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I just built a Jev X Swarm Controller and put 300 agents on autopilot for 6 minutes. 300 K3 workers on autopilot. 6 minutes. 12,480 turns. Jev made a decision on every one of them. 91 reached me. A swarm knows how to execute. It does not know when to stop. every turn gets 6 typed questions: is this result good enough, is there new information, is this the same state as last turn. then one action: continue / retry / stop / merge / spawn / escalate. what the loop actually did: 1,642 STOP - same state twice, the loop was going nowhere 806 MERGE - two workers on the identical finding 91 ESCALATE -

Been building a little browser agent with Jev. Give it a goal. Jev figures out what to do. Playwright does it. Look → Decide → Act → Repeat. No screenshots. No hardcoded clicks. Just an AI figuring out the website as it goes. Solves problems. Fast. Cheap. Simple.

OODA AI + OpenClaw + VM + Jev = 7,1 sec for a Google Flight Search with Agents running full Computer Use. Uses Sol as primary Model, Luna as Light Model and Jev as classifier. But pick your flavor! We also have Laya and Von and any of our over 80+ AI models wrapped in an /v1/systemone endpoint. OODA AI is an All-in-One AI platform with over +150 AI models across Text, Image, Video, Audio, Avatars. Check the comment for a short video of how we use Jev and System1 models to decrease 50% context use, increase speed on Agent decisions in OpenClaw, handle better intent and tool decisions, Guardrail

Over the weekend, our team built a novel agentic document processing system using Jev. The initial results are very promising. Our system completed the same editing task 97% faster than ChatGPT's Word plugin. https://t.co/sZFU4qcgUJ

so uh i've been using my computer while driving lately, and it's in the best interest of the world that i stop doing that. so this weekend I used @typesafeai jev + @kwindla's @pipecat_ai to make a live voice agent for managing multiple tmux coding agents (claude code, codex, opencode, etc) fully hands-free I can talk to one voice agent, who gives me updates and let's me send messages to my team of coding agents working on different projects. something i usually hate about live voice agents is that they always interrupt! so I tried using jev for classifying whether I am speaking directly t

tried using jev to flag browser agents this weekend. it runs through the activity logs live every 3 seconds and builds an average score over the session sure you could do this without jev, but also it took a few hours and cost less than $0.01 per session https://t.co/9XUQIeSqWL

A tiny open source browser agent using Jev instead of an LLM for every click. Found a flight search in 7 SECONDS. Total cost: $0.0039. Here's why that's not a typo. A normal browser agent asks a chat model "what should I click" on every single step. That's a full generation call, just to pick a button. Mine doesn't. The DOM state at each step becomes the input. Jev gets the available actions as a typed choice question. It picks the action, not by generating text, by classifying against what's actually on the page. The only place a language model still runs is typing free text into a fie

noticed below cumulative impact of using Jev + Jevcache + Fable: - Per-decision: ~220–780ms Jev vs 20–40s claude before - Loop's decisions are ~50× cheaper; Fable was consulted only on the 3 low-confidence steps - jevcache: earlier identical-phrasing re-run showed cached (0ms replay) live.. repeat run was 26% faster (7.2→5.3 min)

No, 'caliente, caliente no más! We shipped JarvisCore 1.12 and it comes with Jev by @typesafeai ! Come and learn about Jev next week on Wednesday. We're bringing @askmuyukani founder at @prescottdata for a live discussion on how JarvisCore is using Jev to build faster and cheaper agents, and what opportunities exist to extend Jev in agent harnesses.

Holy shit. Using Jev in my JARVIS just made it like actual super intelligence. what the fuck. Will release the update asap. https://t.co/LJZA4z7fSf

Humble beginnings using Jev. Trying to integrate it into Codex and help with speeding up browser use. Been working on it all day and running hundreds of trails. So far I've spent... $0.00725 https://t.co/yX3mPB41pL

I made an AI agent using Jev to reply to my wife We’re getting a divorce now and she wants to know who Jason is

Using Jev to catch Codex workers ignoring AGENTS.md. Combine live Codex output, Git changes, and AGENTS.md into one observation Use Jev to score the probability that the worker is drifting from AGENTS.md Steer the active Codex turn when drift crosses a threshold, stopping it if the drift continues Added to Foreman, which automatically watches and steers workers on the software factory floor. https://t.co/g9prp3tsy8

Episode 285: Bendcoder We build an experimental coding agent from scratch using Jev from @typesafeai and new programming language Bend2 from @VictorTaelin. ...while playing WoW Forever on CoderOS; demoing the CoderOS GPU-accelerated multiplex panes and hand tracking (goodbye Hyprland, hello Jarvis); and introducing CoderQuest, a forthcoming game for commanding and upgrading coding agents with real-world prizes. Meanwhile in Azeroth, Eetum arrives in Thunder Bluff and purchases a guild charter. Bendcoder repo: https://t.co/UjtjgTEAZS

What I’m doing with #Jev from @typesafeai: Making Ergod, my multiplayer AI agent, better at the work between “let me check” and actually getting it done. Better research. Clearer comparisons. Fewer dead ends. Small decisions. Bigger capabilities. 🧵 A result can match your keywords and still miss your question. Jev helps assess what’s relevant. Alongside better page reading, Ergod can focus on useful evidence in long articles and wiki pages - with headings and tables kept in context. The follow-up is where this gets interesting. “What about the exceptions?” “Where did that figure come f

Seeing how many people are using Jev to control browsers I wanted to try too. Wrote the wrapper for 'dev-browser' and called it 'jev-browser'. And then tried to put it to a test: "Find the best pricing model for WP Multitool for someone who runs 3 sites, spends 3h/yr on each, and has $50/hr rate and will run them for 2 years." I saw that it did the right steps until the last one. Was adding the Lite version to the cart. That's how I discovered that while my Pricing page LOOKS good it's structurally awful and definitely nor readable for BOTS or SCREEN READERS. Learned something = PR

judge jev is the law. score two browser agents w/ different models on task completion, using jev to judge which was more efficient at the job. scored on correctness, time, actions, and cost. https://t.co/8M7JBou6O1

Implemented this exact thing today in the @knocklabs agent harness using Jev based on the common types of requests we see from live traces.

I built a Chrome extension for agentic browsing using Jev by @typesafeai, https://t.co/Xa9toMieqT including AI Gateway by @vercel. Now agents can browse, click, and interact with websites directly in your browser. Cost effective and fassst. Decision-making by Jev. https://t.co/bIqkUbCkvc

Vibe coded a parallel search using jev for agents, planning to hook up a local LLM to this to get human output. Discovers new pages and adds them to a BFS queue, jev consumes pages in parallel, reranks and adds to the queue. https://t.co/EkpZhuYmRB