate with model performance in real-world scenarios.
JEVLAB ARTEnglishSource-linked curation
This command-line interface tool enables users to perform calibrated judgments like ranking, rating, and triaging directly from the shell. It demonstrates an agent-ergonomic approach to interacting with TypeSafe Jev workflows for streamlined data processing.
JEVLAB ARTEnglishSource-linked curation
OFFICIALTRANSLATEDTypeSafe AIThis official TypeSafe AI reference guide demonstrates how to implement line-by-line semantic search functionality. It provides developers with the necessary patterns to perform precise text retrieval within structured datasets.
JEVLAB ARTEnglishJev HOLDFIT 90%CAT 34%
This project provides a benchmarking framework for market analysis using Jev. It demonstrates how developers can structure data-driven evaluations within the Jev ecosystem to assess specific financial modeling tasks.
JEVLAB ARTEnglishSource-linked curation
This project features a guide-directed agent for World of Warcraft. The creator claims the system is designed to optimize and reduce in-game expenses as the agent continues to operate over extended periods of time.
JEVLAB ARTEnglishSource-linked curation
This command-line interface tool by Vercel Labs enables developers to interact with AI models directly in the terminal. It demonstrates how to integrate Jev as an evaluation model for automated performance testing and quality assessment tasks.
JEVLAB ARTEnglishSource-linked curation
roverlab is a 3D planetary rover simulation environment. It serves as a sandbox for developers to experiment with autonomous decision-making processes using TypeSafe AI frameworks within a virtual extraterrestrial terrain.
JEVLAB ARTEnglishSource-linked curation
Idan LevinThis resource showcases Jev performance on the WebMCP benchmark. The creator claims the system achieved full task success while reducing model costs through optimized tool selection and argument generation strategies compared to alternative agentic frameworks.
JEVLAB ARTEnglishSource-linked curation
This tool converts AGENTS.md preference files into a Jev-powered linter. It demonstrates a method for automating the validation of agent configurations by leveraging Jev architecture to enforce defined behavioral standards during the development process.
JEVLAB ARTEnglishSource-linked curation
A decision cache for TypeSafe Jev-class models — memoize decisions so repeats are free, deterministic, and shareable. One 2 MB binary.
JEVLAB ARTEnglishJev HOLDFIT 68%CAT 47%
kenoThis resource demonstrates how Jev can be utilized to analyze competitor advertising materials. It highlights a workflow for processing ad data to generate curated creative shortlists for marketing strategy development.
EnglishJev HOLDFIT 45%CAT 87%
This project demonstrates a Typesafe.ai System One model designed to navigate Neo4j graph databases. It utilizes a classifier to analyze neighboring relationships, providing a structured approach for Jev-based graph traversal and decision-making processes.
JEVLAB ARTEnglishSource-linked curation
This project features a real-time flight simulation game where Jev's decision-making capabilities manage the aircraft. It demonstrates how autonomous logic can be integrated into interactive gaming environments to handle navigation and flight control tasks.
JEVLAB ARTEnglishSource-linked curation
Foreman is an agent supervisor designed to manage coding agents. It utilizes Jev-based decision-making processes to help maintain focus and ensure agents remain on their assigned tasks during development workflows.
JEVLAB ARTEnglishSource-linked curation
This project demonstrates an implementation of Typesafe.AI to automate the generation of code diff reviews. It provides a workflow for integrating AI-driven analysis into version control processes to assist developers in evaluating code changes.
JEVLAB ARTEnglishSource-linked curation
jlink provides a framework for linking data records using plain-English matching rules. It utilizes Jev Noul pair judgments to perform local candidate blocking and automated match resolution for record linkage tasks.
JEVLAB ARTEnglishSource-linked curation
This repository provides a collection of Jev-powered tools for Hermes agents. It demonstrates implementations for model routing, memory management, data compaction, skill selection, and automated computer or browser interaction capabilities.
JEVLAB ARTEnglishSource-linked curation
This project demonstrates the integration of TypeSafe Jev as a decision-making layer for a coding agent. It explores how structured, quiet reasoning can be applied to automate software development tasks within the pi agent framework.
JEVLAB ARTEnglishSource-linked curation
A visual TypeSafe demo where Jev chooses verified Tetris placements.
JEVLAB ARTEnglishJev PASSFIT 75%CAT 98%
Self-hosted AI email classifier for Gmail powered by Jev. Create custom labels, organize your inbox, and filter spam with confidence and cost controls.
JEVLAB ARTEnglishJev PASSFIT 71%CAT 70%
This Rust library provides typed clients for AI services, supporting both asynchronous and blocking backends. It demonstrates how to implement observable retry mechanisms to improve the reliability of AI-driven application interactions.
JEVLAB ARTEnglishSource-linked curation
A small, fast prose linter: ruff-style rule codes for writing, backed by TypeSafe's Jev model.
JEVLAB ARTEnglishJev HOLDFIT 70%CAT 43%
This project demonstrates a camera-only autonomous drone simulation within the MuJoCo environment. It features a TypeSafe Jev judgment model integrated into the control loop, which the creator reports operates at a frequency of 2.5Hz.
JEVLAB ARTEnglishSource-linked curation
This command-line interface facilitates interaction with the Jev evaluation model. It demonstrates a workflow for submitting typed queries and receiving responses formatted as structured JSON, aiming to streamline automated evaluation processes for developers working with TypeSafe AI systems.
JEVLAB ARTEnglishSource-linked curation
This Go SDK provides an interface for the TypeSafe AI API. It enables developers to send typed queries to the service and receive structured probability distributions as output, facilitating integration within Go-based applications.
JEVLAB ARTEnglishSource-linked curation
Uses Jev to conduct a musical orchestra in real time through a demonstration project.
JEVLAB ARTEnglishJev HOLDFIT 62%CAT 27%
x.comThis experiment evaluates Jev as a search reranker, finding limited performance gains over standard vector retrieval. The creator reports mixed results that vary significantly based on the specific evaluation methodology applied during testing.
简体中文Jev PASSFIT 76%CAT 99%
OFFICIALTRANSLATEDTypeSafe AIThis official reference documentation details advanced structural primitives for TypeSafe AI. It provides technical guidance on organizing complex data architectures to ensure consistency and reliability within AI-driven development workflows.
JEVLAB ARTEnglishSource-linked curation
Rob HallamSuperX integrates with Jev to automate content evaluation. The creator claims the tool analyzes 61 distinct questions per post in under one second to estimate viral potential.
EnglishJev HOLDFIT 63%CAT 90%
A developer project for the games shelf, where Jev improvises piano with proper questions.
JEVLAB ARTEnglishJev HOLDFIT 69%CAT 93%
x.comA community post shares a tech talk by Jev's founder, highlighting its speed, cost-effectiveness, and lack of hallucination.
EnglishJev HOLDFIT 45%CAT 64%
This MuJoCo pilot project evaluates robotic pick-and-place performance by comparing Jev, Claude Haiku, and traditional reactive rules. It provides a reproducible environment to observe how different decision-making approaches handle basic manipulation tasks in a simulated physics setting.
JEVLAB ARTEnglishSource-linked curation
CartShield utilizes TypeSafe Jev to assist small and medium-sized businesses in managing checkout fraud. This tool provides a structured approach for evaluating transaction risks and automating disposition processes within e-commerce environments.
JEVLAB ARTEnglishSource-linked curation
This tool automates pull request analysis by evaluating code against Clean Code principles. It utilizes Jev for assessment and Luna for review, providing structured feedback on code quality within a Next.js framework.
JEVLAB ARTEnglishSource-linked curation
von is an open-source System One decision model designed as a local, non-autoregressive alternative to TypeSafe Jev. The creator claims the model achieves sub-15ms inference speeds for decision-making tasks.
JEVLAB ARTEnglishSource-linked curation
TypeSafe AI System One (Jev) task plugin for QuantumNous/new-api — native /v1/systemone, synchronous evaluation, token billing.
JEVLAB ARTEnglishJev HOLDFIT 75%CAT 55%
Tony DinhThis Chrome extension utilizes Jev to identify and automatically bypass sponsor segments within YouTube videos. It demonstrates a practical application of real-time content analysis to streamline the viewing experience for users.
EnglishJev HOLDFIT 61%CAT 49%
Eric ZhangThis project provides a Jev-compatible public API leveraging open models. It demonstrates an approach to achieving fast parallel processing for Jev-based workflows using the sglang framework.
EnglishJev HOLDFIT 49%CAT 31%
This project demonstrates the rapid response capabilities of Jev when executing browser-based tasks. The developer reports that the agent makes operational decisions in approximately 100 milliseconds during standard testing scenarios.
JEVLAB ARTEnglishSource-linked curation
This Python prototype demonstrates an agent playing NES Super Mario Bros. by interpreting structured RAM data. It utilizes Jev to process game state information and determine appropriate movement and jumping actions for the character.
JEVLAB ARTEnglishSource-linked curation
This open-source tool provides a mechanism for calibrating confidence thresholds within Jev systems. It demonstrates a practical approach for users to adjust sensitivity settings to better align model outputs with specific operational requirements.
JEVLAB ARTEnglishSource-linked curation
limpet provides a stop hook designed to prevent coding agents from terminating tasks prematurely. It utilizes plain-language rules evaluated by Jev to maintain process continuity.
JEVLAB ARTEnglishSource-linked curation
Proof of concept MCP for Typesafe's new Jev AI model.
JEVLAB ARTEnglishJev PASSFIT 80%CAT 69%
x.comA 4-minute video explaining what Jev is and its limitations.
EspañolJev HOLDFIT 59%CAT 98%
A tool for tracking decisions made by Jev, using Arize's instrumentation for detailed analysis.
JEVLAB ARTEnglishJev HOLDFIT 87%CAT 17%
x.comThis collection highlights various Jev-based projects and experiments shared on social media. It serves as a curated overview of community-driven applications, demonstrating the practical utility and creative potential of the Jev ecosystem for developers and enthusiasts.
JEVLAB ARTEnglishSource-linked curation
khaledThis demonstration showcases Jev's functionality for rapid variable generation within development workflows. The creator highlights how the tool automates data handling, though users should evaluate its performance and integration capabilities within their own specific coding environments.
EnglishJev HOLDFIT 61%CAT 42%
Eugene CheahSimple Jev is an open-source library designed to convert Hugging Face models into Jev-style endpoints. This tool aims to improve accessibility by simplifying the integration process for developers looking to deploy machine learning models within the Jev ecosystem.
EnglishJev HOLDFIT 49%CAT 70%
This project introduces a System One-style model fine-tuned from Qwen3.5-2B. It demonstrates a method for performing single-pass typed decision-making tasks while incorporating calibrated probability outputs for improved reliability in automated reasoning workflows.
JEVLAB ARTEnglishSource-linked curation
DGUI-HyperMem is a self-hosted hybrid memory MCP server deployed on Cloudflare Workers. It utilizes a JEV reasoning layer and a HuggingFace-based training flywheel to manage memory, demonstrating an experimental approach to integrating persistent data structures with automated reasoning workflows.
JEVLAB ARTEnglishSource-linked curation
This plugin integrates TypeSafe Jev System One decision tools into the Hermes Agent framework. It provides specific functions for checking, routing, scoring, and evaluating agent decisions to improve operational logic and reliability within the system.
JEVLAB ARTEnglishSource-linked curation
This repository provides a benchmark comparing Jev against a strong LLM using the Who&When Pro agent-failure-attribution dataset. It demonstrates a methodology for evaluating how effectively these systems identify and attribute specific failures within agentic workflows.
JEVLAB ARTEnglishSource-linked curation
Jev is used in mobile end-to-end testing with improved efficiency.
JEVLAB ARTEnglishJev HOLDFIT 52%CAT 38%
Small game that tests how Jev handles unknown input.
JEVLAB ARTEnglishJev HOLDFIT 58%CAT 89%
Typed JSON inference with DiffusionGemma, with Every and Jev benchmark results.
JEVLAB ARTEnglishJev HOLDFIT 60%CAT 87%
This tool provides a per-prompt capability router for coding agents. It resolves installed skills, MCP servers, and commands using TypeSafe Jev while attempting to measure the effectiveness of these injections on agent performance.
JEVLAB ARTEnglishSource-linked curation
x.comThis resource contrasts Jev with LLMs, highlighting how Jev evaluates predefined decisions directly. It demonstrates how this architectural difference allows for the parallel processing of independent questions, distinguishing its operational approach from standard generative language models.
EnglishJev HOLDFIT 69%CAT 54%
pg-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.
JEVLAB ARTEnglishSource-linked curation
This tool integrates Jev-powered ranking into zsh shell history. It demonstrates how to provide Fish-style autosuggestions by leveraging TypeSafe AI to prioritize command history based on user context and relevance.
JEVLAB ARTEnglishSource-linked curation
Not every coding task needs your best model. Experimental Jev-powered model routing for Claude Code — V3 prototype runs today, V4 routes at the task boundary.
JEVLAB ARTEnglishJev HOLDFIT 64%CAT 93%
Fayaz AhmedThis project demonstrates an image classification workflow integrating OCR and Jev. The creator reports processing 900 images within a 40-second timeframe using this automated pipeline.
EnglishJev HOLDFIT 66%CAT 53%
River shooter game in Python, inspired by Atari's River Raid, played by a TypeSafe AI pilot.
JEVLAB ARTEnglishJev HOLDFIT 68%CAT 98%
This 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.
JEVLAB ARTEnglishSource-linked curation
This research project compares Jev, Gemini 3.8 Flash, and GPT-5.6 Luna regarding their performance in structured annotation of TJSP legal sentences. It evaluates the quality, processing time, and operational costs associated with each model.
JEVLAB ARTEnglishSource-linked curation
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4 HIGHLIGHTS
TRANSLATED
Tools & apps
Source-linked curation
Agents & browsers
Games & real time
Research & data
Markets & experiments
Creative & growth
Decisions & routing