Jev Model for Fast In-Game Decision Making
TypeSafe's Jev, a fast System One model, makes quick picks from given options. In-game, a rules layer filters legal moves and spells, while Jev chooses where to place runes.
THE JEV GUIDE · CURATED EDITION
Jev Guide.
Launch news, explanations, demos, and community projects around TypeSafe Jev, organized by topic. Every entry links back to its X source.
Curated selection · Not exhaustive · Updated manually
5419curated posts
2789original videos
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Question Design Matters More Than the Model: Jev vs Laya Test
In the same 430-case test, Jev let through 68–92% of false agent reports and Laya 84–88% when shown evidence; after asking one literal question instead, Jev let through only about 1% of wrong counts and files. The question matters more than the model. Link
Jev: A Tiny Decision Model
The post points out that we've been using our smartest frontier models for basic yes/no decisions, wasting their capability. Jev flips that by being a tiny decision model for simple tasks.
Jev Smart Routing: Cut Cost from $18 to $1.30 per 1,000 Calls
User shares using jev as a scorer with Haiku 5.5, Sonnet 5.5, and Opus 5.5 to build a cost-optimized smart model stack. By letting each call climb only as far as the task requires, the cost for 1,000 calls drops from $18.00 (all Opus 5.5) to $1.30.
Jev sparks a question: why generate a paragraph when an agent needs to decide?
OpenBMB discusses how Jev raises the question: why generate a paragraph when an agent only needs to make a decision? It highlights steps like route selection, input classification, and next-action choice in AI workflows as clear choices from known options.
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Free Live Session: Building Decision Layers for AI Agents Using Jev
Youssef Hosni will host a free live session on Thursday, October 15, demonstrating how to build decision layers for AI agents using Jev. Register free via the link in the comments.
Jev Decodes the Secret Recipe Behind Top Creators' Reels
Joon shares how Jev transcribed and broke down 900 Reels from 5 creators like Kallaway and Alex Hormozi, extracting the content strategy behind billions of combined views.
Closed-loop demo of JEV, Claude Opus 5.5, and GPT Dots
The post shows a live closed-loop system with JEV, Claude Opus 5.5, and GPT Dots on a single screen, where the spider carries three things at a time and almost never walks empty, contrasting with most AI stacks that send every task through the same pipe.
Jev + Claude Combined Workflow
The author combines Claude's reasoning with Jev's speed in a single coding pipeline, creating a seamless flow from prompt to planning to execution, and claims this makes traditional AI coding agents look slow and expensive.
JEV now has 12 competitors
A community member notes that TypeSafe's JEV now has 12 competitors, with Cloudflare and OpenAI standing out as particularly strong, and none of these existed three weeks ago.
Jev: Millisecond Responses, Low-Cost AI Answers
Jev answers questions in 70–500 ms at a fraction of the cost of word-by-word chat models. For 1,000 emails with 7 questions each, a chat model takes 5 minutes and $0.62—Jev is faster and cheaper.
Free Webinar: Building Decision Layers for AI Agents with Jev
A free webinar hosted by ToDataBeyond on Thursday, October 15, about building decision layers for AI agents using Jev. Reserve for free via the link in the comments.
