Instant calorie tracking (X)
A video demo of a calorie-tracking app kitze built with Jev.
DiscussionStructured extraction
Jev projects and examples: 638 builds on GitHub, X and YouTube (page 10 of 14)
Entries 433 to 480 of 638, in the hub's default order. The introduction is on page 1.
All entries
Showing 433 to 480 of 638
A research dashboard for X posts labeled by Jev (X)
A personal research dashboard where Jev labels saved X posts across 8 dimensions, including topic, hook and writing style, so the poster can filter and compare engagement. 1,315 posts cost about $0.086 in estimated model cost.
Yum⋆₊˚ (@yuhasbeentaken)OpenA research dashboard for X posts labeled by Jev (X) on x.com70k viewsCost ~$0.086Posts labeled 1,315
Discussion
Stagehand browser control with Jev (X)
A video demo of browser automation combining Jev with Stagehand: the page's accessibility tree is sent as state, Jev answers which action to take next, and Stagehand executes it. One task cost $0.001 and ran at near-instant speed in a remote browser.
Kyle Jeong (@kylejeong)OpenStagehand browser control with Jev (X) on x.com69k viewsCost per task $0.001
DiscussionTyped tool dispatch
This New Frontier Model Is Not An LLM.
Walks through the launch video, why decision models need to exist, and how they differ from LLMs in use. 15 minutes.
Video
Tester Army E2E
An open source framework for running end to end tests with agents, built with Jev, covering web and mobile targets.
Tool
Meet Jev: The AI Built to Make Decisions
Tests Jev on the creator's own inbox, classifying 100 then 1,000 emails by category, priority, spam and reply-needed at around 200ms average response time. Ends by checking the actual bill.
67k viewsAvg response time ~200 msSpeed claim tested ~200x
Ego Lite shopping decisions (X)
A video demo of the Ego Lite shopping agent using Jev with DeepSeek Flash, completing 20 Amazon product decisions in 3.71 seconds versus 54.45 seconds for GPT-5.6 Sol, with the same result on both runs.
ego (@ego_agent)OpenEgo Lite shopping decisions (X) on x.com63k viewsJev run 3.71s / 20 itemsGPT-5.6 Sol run 54.45s
Discussion
Five hundred agents in a 3D environment (X)
A video demo benchmarking Jev running 500 real-time agents in parallel inside a 3D environment, reporting 500ms average latency and 35 API calls per second with an unoptimized, naive implementation.
Cris Lenta (@crislenta)OpenFive hundred agents in a 3D environment (X) on x.com61k viewsAgents 500Avg latency 500 ms
DiscussionReal-time control
AgentRun reusable workflows (X)
A video demo introduces AgentRun, an agent harness built with Jev that learns how to perform a task, writes itself a general solution, and then steps out of the loop.
Discussion
Email fraud detection with Jev and Kimi (X)
A video demo classifies 100 test emails, 50 legitimate and 50 fraudulent, with Jev in 1.42 seconds, routing the 31 cases below 95% confidence to Kimi K3 for a second opinion. The combined pipeline reached 96% accuracy for about $0.07 total.
Hassan (@nutlope)OpenEmail fraud detection with Jev and Kimi (X) on x.com60k viewsJev pass 100 emails, 1.42sCombined accuracy 96/100
DiscussionConfidence-gated actions
OpenRouter benchmarks Jev's speed against other models (X)
OpenRouter benchmarked Jev with its Ori Eval judging harness against popular LLMs and found Jev over 5 times faster than the next fastest model, with its slowest requests still beating every other model's median.
OpenRouter (@OpenRouter)OpenOpenRouter benchmarks Jev's speed against other models (X) on x.com60k viewsSpeed vs next model >5x fasterJev median latency 154 ms
Discussion
Live clinical-transcript classification prototype (X)
A video demo of a prototype that feeds a live clinical consultation transcript to Jev, which traverses a medical ontology to classify symptoms, update the differential diagnosis, suggest treatments, and flag red flags in real time.
Chris McMaster (@rheum_ai)57k viewsOpenLive clinical-transcript classification prototype (X) on x.comDiscussionHierarchical classification
A live viral-post analyzer built with Jev (X)
A live viral-post analyzer built with Jev: it scores viral potential and categorizes a tweet as the user stops typing, shown here as an early, in-progress demo.
Discussion
A visual reference finder built with Jev (X)
A single prompt pulls about 100 reference images from Cosmos, NASA and The Met using Jev, shown as a video demo of the tool.
Discussion
A typed trading-rule experiment (X)
A video demo of a TSLA 50-day moving-average trading rule with Jev in the judgment layer: real API calls return typed answers, and the author's code decides the action from there.
DiscussionConfidence-gated actions
An agent with a model router powered by Jev (X)
A short video demo of an agent whose model router is powered by Jev; the post text gives no further detail on how the routing itself works.
DiscussionIntent and model routing
Jev-review feedback for coding agents (X)
A video demo of jev-review, an experimental local-first MCP plugin that scores a coding agent's work against quality metrics; the agent calls Jev, gets scored, makes improvements, and repeats the loop.
DiscussionSemantic code linting
MuJoCo robot-arm control (X)
A video demo tests Jev as a real-time control policy for a robot arm in MuJoCo, splitting each update into two calls: one to decide the next action, another to decide how to move the arm and gripper. Jev receives simplified geometry and contact data as text rather than images.
DiscussionReal-time control
Artificial Analysis Decision Index: 11 hosted decision models against language models
Artificial Analysis scores 11 hosted decision models on knowledge, reasoning, tool-calling and safety tests, with cost and time per task, and runs language models on the same tests. Jev 1.13 led the decision models at launch at 58, and Liquid's d1-ultra, added by 15 October, now leads at 65; Claude Haiku 5.5 (Low) scores 61 but takes 1.4 seconds per task against 0.13.
Artificial Analysis (@ArtificialAnlys)45k viewsOpenArtificial Analysis Decision Index: 11 hosted decision models against language models on artificialanalysis.aiArticle
Jev Decision Index: Jev against 50+ open decision models
A leaderboard that runs Jev and 54 open System One models and clones through the same 120,000-question suite on one RTX PRO 6000, scoring accuracy and calibration. Jev leads the 0.2 edition at 51.67 on a chance-corrected scale, with AutoJev-27B close behind at 50.94.
apolinario (poli) (@multimodalart)43k viewsOpenJev Decision Index: Jev against 50+ open decision models on huggingface.coArticle
Intelligent autofill buttons (X)
A video demo shows background auto-fill buttons built with Jev integrated directly into an app's UI, contrasted with slower LLM-based alternatives.
Discussion
A plain-English logic interpreter (X)
A video demo of a logic interpreter built to compensate for the fact Jev cannot reason on its own: it runs a logic language whose facts and rules are written in plain English.
Discussion
Jev vs. GLM at chess (X)
A video demo pits Jev against GLM 5.3 at chess: GLM won by checkmate in 29 moves, with Jev responding in about 0.3 seconds per move versus GLM's 5.8 seconds, for a total game cost of 24 cents.
Hassan (@nutlope)OpenJev vs. GLM at chess (X) on x.com39k viewsJev per move ~0.3sGame cost 24 cents
DiscussionReal-time control
MOSS x Jev
Jev picks the target for the MOSS litter-picking robot, for example switching from cans to bottles on a new instruction. In the newer v0.2 physics replays it also picks each arm action, and the page replays MOSS acting on Jev's real recorded decisions.
ProjectReal-time control
Jev (Fully Tested) + Browser Use: Fastest AI Agent I've Tried Yet
Runs Jev through support routing, refund detection, a prompt-injection attempt, exact-value selection, agent auditing and browser automation, with evaluation times as low as 92ms. Notes constrained outputs do not guarantee correct answers when the option list is incomplete.
Jev Detector: Free AI Slop Detector
Paste up to 10,000 words and see the generated-sounding sentences worth a second look. Free and no login.
Jozef (@jozef_gherman)OpenJev Detector: Free AI Slop Detector on jevdetector.com36k viewsScan speed ~2s/10k words
ArticleRethinking security engineering with Jev (X)
Argues that the purely engineering decisions inside security workflows belong to a typed decision model like Jev rather than a chat model.
Kostas Tsale (@Kostastsale)OpenRethinking security engineering with Jev (X) on x.com34k viewsSpeed and cost x200
OCR-powered image classification (X)
A video demo combines OCR with Jev to build an image classifier that categorized about 900 images in 40 seconds.
Fayaz Ahmed (@fayazara)OpenOCR-powered image classification (X) on x.com34k viewsThroughput 900 in 40s
DiscussionHierarchical classification
Jev-browser, a general browser skill for agents (X)
A demo of a general-purpose browser skill where an agent is given a site and a task, and Jev decides every click based on what is on screen.
AI Builder Club (@aibuilderclub_)33k viewsOpenJev-browser, a general browser skill for agents (X) on x.comDiscussion
Is Jev What AI Has Been Missing? I Tested It.
Hands-on test of Jev through the TypeSafe console with commentary on where it fits. 17 minutes.
Video
A page-by-page OCR router (X)
A video demo of a per-page PDF router built with Jev that decides which pages need OCR and extracts the rest locally, aiming to cut both cost and processing time.
Discussion
A 6502 emulator experiment (X)
A video demo runs 6502 CPU emulation directly on Jev, executing short programs in real time with no speed-up, though the output occasionally diverges from a reference emulator.
Discussion
A job crawler that matches your profile (X)
A video demo rebuilds a job crawler with Jev: the model finds a company's careers page, chooses which links to follow, recognizes job postings, and scores each role against the user's profile, cutting the task from about 5 minutes with an LLM to about 20 seconds.
25k viewsBefore (LLM) ~5 minAfter (Jev) ~20s
Discussion
Local Laya vs Cloud Jev on the Same Snake Game
30-second Snake benchmark: a local 421M Laya checkpoint scores 46 at 86.5 decisions per second, while Jev 1.13.0 over the cloud API scores 1 at 3.2 decisions per second.
Simplifying AI (@simplifyinAI)OpenLocal Laya vs Cloud Jev on the Same Snake Game on x.com24k viewsLaya speed 86.5/sJev speed 3.2/s
VideoReal-time control
Supabase RLS Linter
An experimental linter for Postgres Row Level Security policies, built with Jev. It sends nine judgments about a submitted policy and table schema in a single request to check whether access controls actually restrict users to their own data, not just that RLS is turned on.
ProjectSemantic code linting
Real-time Clippy built with Jev (X)
A Clippy-style assistant that watches product usage and only appears when Jev judges the user is hesitating, confused or stuck; Jev also drives its reactions.
Discussion
Jev AI Is INSANE... 193x Faster Than LLMs?!
Breaks down the side-by-side against GPT-5.6 Terra, the 193.6x faster and 444.6x cheaper workflow evals, and the 0% type-error chart. Covers the Doom and Wikiracing demos.
VideoReal-time control
Finding the intent signals that book demos with Jev (X)
Given a dataset of outreach messages, Jev found which intent signals correlated with the most booked demos in 40 seconds for under $0.20; the poster says it can also rank leads and measure prospect-message fit.
Pierre-Eliott Lallemant (@pierreeliottlal)OpenFinding the intent signals that book demos with Jev (X) on x.com22k viewsTurnaround 40sCost <$0.20
Discussion
Tagging X posts in real time with Jev (X)
A video demo of Jev tagging X posts in real time as breaking, a golden nugget, or slop.
Discussion
Keep anything as Markdown for your AI agents
Save notes, links, images, videos, PDFs, audio, and other useful material as clean Markdown your AI agents can search, read, and update.
Ian Nuttall (@iannuttall)OpenKeep anything as Markdown for your AI agents on keep.md20k viewsSearch rerank 7x fasterTagging speed 50x faster
Article
Filtering unwanted X replies (X)
A video demo uses Jev to filter out low-quality reply comments on X that the platform's own filters miss, built in about 5 minutes with Astra and an API key.
Ian Nuttall (@iannuttall)OpenFiltering unwanted X replies (X) on x.com18k viewsBuild time ~5 min
DiscussionLLM guardrails
System One Jev (Fully Explained): Does this really beat Transformer models?
Examines the speed and cost claims and what the published benchmarks show, noting Jev competes on some tasks and falls well behind on others. Clarifies the zero-hallucination claim covers output structure, not decision correctness.
AISeeKing17k viewsOpenSystem One Jev (Fully Explained): Does this really beat Transformer models? on youtube.comVideo
Jev-thoven music composition (X)
A video demo shows Jev-thoven, a system built on Jev, composing an entire two-minute song from first principles.
Discussion
System 1 Models Jev Explained: 200ms AI Decisions, Zero Token Streaming
Explains the autoregressive latency floor set by memory bandwidth per token and how a single-pass architecture bypasses it. Covers the Kahneman framing, calibration and the Jevons Paradox naming.
Dots and Arrows15k viewsOpenSystem 1 Models Jev Explained: 200ms AI Decisions, Zero Token Streaming on youtube.comVideo
Voice-controlled Figma (X)
A video demo of controlling Figma with voice commands routed through Jev, with a total cost of $0.01 from first line of code to the recorded demo.
DiscussionTyped tool dispatch
Bannerbear instant field mapping (X)
A video demo of Bannerbear using Jev to map template fields such as photo, name, and company name to differently named data source fields such as avatar, full name, and business, in one click.
DiscussionEntity alignment
Contextual clipboard quick actions (X)
A video demo of an app that monitors the macOS clipboard with Jev, detecting when the copied content is a terminal command and offering a quick action to run it.
DiscussionTyped tool dispatch
Jev on Sol
A live trading site where Jev re-reads a Solana token every 5 seconds for its call, dump risk and buyer control. Users write their own yes-or-no, choice or score classifiers, combine up to six into a strategy, and backtest or run it live against every new launch.
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