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this was never supposed to leave the studio group chats Jev doesn't generate images or write code. it picks. layout A or B, serif or sans, cut here or there. code does the drawing. that's why it never ships something half-broken. want a whole design system from one sentence?... -> jev-design: type "an 18th century printed book" and the dashboard becomes one a second or two later want full UI screens from a one-line prompt? -> jev-design-test: real shadcn screens in ~1-2 seconds, Jev never writes a line of JSX want Figma to follow plain sentences? -> jev-figma-design-plugin: Jev decides, code draws want a long video cut into shorts? -> jevcut: 62 clips out of a 97-minute podcast, about 3 cents of Jev per hour of video want a video editor with Jev inside? -> HyperEdit: FFMPEG + Remotion, powered by Jev the catch: Jev only chooses from options a human already built. no vocabulary, no design. and it's still behind a waitlist. the taste is yours. the thousand tiny choices don't have to be. bookmark this. pick one. ship something this week.show more

kiosa

5,772 subscribers

15,484 views • 1 day ago •via X (Twitter)

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11 Comments

sanzida19 hours ago

Okay, Jev. This "it picks" philosophy? That's the real magic. It's not about replacing human creativity, it's about accelerating it by removing decision fatigue.

Sophia b,1 day ago

so it's basically a design lead that learned to talk. routing layer with taste

Elias Andualem1 day ago

Another use case: choosing whether to correct a misheard word. I’m using this in Entune and just compared Jev, Perplexity, OpenAI and local Laya on the same dictation.

kiosa1 day ago

Good one

TimeFliesBuy1 day ago

@Bonzsol for reference i have seen a lot of these animations, wondering how real they are

Yuvraj Angad Singh1 day ago

picking a or b fast is the whole product, nothing else

7dim_1881 day ago

honestly the “Jev decides, code draws” part is kinda sick. feels like the right way to use AI without letting it freestyle everything 😂

kiosa1 day ago

Sick mate

wast31 day ago

how long would it take to make one just like this?

kiosa1 day ago

30-60 minutes

Âxel ⟢15 hours ago

It was never

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How does Jev work? Jev takes two things: your input and an output schema. The schema gives the structure of the answer you want. I send an email. My schema asks for two fields: is spam, and a category from marketing, finance, or spam. Jev returns: - is spam: 0.90 - category: spam That is a 90% chance of spam. Jev selects the category only from the list I give it. It writes no sentences. The 0.90 is a number object, so my code can use it immediately without extra processing. Jev shows no reasoning. You get the answer and nothing more, so some people do not trust it. Use Jev for choices your code must make fast and at low cost: spam or normal, buy or no buy, reply or escalate.

How does Jev work? Jev takes two things: your input and an output schema. The schema gives the structure of the answer you want. I send an email. My schema asks for two fields: is spam, and a category from marketing, finance, or spam. Jev returns: - is spam: 0.90 - category: spam That is a 90% chance of spam. Jev selects the category only from the list I give it. It writes no sentences. The 0.90 is a number object, so my code can use it immediately without extra processing. Jev shows no reasoning. You get the answer and nothing more, so some people do not trust it. Use Jev for choices your code must make fast and at low cost: spam or normal, buy or no buy, reply or escalate.

The Startup Ideas Podcast (SIP) 🧃

12,032 views • 20 days ago

Jev dropped barely a week ago and traders are already doing some wild sh*t with it. live order books. real-time signals. trading bots. entire AI hedge funds. here's what happened: > jev-trader · every ~0.3s asks Jev “buy or sell?” on Monad and trades > jev-trade · reads Hyperliquid order book -> Jev picks -> code sends the order > beebots · 3 OKX trading “bees”; every choice is Jev (paper trading by default) > QuantDinger · full AI trading OS; optional Jev gate = “should we trade at all?” > ai-hedge-fund · multi-agent “fund” with a Jev adapter for fast yes/no calls and that’s the funny part: Jev isn’t here to think. it’s here to make the call. the market moves -> Jev picks LONG / SHORT / HOLD -> code executes. no essays. no chain of thought. no expensive model debating every tiny market move. big models figure out the strategy. Jev handles the split-second calls. code makes it real.

Jev dropped barely a week ago and traders are already doing some wild sh*t with it. live order books. real-time signals. trading bots. entire AI hedge funds. here's what happened: > jev-trader · every ~0.3s asks Jev “buy or sell?” on Monad and trades > jev-trade · reads Hyperliquid order book -> Jev picks -> code sends the order > beebots · 3 OKX trading “bees”; every choice is Jev (paper trading by default) > QuantDinger · full AI trading OS; optional Jev gate = “should we trade at all?” > ai-hedge-fund · multi-agent “fund” with a Jev adapter for fast yes/no calls and that’s the funny part: Jev isn’t here to think. it’s here to make the call. the market moves -> Jev picks LONG / SHORT / HOLD -> code executes. no essays. no chain of thought. no expensive model debating every tiny market move. big models figure out the strategy. Jev handles the split-second calls. code makes it real.

kiosa

108,417 views • 8 days ago

this is f*cking gold 20 GitHub repos with 500K+ combined stars that will level up your JEV workflow AGENTS > jev-ultrafast: Jev picks every click and DOM target, a small LLM only types > hermes-jev-skills: routing, memory, compaction and skill picks in one pack > typesafe-computer-use: OCR reads your Mac screen, Jev picks the next click MEMORY > fast-jev-compaction: scores every tool call keep, truncate or drop instead of summarizing > jevmem: project memory for Claude Code, Cursor and Codex, updated every turn > jev-second-brain: your Obsidian vault, Jev judges which notes duplicate, revise or contradict SAFETY > jev-guard: a gate before every tool call, Jev scores the risk, you set allow, ask or deny TOOLS > skills: the official TypeSafe skill for Claude Code and Codex > system-one-adapter-python: dry-run your questions on an ordinary LLM before you burn a Jev key > jev-mcp: claim checks, screening and ranking as MCP tools > typesafe-mcp: plug Jev into any MCP client > json-render: Vercel's generative UI, where Jev picks the components OPEN MODELS > SemIf-OpenJev: semantic ifs from frozen open models kev: Jev-like models on Qwen that run on your MacBook > laya-mlx: the Laya decision engine on Apple silicon > clm: an open System One model with Choice, Noul and Score > jevlike: train your own Jev-like model TRADING > jev-trader: one buy or sell decision per Monad block START HERE > awesome-jev: the biggest map of everything built on Jev > awesome-jev-by-typesafe: use cases, patterns and starter code bookmark it before your next build

this is f*cking gold 20 GitHub repos with 500K+ combined stars that will level up your JEV workflow AGENTS > jev-ultrafast: Jev picks every click and DOM target, a small LLM only types > hermes-jev-skills: routing, memory, compaction and skill picks in one pack > typesafe-computer-use: OCR reads your Mac screen, Jev picks the next click MEMORY > fast-jev-compaction: scores every tool call keep, truncate or drop instead of summarizing > jevmem: project memory for Claude Code, Cursor and Codex, updated every turn > jev-second-brain: your Obsidian vault, Jev judges which notes duplicate, revise or contradict SAFETY > jev-guard: a gate before every tool call, Jev scores the risk, you set allow, ask or deny TOOLS > skills: the official TypeSafe skill for Claude Code and Codex > system-one-adapter-python: dry-run your questions on an ordinary LLM before you burn a Jev key > jev-mcp: claim checks, screening and ranking as MCP tools > typesafe-mcp: plug Jev into any MCP client > json-render: Vercel's generative UI, where Jev picks the components OPEN MODELS > SemIf-OpenJev: semantic ifs from frozen open models kev: Jev-like models on Qwen that run on your MacBook > laya-mlx: the Laya decision engine on Apple silicon > clm: an open System One model with Choice, Noul and Score > jevlike: train your own Jev-like model TRADING > jev-trader: one buy or sell decision per Monad block START HERE > awesome-jev: the biggest map of everything built on Jev > awesome-jev-by-typesafe: use cases, patterns and starter code bookmark it before your next build

NO1ennn

18,445 views • 11 days ago

Everyone is talking about JEV. Almost nobody knows how to actually use it. These 10 GitHub repos fix that. 1. browser-use/jev-ultrafast (~16.6k⭐) Jev for browser agents: pick the next action without another expensive LLM call. 2. tamaratran/fast-jev-compaction (~6.5k⭐) Uses Jev to decide what context still matters and what can be dropped. 3. TheoLeeCJ/SemIf (~4k⭐) Open-source Jev-style decision making you can run locally. 4. jarrodwatts/jev-trader (~2.1k⭐) Real-time trading loop where Jev decides buy, sell or wait. 5. kerpopule/hermes-jev-skills (~670⭐) Jev routing, memory, compaction and skill selection for AI agents. 6. devagrawal09/jev-review (~570⭐) Code review powered by Jev decisions instead of one giant prompt. 7. thruwire/foreman (~520⭐) Jev as a supervisor for coding agents: continue, retry, verify or stop. 8. superagents-lab/jev-search (~400⭐) Jev decides where and how an agent should search. 9. droidrun/mobile-jev (~350⭐) Jev for Android agents choosing the next app action. 10. gargpratyush/jev-router (~340⭐) Routes agent tasks to the right model with Jev. After looking through these, the pattern is pretty clear: LLMs generate. Agents execute. JEV decides. That decision layer is what most agent stacks are still missing. Save this if you want to integrate Jev into your workflow👇

Everyone is talking about JEV. Almost nobody knows how to actually use it. These 10 GitHub repos fix that. 1. browser-use/jev-ultrafast (~16.6k⭐) Jev for browser agents: pick the next action without another expensive LLM call. 2. tamaratran/fast-jev-compaction (~6.5k⭐) Uses Jev to decide what context still matters and what can be dropped. 3. TheoLeeCJ/SemIf (~4k⭐) Open-source Jev-style decision making you can run locally. 4. jarrodwatts/jev-trader (~2.1k⭐) Real-time trading loop where Jev decides buy, sell or wait. 5. kerpopule/hermes-jev-skills (~670⭐) Jev routing, memory, compaction and skill selection for AI agents. 6. devagrawal09/jev-review (~570⭐) Code review powered by Jev decisions instead of one giant prompt. 7. thruwire/foreman (~520⭐) Jev as a supervisor for coding agents: continue, retry, verify or stop. 8. superagents-lab/jev-search (~400⭐) Jev decides where and how an agent should search. 9. droidrun/mobile-jev (~350⭐) Jev for Android agents choosing the next app action. 10. gargpratyush/jev-router (~340⭐) Routes agent tasks to the right model with Jev. After looking through these, the pattern is pretty clear: LLMs generate. Agents execute. JEV decides. That decision layer is what most agent stacks are still missing. Save this if you want to integrate Jev into your workflow👇

unicode

20,745 views • 16 days ago

this is f*cking gold 12 open-source repos that plug Jev into real AI work, 550.7k stars combined Jev decides, your LLM writes. these repos are where that split already runs: agents > browser-use/jev-ultrafast (~20.3k): Jev picks the next action + DOM element, a small LLM only types. Zürich to London flights in ~7s > awlevin/typesafe-computer-use (~978): macOS computer use, OCR reads the screen, Jev picks the next click local decision models > jaredpalmer/kev (~7.1k): Jev-like models on Qwen, same /v1/systemone wire format > mizorewww/laya-mlx (~6.4k): Laya, the main open Jev-style engine, running on Apple silicon > TheoLeeCJ/SemIf-OpenJev (~4.3k): local semantic ifs from frozen open models, not a TypeSafe project > contrastive-lm/clm (~1.3k): open System One model with a Choice / Noul / Score API > vinnylarouge/jevlike (~1.3k): community trainer and tooling for your own Jev-like model context + skills > tamaratran/fast-jev-compaction (~6.9k): Claude Code plugin, Jev keeps, drops or truncates tool results instead of summarizing context > typesafe-ai/skills (~2.2k): official TypeSafe skill for Claude Code and Codex trading > jarrodwatts/jev-trader (~2.4k): one Jev buy/sell decision per Monad block catalogs > yibie/awesome-jev (~1.7k): the biggest map of Jev projects and discussions > Anil-matcha/awesome-jev-by-typesafe (~851): use cases, patterns and starter code start with jev-ultrafast

this is f*cking gold 12 open-source repos that plug Jev into real AI work, 550.7k stars combined Jev decides, your LLM writes. these repos are where that split already runs: agents > browser-use/jev-ultrafast (~20.3k): Jev picks the next action + DOM element, a small LLM only types. Zürich to London flights in ~7s > awlevin/typesafe-computer-use (~978): macOS computer use, OCR reads the screen, Jev picks the next click local decision models > jaredpalmer/kev (~7.1k): Jev-like models on Qwen, same /v1/systemone wire format > mizorewww/laya-mlx (~6.4k): Laya, the main open Jev-style engine, running on Apple silicon > TheoLeeCJ/SemIf-OpenJev (~4.3k): local semantic ifs from frozen open models, not a TypeSafe project > contrastive-lm/clm (~1.3k): open System One model with a Choice / Noul / Score API > vinnylarouge/jevlike (~1.3k): community trainer and tooling for your own Jev-like model context + skills > tamaratran/fast-jev-compaction (~6.9k): Claude Code plugin, Jev keeps, drops or truncates tool results instead of summarizing context > typesafe-ai/skills (~2.2k): official TypeSafe skill for Claude Code and Codex trading > jarrodwatts/jev-trader (~2.4k): one Jev buy/sell decision per Monad block catalogs > yibie/awesome-jev (~1.7k): the biggest map of Jev projects and discussions > Anil-matcha/awesome-jev-by-typesafe (~851): use cases, patterns and starter code start with jev-ultrafast

NO1ennn

42,546 views • 13 days ago

Jev has been blowing up lately. If you've got the Jev API but don't know how to play around with it yet, you can just copy this checklist. 1. jev-ultrafast A high-speed browser Agent built with Browser Use. Jev only judges "what to do, which element to click" at each step, and only calls the small model when typing is needed. Searching for a flight on Google Flights takes about 7 seconds. 2. fast-jev-compaction Context compression for Claude Code. Before each tool call, have Jev judge if there's anything still useful; delete the useless stuff, and keep the original text without rewriting it. 3. json-render Vercel Labs' generative UI framework. In experiments, Jev doesn't write JSON token by token; it just handles selecting components, properties, and layouts. 4. typesafe-mcp Best for people who just got the API. Plug Jev into Claude Code, Claude Desktop, Codex, and Pi, and do Choice / Score / Noul anytime. 5. jev-mcp Ready-made Agent judgment toolkit: fact-checking, content screening, semantic ranking, classification, and information extraction. 6. SemDecide Turn Jev into a command-line tool. Directly classify, score, and filter in the Shell—great for hooking up to crawlers, CI, and data pipelines. 7. jev-codex-router First have Jev judge how hard this round of programming tasks is, then decide the model tier, reasoning depth, and speed mode. 8. Winnow Context garbage collection for Claude Code. When Read / Bash / Grep spits out a ton of stuff, Jev first judges which parts are really relevant to the current task. 9. jev-review Before code review, run it through Jev first to pick out high-risk changes, then hand them off to a pricier big model or a human. Comes with a local dashboard. 10. Blink Use Jev as a code repository navigator. At each directory level, judge which files are most relevant to the current issue, then keep digging down. Copy these complete Jev blueprints - then read full Jev setup below ↓ ↓

Jev has been blowing up lately. If you've got the Jev API but don't know how to play around with it yet, you can just copy this checklist. 1. jev-ultrafast A high-speed browser Agent built with Browser Use. Jev only judges "what to do, which element to click" at each step, and only calls the small model when typing is needed. Searching for a flight on Google Flights takes about 7 seconds. 2. fast-jev-compaction Context compression for Claude Code. Before each tool call, have Jev judge if there's anything still useful; delete the useless stuff, and keep the original text without rewriting it. 3. json-render Vercel Labs' generative UI framework. In experiments, Jev doesn't write JSON token by token; it just handles selecting components, properties, and layouts. 4. typesafe-mcp Best for people who just got the API. Plug Jev into Claude Code, Claude Desktop, Codex, and Pi, and do Choice / Score / Noul anytime. 5. jev-mcp Ready-made Agent judgment toolkit: fact-checking, content screening, semantic ranking, classification, and information extraction. 6. SemDecide Turn Jev into a command-line tool. Directly classify, score, and filter in the Shell—great for hooking up to crawlers, CI, and data pipelines. 7. jev-codex-router First have Jev judge how hard this round of programming tasks is, then decide the model tier, reasoning depth, and speed mode. 8. Winnow Context garbage collection for Claude Code. When Read / Bash / Grep spits out a ton of stuff, Jev first judges which parts are really relevant to the current task. 9. jev-review Before code review, run it through Jev first to pick out high-risk changes, then hand them off to a pricier big model or a human. Comes with a local dashboard. 10. Blink Use Jev as a code repository navigator. At each directory level, judge which files are most relevant to the current issue, then keep digging down. Copy these complete Jev blueprints - then read full Jev setup below ↓ ↓

rody

202,492 views • 18 days ago

CLAUDE + JEV ENGINEERING = THE HARNESS SKILL THAT GETS AI ENGINEERS PROMOTED IN 2026 1,000 decisions on a cold frontier model cost $605 the same 1,000 through this harness cost $0.17 the core idea: Claude proposes, Jev answers, code decides every step leaves a receipt the loop: > propose - Claude writes plans and patches, and decides nothing > filter - code drops the routes your machine can't run before Jev ever sees them > answer - Jev picks from code's menu with a probability, or abstains > re-check - code checks the pick against live state. stale goes to fallback > act - the tool runs through the normal approval path > receipt - every step logged and replayable against a new policy the numbers: > 0.2s median per call > ~$0.0002 per desktop step > 49 of 49 WebMCP tasks passed the key insight: "I don't know" is a real answer here when Jev is only 38% sure, a fallback written in advance fires instead of a guess worth stealing even if you never touch Jev: > one decision the harness can check > the exact options code prepared > a defined path for when the model isn't sure > a way to measure what actually happened the engineer who can walk into a meeting and turn a $605 line into 17 cents is the one who gets asked to design the next system the model got the words, Jev got the choices, and code kept the final say

CLAUDE + JEV ENGINEERING = THE HARNESS SKILL THAT GETS AI ENGINEERS PROMOTED IN 2026 1,000 decisions on a cold frontier model cost $605 the same 1,000 through this harness cost $0.17 the core idea: Claude proposes, Jev answers, code decides every step leaves a receipt the loop: > propose - Claude writes plans and patches, and decides nothing > filter - code drops the routes your machine can't run before Jev ever sees them > answer - Jev picks from code's menu with a probability, or abstains > re-check - code checks the pick against live state. stale goes to fallback > act - the tool runs through the normal approval path > receipt - every step logged and replayable against a new policy the numbers: > 0.2s median per call > ~$0.0002 per desktop step > 49 of 49 WebMCP tasks passed the key insight: "I don't know" is a real answer here when Jev is only 38% sure, a fallback written in advance fires instead of a guess worth stealing even if you never touch Jev: > one decision the harness can check > the exact options code prepared > a defined path for when the model isn't sure > a way to measure what actually happened the engineer who can walk into a meeting and turn a $605 line into 17 cents is the one who gets asked to design the next system the model got the words, Jev got the choices, and code kept the final say

Mr. Buzzoni

32,459 views • 9 days ago

Jev has been exploding across GitHub since launch, here's what people have already built with it if you have API access and don't know where to start, copy this: jev-trader - real trading bot placing live limit orders on Monad every 300ms block, judged by Jev alone. 1,911 stars jev-ultrafast - browser agent that picks every click itself, only calling a text model when it actually needs to type something. 16,758 stars jev-doom-agent - real Chocolate Doom compiled to WebAssembly, two engines running the same map, Jev picking the tactical macro every frame jev-t-rex-runner - the Chrome dinosaur game you've procrastinated with a hundred times, now played entirely by Jev picking jump, duck, or keep running typesafe-chess - Jev vs a real search engine, two games, colors swapped. the search won both, but overruled Jev's first instinct on roughly half the moves jev-drone - a simulated quadrotor clears a five-station obstacle course by camera alone, Jev judging the situation twice a second tax-doc-classifier - sorts real IRS tax forms with 100% strict accuracy across 261 forms, at roughly $0.001 a page killmyidea - describe your startup idea, Jev scores it from every angle, then hands back kill, fix, or ship jev-curate - streams Parquet and JSONL rows through typed judgments at 1,500+ rows a second, keeping only what clears the bar pg-jev - a PostgreSQL extension that lets you ask your own database tables plain-English questions and get a real answer back none of these ten generate a single word of text. every one of them returns a number against an answer someone already defined full setup below, then run the three-question test from the article before you build an eleventh

Jev has been exploding across GitHub since launch, here's what people have already built with it if you have API access and don't know where to start, copy this: jev-trader - real trading bot placing live limit orders on Monad every 300ms block, judged by Jev alone. 1,911 stars jev-ultrafast - browser agent that picks every click itself, only calling a text model when it actually needs to type something. 16,758 stars jev-doom-agent - real Chocolate Doom compiled to WebAssembly, two engines running the same map, Jev picking the tactical macro every frame jev-t-rex-runner - the Chrome dinosaur game you've procrastinated with a hundred times, now played entirely by Jev picking jump, duck, or keep running typesafe-chess - Jev vs a real search engine, two games, colors swapped. the search won both, but overruled Jev's first instinct on roughly half the moves jev-drone - a simulated quadrotor clears a five-station obstacle course by camera alone, Jev judging the situation twice a second tax-doc-classifier - sorts real IRS tax forms with 100% strict accuracy across 261 forms, at roughly $0.001 a page killmyidea - describe your startup idea, Jev scores it from every angle, then hands back kill, fix, or ship jev-curate - streams Parquet and JSONL rows through typed judgments at 1,500+ rows a second, keeping only what clears the bar pg-jev - a PostgreSQL extension that lets you ask your own database tables plain-English questions and get a real answer back none of these ten generate a single word of text. every one of them returns a number against an answer someone already defined full setup below, then run the three-question test from the article before you build an eleventh

Ryven

276,722 views • 16 days ago

Jev has been exploding in popularity recently. If you already have access to the Jev API but aren't sure how to start experimenting with it, just copy this checklist: 1. jev-ultrafast Browser Use's fastest agent. Jev decides the next action and which element to click, and a language model is only called when text has to be typed. 2. typesafe-mario Jev plays Super Mario Bros. from structured emulator state, choosing every action from features pulled out of the game. 3. jev-plays-pokemon Reads Pokémon Red's game state as text, answers typed questions each turn, and lets plain code turn the answers into moves. 4. jev-drone A camera-only autonomous drone in MuJoCo with a Jev judgment model sitting in the control loop at 2.5 Hz. 5. robo-harness A real SO-101 robot arm workbench where Jev picks bounded joint steps from typed candidate actions under a spend budget. 6. fast-jev-compaction Claude Code plugin that replaces the compaction summary with Jev decisions, scoring every tool call for whether it is still needed. 7. jev-claude Routes Claude Code's own judgment calls through Jev: typed choices with probabilities at plan approval, on questions, and before risky commands. 8. is-malicious Supply-chain check before you run anything: Jev Noul checks over source and build files, returning the implicated files and lines. 9. sqlite-jev Jev inside SQL. Noul, Choice and Score judgments exposed as SQLite functions, with confidence on every row. 10. jevinci Paints images by having Jev predict every pixel's colour in parallel, with confidence deciding how wide each stroke is drawn. Copy these complete Jev blueprints - then read full Jev setup below ↓ ↓

Jev has been exploding in popularity recently. If you already have access to the Jev API but aren't sure how to start experimenting with it, just copy this checklist: 1. jev-ultrafast Browser Use's fastest agent. Jev decides the next action and which element to click, and a language model is only called when text has to be typed. 2. typesafe-mario Jev plays Super Mario Bros. from structured emulator state, choosing every action from features pulled out of the game. 3. jev-plays-pokemon Reads Pokémon Red's game state as text, answers typed questions each turn, and lets plain code turn the answers into moves. 4. jev-drone A camera-only autonomous drone in MuJoCo with a Jev judgment model sitting in the control loop at 2.5 Hz. 5. robo-harness A real SO-101 robot arm workbench where Jev picks bounded joint steps from typed candidate actions under a spend budget. 6. fast-jev-compaction Claude Code plugin that replaces the compaction summary with Jev decisions, scoring every tool call for whether it is still needed. 7. jev-claude Routes Claude Code's own judgment calls through Jev: typed choices with probabilities at plan approval, on questions, and before risky commands. 8. is-malicious Supply-chain check before you run anything: Jev Noul checks over source and build files, returning the implicated files and lines. 9. sqlite-jev Jev inside SQL. Noul, Choice and Score judgments exposed as SQLite functions, with confidence on every row. 10. jevinci Paints images by having Jev predict every pixel's colour in parallel, with confidence deciding how wide each stroke is drawn. Copy these complete Jev blueprints - then read full Jev setup below ↓ ↓

Hanako

29,894 views • 14 days ago

JEV + Opus 5.5 is insane for live design... I built a live site redesigner with JEV + Opus 5.5 Paste any link → press Start → scroll, and Jev + Opus 5.5 rebuild every section of the site in front of you Full production ship in 20 seconds: 1. IntersectionObserver fires when a section is 30%+ in the viewport 2. Jev returns one typed decision in ~0.1s: { layout, copy, drop, type, palette, p } 3. Opus 5.5 writes the component (TSX) + a CSS patch for the chosen style 4. The new section wipes in with clip-path, the old one blurs out 5. Next section enters the queue, one at a time, no race conditions Output: 8 sections of a 2015 hosting site rebuilt in ~20s, streamed line by line in the terminal 3 styles, one renderer: orthographic globe + lambert shading → ASCII / 2-color halftone / ink stipple Scroll yourself and it redesigns whatever you land on Jev decides fast, Opus designs it

JEV + Opus 5.5 is insane for live design... I built a live site redesigner with JEV + Opus 5.5 Paste any link → press Start → scroll, and Jev + Opus 5.5 rebuild every section of the site in front of you Full production ship in 20 seconds: 1. IntersectionObserver fires when a section is 30%+ in the viewport 2. Jev returns one typed decision in ~0.1s: { layout, copy, drop, type, palette, p } 3. Opus 5.5 writes the component (TSX) + a CSS patch for the chosen style 4. The new section wipes in with clip-path, the old one blurs out 5. Next section enters the queue, one at a time, no race conditions Output: 8 sections of a 2015 hosting site rebuilt in ~20s, streamed line by line in the terminal 3 styles, one renderer: orthographic globe + lambert shading → ASCII / 2-color halftone / ink stipple Scroll yourself and it redesigns whatever you land on Jev decides fast, Opus designs it

Movez

106,833 views • 15 days ago

Jev Founder, Diogo Almeida (ex-OpenAI): "The next era is not the Claude Code or Codex era, they are still part of the assistance era with human in the loop - JEV is what comes next for LLMs x200 faster, x400 cheaper, 0 hallucination, no human in the loop - that's JEV, this is how LLMs will look like" in 36-minute tech talk, Jev Founder explained why RLHF isn't a thing anymore and how modern LLMs will be built this talk is worth more than a Stanford Machine Learning degree watch today no matter what, then learn how to become a Jev Engineer in the article below

Jev Founder, Diogo Almeida (ex-OpenAI): "The next era is not the Claude Code or Codex era, they are still part of the assistance era with human in the loop - JEV is what comes next for LLMs x200 faster, x400 cheaper, 0 hallucination, no human in the loop - that's JEV, this is how LLMs will look like" in 36-minute tech talk, Jev Founder explained why RLHF isn't a thing anymore and how modern LLMs will be built this talk is worth more than a Stanford Machine Learning degree watch today no matter what, then learn how to become a Jev Engineer in the article below

Codez

460,702 views • 20 days ago

this is unreal f*cking gold for Jev builders 20 repos people are building on Jev right now. browser agents, context tools, trading bots, even a drone 1. JEV-Ultrafast - a fast browser agent ↳ 2. Fast-JEV-Compaction - context compression ↳ 3. JSON-Render - generative UI ↳ 4. Typesafe-MCP - use Jev with any client ↳ 5. JEV-MCP - a judgment toolkit ↳ 6. Semdecide - a classifier that lives in your CLI ↳ 7. JEV-Codex-Router - routes each task to the right model ↳ 8. Winnow - garbage collection for your context ↳ 9. JEV-Review - code review triage ↳ 10. Blink - a repo navigator ↳ 11. Agent-Desktop - desktop automation ↳ 12. Typesafe-Mario - an agent that plays Super Mario ↳ 13. JEV-Drone - drone control ↳ 14. OneVOneJev - a browser FPS ↳ 15. JEV-Trader - HFT market making ↳ 16. Prism - liquidity signal detection ↳ 17. Neo4Jev - knowledge graph traversal ↳ 18. JEV-Curate - training data screening ↳ 19. Canny - checks whether a task was actually completed ↳ 20. KillMyIdea - scores startup ideas before you build them ↳ pick by what you do: > coding -> JEV-Review, Blink, Canny, JEV-Codex-Router > context -> Fast-JEV-Compaction, Winnow > automation -> JEV-Ultrafast, Agent-Desktop > clients and tools -> Typesafe-MCP, JEV-MCP, Semdecide > UI -> JSON-Render > trading -> JEV-Trader, Prism > data -> Neo4Jev, JEV-Curate > founders -> KillMyIdea > just for fun -> Typesafe-Mario, OneVOneJev, JEV-Drone grab the one closest to your job and ship something on top of it this week

this is unreal f*cking gold for Jev builders 20 repos people are building on Jev right now. browser agents, context tools, trading bots, even a drone 1. JEV-Ultrafast - a fast browser agent ↳ 2. Fast-JEV-Compaction - context compression ↳ 3. JSON-Render - generative UI ↳ 4. Typesafe-MCP - use Jev with any client ↳ 5. JEV-MCP - a judgment toolkit ↳ 6. Semdecide - a classifier that lives in your CLI ↳ 7. JEV-Codex-Router - routes each task to the right model ↳ 8. Winnow - garbage collection for your context ↳ 9. JEV-Review - code review triage ↳ 10. Blink - a repo navigator ↳ 11. Agent-Desktop - desktop automation ↳ 12. Typesafe-Mario - an agent that plays Super Mario ↳ 13. JEV-Drone - drone control ↳ 14. OneVOneJev - a browser FPS ↳ 15. JEV-Trader - HFT market making ↳ 16. Prism - liquidity signal detection ↳ 17. Neo4Jev - knowledge graph traversal ↳ 18. JEV-Curate - training data screening ↳ 19. Canny - checks whether a task was actually completed ↳ 20. KillMyIdea - scores startup ideas before you build them ↳ pick by what you do: > coding -> JEV-Review, Blink, Canny, JEV-Codex-Router > context -> Fast-JEV-Compaction, Winnow > automation -> JEV-Ultrafast, Agent-Desktop > clients and tools -> Typesafe-MCP, JEV-MCP, Semdecide > UI -> JSON-Render > trading -> JEV-Trader, Prism > data -> Neo4Jev, JEV-Curate > founders -> KillMyIdea > just for fun -> Typesafe-Mario, OneVOneJev, JEV-Drone grab the one closest to your job and ship something on top of it this week

Mr. Buzzoni

29,333 views • 14 days ago

Jev + Claude Opus 5.5... i can't understand why everyone isn't wiring this up yet the forks alone drop from about $110 a day to $4 once jev takes them over. right now it's the best way i know to run opus what jev handles: -> scores which project notes matter before the context even loads -> hands the easy steps to a faster worker -> picks a recovery path when a tool fails, so nothing retries blind -> runs the focused checks before the full test suite opus does the hard reasoning. jev chooses from options the harness already prepared and validated that's jev engineering in one line: the expensive model thinks, the cheap one decides $106 a day back on the same work is a number your manager remembers read the paper, then the full jev guide below

Jev + Claude Opus 5.5... i can't understand why everyone isn't wiring this up yet the forks alone drop from about $110 a day to $4 once jev takes them over. right now it's the best way i know to run opus what jev handles: -> scores which project notes matter before the context even loads -> hands the easy steps to a faster worker -> picks a recovery path when a tool fails, so nothing retries blind -> runs the focused checks before the full test suite opus does the hard reasoning. jev chooses from options the harness already prepared and validated that's jev engineering in one line: the expensive model thinks, the cheap one decides $106 a day back on the same work is a number your manager remembers read the paper, then the full jev guide below

Annatar.md

130,171 views • 8 days ago

this is pure f*cking gold for anyone running coding agents Jev founder, Diogo Almeida, wrote a guide on building a Jev harness the expensive model only writes the code. every fork around it goes to Jev the bill: > 6,000 forks a day on a frontier model: $180 > the same 6,000 forks on Jev: $0.25 > the whole harness, patches included: about $24 99 percent of what's left is the code itself, which is the only part you should be paying for what's inside: > the turn snapshot, five hooks, the cascade > thresholds read off your own receipts > the one rule a model never gets a vote on one evening of setup and your agent stops paying frontier prices to answer yes or no ↓

this is pure f*cking gold for anyone running coding agents Jev founder, Diogo Almeida, wrote a guide on building a Jev harness the expensive model only writes the code. every fork around it goes to Jev the bill: > 6,000 forks a day on a frontier model: $180 > the same 6,000 forks on Jev: $0.25 > the whole harness, patches included: about $24 99 percent of what's left is the code itself, which is the only part you should be paying for what's inside: > the turn snapshot, five hooks, the cascade > thresholds read off your own receipts > the one rule a model never gets a vote on one evening of setup and your agent stops paying frontier prices to answer yes or no ↓

Hanako

20,837 views • 12 days ago

Jev is incredibly good! If you haven't heard, Jev is a new "System One" model optimized for decision-making. For example, you can give it a set of possible choices, and Jev will classify the input text based on those choices, including a confidence score for each. Best of all: Jev is really fast and cheap, so you can use it in all sorts of applications. The first thing I built with it is a classifier to pick the hotels I want to visit. I use Apify to collect thousands of reviews, then classify them with Jev based on specific criteria I care about. You just couldn't do this reliably, but now you can. Link to the repository:

Jev is incredibly good! If you haven't heard, Jev is a new "System One" model optimized for decision-making. For example, you can give it a set of possible choices, and Jev will classify the input text based on those choices, including a confidence score for each. Best of all: Jev is really fast and cheap, so you can use it in all sorts of applications. The first thing I built with it is a classifier to pick the hotels I want to visit. I use Apify to collect thousands of reviews, then classify them with Jev based on specific criteria I care about. You just couldn't do this reliably, but now you can. Link to the repository:

Santiago

17,898 views • 11 days ago

this is pure f*cking treasure 15 GitHub repos with 116K combined stars where a model that can't write a single word makes the calls browsers. phones. cars. Minecraft. trading. agents that die if they can't pay PLUG IN -> give any agent a decision brain 01 litellm · Jev behind one proxy > 02 vercel ai sdk · experimental_evaluate > 03 pydantic-ai · TypeSafeModel > ACT -> Jev picks every move 04 jev-ultrafast · Google Flights in 7.1s > 05 mobile-jev · real Android, 9 actions in ~21s > 06 jev-voice-browser · ~300ms per spoken word > 07 jevpilot · steers up to 4x a second > 08 minecraft-agent · dragon down in 8:43, 131 Jev decisions > SURVIVE -> every decision comes with a bill 09 automaton · "if it cannot pay, it stops existing" > 10 jev-trader · one decision every ~300ms block > THINK LESS -> pay for a thought only when it's worth it 11 wakegate · the LLM sleeps until Jev says wake > 12 fast-jev-compaction · keeps or drops, rewrites nothing > 13 jev-pruner · 76K-char log -> 4K, the error line stays > 14 unclutter · hides the ads, reuses rules per site > DOUBT -> check if its "I'm sure" is true 15 Jev-Calibration · calibration error 0.117 -> 0.008 > the loop: state comes in -> Jev picks -> the big model only when it's worth it -> confidence check -> code executes -> the bill gets paid none of them need Jev to write a single word save this, then read why the smartest brain goes broke first

this is pure f*cking treasure 15 GitHub repos with 116K combined stars where a model that can't write a single word makes the calls browsers. phones. cars. Minecraft. trading. agents that die if they can't pay PLUG IN -> give any agent a decision brain 01 litellm · Jev behind one proxy > 02 vercel ai sdk · experimental_evaluate > 03 pydantic-ai · TypeSafeModel > ACT -> Jev picks every move 04 jev-ultrafast · Google Flights in 7.1s > 05 mobile-jev · real Android, 9 actions in ~21s > 06 jev-voice-browser · ~300ms per spoken word > 07 jevpilot · steers up to 4x a second > 08 minecraft-agent · dragon down in 8:43, 131 Jev decisions > SURVIVE -> every decision comes with a bill 09 automaton · "if it cannot pay, it stops existing" > 10 jev-trader · one decision every ~300ms block > THINK LESS -> pay for a thought only when it's worth it 11 wakegate · the LLM sleeps until Jev says wake > 12 fast-jev-compaction · keeps or drops, rewrites nothing > 13 jev-pruner · 76K-char log -> 4K, the error line stays > 14 unclutter · hides the ads, reuses rules per site > DOUBT -> check if its "I'm sure" is true 15 Jev-Calibration · calibration error 0.117 -> 0.008 > the loop: state comes in -> Jev picks -> the big model only when it's worth it -> confidence check -> code executes -> the bill gets paid none of them need Jev to write a single word save this, then read why the smartest brain goes broke first

Paone

32,087 views • 13 days ago

10 Jev use cases a marketer can see: 1. Lead scoring - You get 100 new leads overnight. Jev can score which ones are most likely to buy. Sales gets the best ones first. 2. Email prioritization - Drop hundreds of emails into it. Jev can score priority, spam, category, and reply probability. 3. Support routing - A client reports a billing issue, another one has an API problem. Jev can instantly decide where each ticket should go. 4. Customer intent - A user visits pricing three times this week. Jev can score how likely they are to upgrade. 5. Marketplace matching - Someone explains exactly what service they need. Jev can score which provider is the closest match. 6. Lead qualification - A prospect fills out your website form. Jev can decide between sales, self-serve, or nurture. 7. Content clipping- Give it a 60-minute podcast transcript. Jev can score the moments most worth clipping. 8. Browser tasks - Tell an agent to find the right hotel. Jev can help choose the best one in 8 seconds. 9. Human vs AI routing - Jev can decide whether it goes to AI or a human. 10. Workflow decisions - Most workflows eventually hit the same question: What should happen next? That's probably the best place to use Jev.

10 Jev use cases a marketer can see: 1. Lead scoring - You get 100 new leads overnight. Jev can score which ones are most likely to buy. Sales gets the best ones first. 2. Email prioritization - Drop hundreds of emails into it. Jev can score priority, spam, category, and reply probability. 3. Support routing - A client reports a billing issue, another one has an API problem. Jev can instantly decide where each ticket should go. 4. Customer intent - A user visits pricing three times this week. Jev can score how likely they are to upgrade. 5. Marketplace matching - Someone explains exactly what service they need. Jev can score which provider is the closest match. 6. Lead qualification - A prospect fills out your website form. Jev can decide between sales, self-serve, or nurture. 7. Content clipping- Give it a 60-minute podcast transcript. Jev can score the moments most worth clipping. 8. Browser tasks - Tell an agent to find the right hotel. Jev can help choose the best one in 8 seconds. 9. Human vs AI routing - Jev can decide whether it goes to AI or a human. 10. Workflow decisions - Most workflows eventually hit the same question: What should happen next? That's probably the best place to use Jev.

Yum⋆₊˚

130,108 views • 20 days ago

this is unreal f*cking gold for Jev builders 20 repos people are building on Jev right now. browser agents, context tools, trading bots, even a drone 1. JEV-Ultrafast - a browser agent built for speed ↳ 2. Fast-JEV-Compaction - squeezes your context down ↳ 3. JSON-Render - UI generated on the fly ↳ 4. Typesafe-MCP - plugs Jev into any client ↳ 5. JEV-MCP - a toolkit for judgment calls ↳ 6. Semdecide - a classifier right in your terminal ↳ 7. JEV-Codex-Router - sends every task to the model that fits it ↳ 8. Winnow - clears the junk out of your context ↳ 9. JEV-Review - sorts code reviews by what needs eyes first ↳ 10. Blink - finds your way around any repo ↳ 11. Agent-Desktop - runs your desktop for you ↳ 12. Typesafe-Mario - an agent playing Super Mario ↳ 13. JEV-Drone - flies a drone ↳ 14. OneVOneJev - a shooter in your browser ↳ 15. JEV-Trader - high-frequency market making ↳ 16. Prism - spots liquidity signals ↳ 17. Neo4Jev - walks a knowledge graph ↳ 18. JEV-Curate - screens training data ↳ 19. Canny - confirms a task is really finished ↳ 20. KillMyIdea - scores a startup idea before you sink time into it ↳ start where your work is: > coding -> JEV-Review, Blink, Canny, JEV-Codex-Router > context -> Fast-JEV-Compaction, Winnow > automation -> JEV-Ultrafast, Agent-Desktop > clients and tools -> Typesafe-MCP, JEV-MCP, Semdecide > UI -> JSON-Render > trading -> JEV-Trader, Prism > data -> Neo4Jev, JEV-Curate > founders -> KillMyIdea > for fun -> Typesafe-Mario, OneVOneJev, JEV-Drone pick one, build on it this week, and you'll be the person on your team who actually knows Jev engineering when it gets asked for

this is unreal f*cking gold for Jev builders 20 repos people are building on Jev right now. browser agents, context tools, trading bots, even a drone 1. JEV-Ultrafast - a browser agent built for speed ↳ 2. Fast-JEV-Compaction - squeezes your context down ↳ 3. JSON-Render - UI generated on the fly ↳ 4. Typesafe-MCP - plugs Jev into any client ↳ 5. JEV-MCP - a toolkit for judgment calls ↳ 6. Semdecide - a classifier right in your terminal ↳ 7. JEV-Codex-Router - sends every task to the model that fits it ↳ 8. Winnow - clears the junk out of your context ↳ 9. JEV-Review - sorts code reviews by what needs eyes first ↳ 10. Blink - finds your way around any repo ↳ 11. Agent-Desktop - runs your desktop for you ↳ 12. Typesafe-Mario - an agent playing Super Mario ↳ 13. JEV-Drone - flies a drone ↳ 14. OneVOneJev - a shooter in your browser ↳ 15. JEV-Trader - high-frequency market making ↳ 16. Prism - spots liquidity signals ↳ 17. Neo4Jev - walks a knowledge graph ↳ 18. JEV-Curate - screens training data ↳ 19. Canny - confirms a task is really finished ↳ 20. KillMyIdea - scores a startup idea before you sink time into it ↳ start where your work is: > coding -> JEV-Review, Blink, Canny, JEV-Codex-Router > context -> Fast-JEV-Compaction, Winnow > automation -> JEV-Ultrafast, Agent-Desktop > clients and tools -> Typesafe-MCP, JEV-MCP, Semdecide > UI -> JSON-Render > trading -> JEV-Trader, Prism > data -> Neo4Jev, JEV-Curate > founders -> KillMyIdea > for fun -> Typesafe-Mario, OneVOneJev, JEV-Drone pick one, build on it this week, and you'll be the person on your team who actually knows Jev engineering when it gets asked for

Mr. Buzzoni

11,667 views • 9 days ago

sharing an easy way to test DJev (Diffusion Gemma Jev), the next evolution of the incredible jev concept and fully open sourced (model, code, api...) imagine jev but it also has: - native image-input support - native image as options!! - real-time video streaming input - as fast as jev (not with images, 600ms) - same price as jev, but can get even cheaper - using Diffusion Gemma adapted - we are seeing on-par performance but happy to have external validation! It is a research preview made for fun, so don't expect stability and the awesome scaling as jev team has delivered! this was a weekend project :) have fun!

sharing an easy way to test DJev (Diffusion Gemma Jev), the next evolution of the incredible jev concept and fully open sourced (model, code, api...) imagine jev but it also has: - native image-input support - native image as options!! - real-time video streaming input - as fast as jev (not with images, 600ms) - same price as jev, but can get even cheaper - using Diffusion Gemma adapted - we are seeing on-par performance but happy to have external validation! It is a research preview made for fun, so don't expect stability and the awesome scaling as jev team has delivered! this was a weekend project :) have fun!

David Villalón

43,117 views • 20 days ago

THIS IS F*CKING INSANE, I ADDED A CRAWLER TO JEV + MY GROK BOTS AND SLEPT, MY $100 RESTART IS NOW $12,161 AFTER 3 NIGHTS everyone on my timeline built a web crawler this week most of them just scrape headlines a crawler is a bot that reads web pages for you i plugged mine into the setup i already had the crawler reads, Jev decides, my Grok bots trade Jev is the AI that answers every question yes or no, under a second, under a cent honestly the crawler alone is a toy, Jev is what turns reading into a trade a coin called CRAWL launched at 10pm at $46K, by 11pm it was $2.05M what the three of them did while i slept: → crawler went through 88 fresh coins, Jev kept one → 11pm crawler read 1,204 posts about the coin, Jev said real people, no farm → crawler walked 6,389 holders, Jev said dev wallet clean, tradable → 12:05am it dumped to $670K, crawler flagged it, Jev said buy, bots bought → 1:30am $2.81M, Jev said out, +$4,710 → 2:35am bought again at $1.97M, 3:45am out at $3.54M, +$1,610 not every call worked, a push at 4:50am faded and cost $285 holding the coin from 11pm made you 29% my bots made 145% on that chart, five green, one red i woke up at 7am to $12,161.37 $100 → $2,197.67 → $4,962.34 → $12,161.37 at second 3 the spider taps the $670K bottom i wrote up the whole chain, crawler to Jev to bots, it's below ↓ costs nothing bookmark this and check me tomorrow show this to the one friend whose crawler only scrapes headlines night 4 is tonight, does the crawler make Jev better or is $12,161 the top?

THIS IS F*CKING INSANE, I ADDED A CRAWLER TO JEV + MY GROK BOTS AND SLEPT, MY $100 RESTART IS NOW $12,161 AFTER 3 NIGHTS everyone on my timeline built a web crawler this week most of them just scrape headlines a crawler is a bot that reads web pages for you i plugged mine into the setup i already had the crawler reads, Jev decides, my Grok bots trade Jev is the AI that answers every question yes or no, under a second, under a cent honestly the crawler alone is a toy, Jev is what turns reading into a trade a coin called CRAWL launched at 10pm at $46K, by 11pm it was $2.05M what the three of them did while i slept: → crawler went through 88 fresh coins, Jev kept one → 11pm crawler read 1,204 posts about the coin, Jev said real people, no farm → crawler walked 6,389 holders, Jev said dev wallet clean, tradable → 12:05am it dumped to $670K, crawler flagged it, Jev said buy, bots bought → 1:30am $2.81M, Jev said out, +$4,710 → 2:35am bought again at $1.97M, 3:45am out at $3.54M, +$1,610 not every call worked, a push at 4:50am faded and cost $285 holding the coin from 11pm made you 29% my bots made 145% on that chart, five green, one red i woke up at 7am to $12,161.37 $100 → $2,197.67 → $4,962.34 → $12,161.37 at second 3 the spider taps the $670K bottom i wrote up the whole chain, crawler to Jev to bots, it's below ↓ costs nothing bookmark this and check me tomorrow show this to the one friend whose crawler only scrapes headlines night 4 is tonight, does the crawler make Jev better or is $12,161 the top?

savip.

3,135,774 views • 5 days ago