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Independent radar of Jev builds, experiments and use cases — scored by Jev, not by likes. Not affiliated with TypeSafe AI.

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1298 published builds · 5606 buildersBuilt with Amp · © 2026 Jev Radar

CHOOSEAgents & automation

Jev AI Assistant

VertrAI@vertr_ai

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1:44

Original post ↗

Sep 21

293 views · 3 likes · 1 reposts on X · does not affect score

Jev is an AI assistant that helps in decision-making, as demonstrated in a Minecraft context and browser automation.

ChatGPT thinks through the plan. Jev helps pick the next move. ⚡ Minecraft, browser automation, speed and cost—Jev explained in under 2 minutes. 👇 Featuring demos by @rronak_ and @gregpr07, benchmarks from @OpenRouter, and Jev by @typesafeai. #Jev #AI x.com/vertr_ai/status/2101921554116592055/

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Jev Decision Model

Jev is a typed decision model that returns a probability for a given state (question, answer, evidence) instead of generating prose or structured data, making it faster and cheaper than traditional AI judges.

Jose Luis Latorre | #MVP | #K6 | @DotNetZurich@joslat

40 views on XJev score 79

Jev Model Asymmetry Analysis

This project analyzes the Jev model's behavior, revealing that natural language wording induces a significant conviction asymmetry between buy and sell sides, while the model itself is symmetric when presented with symmetric prompts.

Dan Holzrichter@dholzric

83 views on XJev score 79

TypeSafe Computer Use

This project enables a Mac to achieve plain-English goals by combining OCR and the Accessibility tree to drive actions, avoiding large model loops for screenshots.

Yash Chaudhary@YashChaudhary

4 views on XJev score 78

Jev Decision Model Evaluation

Jev, a decision model from TypeSafe, was tested on standard AI problems, answering structured questions with probabilities and performing comparably to or better than other models on single-step tasks, but struggled with sequential reasoning without state information.

Nikhil Deshpande@nikhdesh

94 views on XJev score 76

Quality35

NoveltyiHow surprising the Jev use is versus an obvious typed-decision call. Generic mentions score low; a new primitive scores high.31
UsefuliHow reusable the technique is for another builder. Toys score low; a production-quality idea scores high.42
SubstanceiHow much concrete evidence supports the claim: code, numbers, demo, architecture. Hype scores low.33

Quality is Jev’s judgment of the idea. Likes, reposts and views do not affect it. Relevance is a separate gate.