X posts

🧵 I gave Jev $10,000 and let it trade BTC again. But this time, I gave it everything a trader would look at: market data, derivatives, macro, on-chain data, news and sentiment. 30 days https://t.co/6STcUk4ml1

Added a live eval system to my webmcp native component library, which I have been using for generative ui and consulting. It evaluates the component as soon as it's generated and if it's not valid, regenerates instantly. Left side is a chat agent with Claude, right side is the Jev Eval loop, webmcp tool calls.

Jev-style "typed decisions" without training anything. On a frozen Qwen3-4B: turn each schema field into a lettered question and read the option letters' logits. No output tokens. Same accuracy as grammar-constrained JSON on closed enums. 4× faster on short inputs, up to 2.4× on long ones with a shared-prefix cache. Strings and numbers still need generation. Write-up, figures, teaching bench: http

Built a pumpfun grading bot with Jev! Every new launch, Jev grades its chance at graduating. If it's over 10% it buys. Starting with a $10k paper account. https://t.co/4t9Xa6pAaL https://t.co/gJ6kUdPnLD

First quick test of Jev from @typesafeai Install via @vercel gateway Sending evaluation (input validation passed): { "model": "typesafe-ai/jev", "state": { "character": "2" }, "questions": { "kind": { "type": "choice", "instructions": "Is the character a number or a letter?", "criteria": { "number": "The character is a single numeric digit from 0 through 9.", "letter": "The character is an upperca

a binary event contract's price IS a probability. 0.62 = the market says 62%. so i pointed a @typesafeai jev at @dreamDEXSomnia to disagree with the book. @Somnia_Network reactivity pushes every event, whole loop under a second. 70k events tracked in 10 sec with offchain websocket. 0.212 brier vs the book's 0.311. testnet. mainnet next.

I built real-time Clippy with Jev. It quietly watches how you use the product and only wakes up when it thinks you’re struggling. Hesitating? Confused? Stuck? Clippy knows. Even its reactions are controlled by Jev. 👀 https://t.co/EgMhw8FPi1

I build a SQL extension that turns plain english into a WHERE clause with jev @typesafeai WHERE jev(people, 'could work from home') Every row gets judged individually, no index and no embeddings needed. Try it out (don't burn my wallet pls) https://t.co/4nYZVH9iXs

Can Jev bluff itself? I spun up two Jev agents, gave them 1,000 chips each, hid their cards from each other and let them play heads-up poker until one went broke. 20 hands. 153 Jev decisions. Biggest pot: 1,760 chips. Both got caught bluffing. Red Jev took all 2,000. The entire match cost $0.02. @typesafeai

Jev made a coin. Jev is TypeSafe's System One model. It answers in types, not prose. So its first coin is typed too. One schema, validated once, sent to two chains in the same request. $JEVCOIN Solana, on Pump CA: A66FqchgzB8PCv9smWYvDctB4tWBefoEMnCecLvfpump Robinhood Chain, on Pons v2 CA: 0x8C0B9EaE5a2aF9680968c4d46fB43266491681cC

open sourced jev-lint, the linter i run on my own markdown wiki. one run over 99 pages: 16 flags for me to read, about 2 cents in input tokens. it never edits anything. agents wrote most of it, i set the constraints. #AIAgents #Obsidian https://t.co/5mrgk9AT8R

Dowse is a terminal-native web browser + answer engine. Search the web, read pages, follow links and generate cited answers — without leaving your terminal. I’ve added @typesafeai @CompleteSkeptic Jev as an opt-in System One layer in the answer pipeline: Search → Jev → LLM Before generation, Jev makes fast, structured judgments over the retrieved sources — relevance, usable evidence and prompt-inj

Jev only outputs probabilities. So I gave it the Snake board as text and asked one question every frame: up, down, left, or right? No training, no game code inside the model. It played fine for a while, then boxed itself with nowhere left to go. https://t.co/e6lGyVTrlk

I taught Jev to paint! Jev predicts a probability for each color of each cell, then we visualize the probability distribution: high confidence = big, flat strokes; low confidence = fine brush to layer different possibilities https://t.co/L99f5txwha

jevによる絵文字候補のリアルタイム出力デモ 100ms~200msで応答してくれる 絵文字の選択肢は3種類でも200種類でも、応答速度は変わらないのが面白い https://t.co/ImSC2zLLje

I just got access to Jev from @typesafeai and implemented it into https://t.co/U9dQ9zMz2T to replace the AI classifier I was using to clean the newsletters users are forwarding to read on their reMarkable or Kindle. The results are amazing and the newsletter content is now beautifully formatted. #jev #typesafeai

Wow it’s fast 🤯 Here’s Jev, in real time, scoring guesses and categorizing questions inside a tiny “Hot or Cold” game I threw together https://t.co/tJ0nKVsMxJ

I used Jev to make an audience of 100 personalities to yap to. Each blob has its own personality and makes its own Jev call every time you talk to decide if it’s bored of you yet. Each round costs <$0.01 in credits. Really cool model from @typesafeai ! https://t.co/nGlKuxxfAA https://t.co/YgRdcS5pfs

Jev is fun! One-click invoice finder for any website 🧾 - Automatically finds billing pages using @typesafeai's Jev - List/download all invoices with 1 click - Works with Stripe billing portals too - Remembers where invoices live for next time Should I open-source it? https://t.co/0pZmbrG7a4

Jevでポケモンのタイプ判定機作った サムアルトマンは、でんき・エスパー イーロンマスクは、でんき・はがね で解釈一致w https://t.co/nusP1ElSjV

This is absolutely crazy. I connected @typesafeai to my Icy Tower game and I’m shocked by how fast Jev reacts. Jev picks the landings, the game handles the jumps, and a live inspector shows its choices, probabilities, and inputs. Super excited to see how this evolves! https://t.co/wPWS9HrqxP

Just got access to Jev and built the most requested feature in quickinbox with it. It can label incoming emails as spam or any custom labels you set. You can classify the old emails from before this too, and it's actually fast. Quick walkthrough: https://t.co/h727bKMcBE

Evangelion's MAGI, but real. 3 AI sages (powered by Jev, TypeSafe's System One model) deliberate your question and vote. Typed, calibrated, no hallucinations. Built entirely with Kiro — even this video. 🎬 👉 https://t.co/vWgK5vwqCQ #Jev #Kiro #AWS https://t.co/YuEBHxbVku

Jevによるリアルタイム接客の試作📝 クリックする前のカーソルの往復や滞在から、迷いや関心をAIで推定。 お客さんの様子をつぶさに見て、状態を判断。 説明を補ったり、比較を提案したり、そっと見守ったりする。 パラメーターを頑張れば、百貨店の店員さんを再現できそう。 https://t.co/cZrEsUyAxq

Some more experiments with Jev. It can (sorta) control a robot body https://t.co/OHaYU2rCqG

I built a visual reference finder with Jev One single prompt → 100 images from Cosmos, NASA, and The Met my new rabbit hole for creative work 🌻

The speed and cost is going to enable use cases that haven't been possible before. Here's a quick demo of live decisions of what slide to pull up as I'm speaking, powered by @typesafeai Jev. Also, sorry for the sniffling. I have a bit of a cold. https://t.co/124B5YEjmF

jevil is in the details 😈 built a quick POC running agent-device with jev and learned a ton. check the source code or read a short blog post ⬇️ https://t.co/XVOUa0JW6U

@typesafeai is such a paradigm shift for realtime data. I just built https://t.co/z1tVgD11VK, which watches a livestream, feeds it to Jev, and generates clips if they are good. Imagine a streamer being able to auto-publish shorts while they are livestreaming. No post-processing. Just live, auto-generated clips instantly. Give it a try and let me know what you think!

Have been sick all day so haven’t had much time to mess around with Jev yet. But I did add an update to my game. I realized I suck at it so added a training mode where you can design your training session. You can add rebound boards, cones, more balls and much more. Then just jump into practice. Actually really fun. Also learning tons of cool stuff you can do with @unity

i used Jev to classify a youtubers last 100 videos based on how likely it is to sell me something... it analyzed & assigned a sales intent score to each video within 12 seconds & cost about $0.02 i haven't done a deep dive into how accurate the score is yet, but from a quick glance it looks like a super promising classifier model

PythonでJevにプレイさせるSnake Game作った（AIにつくらせた）リアルタイムで操作するのが素晴らしい。赤は従来のアルゴリズムNPC（盤面全部みて計算してるので有利） https://t.co/gOy4kq2YXl

Made a wikiracer using jev. Go try it out https://t.co/qUoye0IDVH https://t.co/5F4rvqXwOw

Jev + SuperX = virality solved ✅ Every post gets 61 questions in ~1s for $0.0004 🤯 > fitted on 9,481 real posts from 207 creators > picks the viral post 2 in 3 times > never rewards reply bait So: write, score, rewrite, stop when it peaks. Free, no signup. try it below ↓ https://t.co/57KJBgkoiv

Jevとgpt-live-1を使ってECのリアルタイム接客デモ作りました。 会話途中でもユーザーの発話に合わせておすすめ商品を即座に出してくれるのはかなり体験良さそう。 あと今回のデモではちゃんと簡単にしか作ってないけど、対話内容に応じてアバターの表情を変化させるって芸当もJevならでは。 https://t.co/hi0RhtX27O

Jev by @typesafeai could be the pilot on your next flight. I've built a simulator where Jev has full control of the airplane. It takes off, follows waypoints, and lands safely. It has full access to flight telemetry, avoids mountains, etc. 🤯 https://t.co/G2xrcaYzGk

Jevで、会話をリアルタイムに観測するセンサーを試作しました。 発言のたびに ・探索 ↔ 収束 ・解消 ↔ 未決 ・未合意 ↔ 合意 を更新し、会議の状況を可視化します ユーザーインタビューのリアルタイム解析などにも使えそう。 https://t.co/cO21f4AK99

I gave 24 AI people a town. Then I flooded it. Each had their own memories, relationships, and limited sight. Jev chose their actions: escape, help a stranger, or look for family. 237 real API calls. Here’s what happened: https://t.co/xYcIn5e0RQ @typesafeai @CompleteSkeptic

i built a codebase classifier with Jev and this might be the solution to overengineered code that agents create what should I test Jev on next? https://t.co/40LgzIsxpo

i built computer use using @typesafeai ! it is 155x cheaper than opus 5, ~20x faster, and generalizes across OS's more on how it works in the vid & thread below: https://t.co/K0ZaRRnEX5