Entries 481 to 528 of 743, in the hub's default order. The introduction is on page 1.
Showing 481 to 528 of 743
A video demo building a small language model out of a classifier: Jev answers 29 yes/no questions per character, the highest-probability answer is appended, and the updated text is fed back in for the next character.
vogel (@ryanvogel)OpenWriting one character at a time (X) on x.com167k viewsQuestions/char 29
Author's announcement of the jevlike repo, which lets others train their own one-pass option-scoring models inferred from Jev's published input/output type.
Vincent Wang-Mascianica (@vinnylarouge)OpenI reverse-engineered a jev-like architecture given its type (X) on x.com167k viewsSynthetic accuracy ~98%Speed at 8 options ~100x faster
Widely-shared skeptical-but-interested summary, around 145k views, of Jev's claims: 20-200x faster, 40-400x cheaper, $0.042 per 1M input tokens with free output, trained with a new method called RLCD.
kimmonismus (@kimmonismus)Openkimmonismus on Jev: sounds almost too good to be true (X) on x.com163k viewsSpeed 20-200x fasterInput cost $0.042/1M tok
A video demo evaluates a candidate profile against 400 companies in 12 seconds, ranking job matches with a confidence score and flagging candidate-job mismatches, for a total cost of $0.0005.
Sarvagya Kulshreshtha (@sarvagya_kul)OpenJob and candidate matching (X) on x.com150k views400 companies 12 sTotal cost $0.0005
A video demo uses Jev for incident triage in Box: it answers whether an incident is customer-facing and how severe it is, then routes the file into Escalate, Monitor, or Review folders and sets a metadata template with the result. Incidents below a confidence threshold go to Review for a human instead of routing automatically.
A video demo of a macOS app that monitors the Downloads folder with Jev: it checks whether a downloaded file is an invoice, then moves matching files into a folder with a corrected filename, using no other LLM calls.
A video demo of intent-based email search in Gmail built with Jev, with the author suggesting a large inbox would first narrow results with semantic search or embeddings before Jev ranks them.
A follow-up demo where Jev scrolls 723 ads as 30 simulated buyer personalities, producing 21,690 stop-or-scroll decisions for 22 cents.
Matthew Berman (@TheMattBerman)OpenScoring 723 ads against 30 simulated buyers with Jev (X) on x.com131k viewsDecisions 21,690Total cost 22 cents
A video demo backtests Jev trading the Danish stock market across all 239 trading days of 2025, using sentiment derived from market data, news articles, Wikipedia, and Google Trends, at a cost of 8.1 million tokens for $0.32.
Tommy Jepsen (@tommy_jepsen)OpenDanish stock-market backtest (X) on x.com125k viewsToken cost 8.1M tok, $0.32
Jev filters and selects creative assets, which DeepSeek and Higgsfield then turn into ad creatives, shown as a video demo from Higgsfield AI.
Higgsfield AI 🧩 (@higgsfield_ai)123k viewsOpenFiltering creative assets for ad generation with Jev (X) on x.comA video demo of Jev picking the next shell command to run based on shell history.
Announces ai-cli, an npm package installed with npm install -g ai-cli, that lets any agent harness ask yes/no questions, choose between options, or score against criteria using Jev.
Demo in which Jev decides which model should serve a request before the request is forwarded.
Vercel's eve agent framework announcing criteria-based model routing built on Jev: its experimental autoModel uses typesafe-ai/jev to pick between models described in plain language.
A chat bot that uses Jev to pick which tool to call, such as web search, Wikipedia, weather, Todoist or Home Assistant, and what arguments to pass, with no general-purpose LLM in the loop.
CJ (Coding Garden) (@CodingGarden)114k viewsOpenA chat bot that picks tools with Jev, no LLM (X) on x.com
A video demo replaces an LLM's tool-calling decision step with Jev, exploring how voice agents could act on partial speech before the user finishes speaking, aiming for lower latency and cost than running an LLM at each step.
A video demo of Jev orchestrating a 3D character's mouth, brows, eyes, cheeks, gaze, and body, ten decisions per message composed live into one reaction with no preset expressions, built for the Mutuals project.
Joao Bortotti (@john_bortotti)OpenLive 3D character expressions (X) on x.com112k viewsDecisions/message 10
An API that routes a request across more than 1,000 AI models from 50 or more providers. Corent's routing layer now uses Jev to decide what a request needs and how confident it is in that route before generation happens, falling back to a safer model below a set confidence level.
corent (@corentAI)OpenCorent on corent.tech110k viewsModel pool 1,000+ models
Builder reports that an MLP trained on top of Qwen 4B works like Jev for typed decisions, and links the weights on Hugging Face as openjev.
Jev scanned thousands of Zillow listings and classified them by traits Zillow's own filters do not expose, such as architecture style, renovation status and proximity to freeways, in under 20 seconds for $0.18.
Justine Moore (@venturetwins)OpenA natural-language search for Zillow listings with Jev (X) on x.com107k viewsScan cost <20s, $0.18
An open source library that takes any Hugging Face model and gives it Jev-style structured decision output through an API endpoint, including vision models.
Eugene Cheah - AI builder @ 🇸🇬|🇺🇸 (@picocreator)104k viewsOpenSimple Jev: Turn context into decisions on simplejev.ai
Explains how to replicate Jev-style probability output on other open models using sglang's /v1/score endpoint instead of /generate, demonstrated on a new deepseek-v4.1-flash-jev endpoint that needs a closing think tag to force a direct answer.
A video demo feeds Jev 3 million session-replay events. In 40 seconds it watched 3,247 sessions, caught 132 rage clicks, 116 dead clicks and 95 JavaScript errors, and opened 213 draft pull requests to fix them, for $2.17 in total.
Taras (@tarasshyn)OpenSession replay to bug fixes (X) on x.com101k views3M events 40s, $2.17
Paste a URL and jev-1.13.0 decides how to rebuild that website as a native iOS or Android app, which their shipper tool then submits to the app stores.
OpenRouter and TypeSafe's hosted router, typesafe/jev-router, uses Jev to pick the model and reasoning effort for each turn and avoids switches that would lose the cached conversation. OpenRouter reports it solved 237 of 423 agent tasks against 130 for its own Auto Router.
Public Convex-backed demo inviting a million judged questions instead of generated answers.
Describes 7 SEO/GEO workflows built on Jev: scoring competitor pages, flagging on-page changes for citation, matching buyer questions to pages, rating citation likelihood, sorting search terms by buyer intent, mapping internal links and verifying AI-written pages before a human sees them.
A browser fighting game where you play against Jev, TypeSafe's decision model, from the keyboard on desktop or mobile.
Compares packaged snacks for kids across brands, sorted by sugar content and filterable by age, allergen and category. Jev scored 3,000 snacks against multiple criteria in 28 seconds for $0.11.
Nikunj Kothari (@nikunj)OpenNoSugarForKids on nosugarforkids.com92k views3,000 snacks 28s, $0.11
A video demo adds Jev to the AI Hedge Fund project, using it to backtest trading decisions after setting a strategy and picking tickers, running the process in seconds rather than minutes.
Virat Singh (@virattt)OpenAI Hedge Fund with Jev (X) on x.com91k viewsSpeed 100x faster
Jev scored 3,282 of the poster's X posts, covering 100M views, on 8 questions each about topic, hook and tone, for $0.1282 and 8m34s total. How-to posts got a 150 median likes versus 44 overall.
Ian Nuttall (@iannuttall)OpenJev scored 3,282 X posts for what drives growth (X) on x.com88k viewsTotal cost $0.1282Run time 8m 34s
Technical breakdown of schema-constrained output, RLCD, the Doom and Wikiracing demos, and pricing. Lists limits including the 255-option cap on Choice and the absence of public benchmarks or released weights.
85k viewsLatency 70-500 msChoice cap 255 options
A browser extension that hides or collapses X posts by a natural-language rule, using Jev to judge each post fast enough that the filtering is not noticeable while scrolling.
Marcel Pociot 🧪 (@marcelpociot)85k viewsOpenA browser extension that filters X posts with Jev (X) on x.com
Find Reddit buyer intent and see what every lead's data cost.
Kevin Wang (@mxfp4)Openlurk by AnyAPI on lurk.so84k viewsThreads scanned 4,000
Reports using Jev in place of smaller models on a security pipeline, citing over 5x lower cost, faster responses, and much higher accuracy.
Greg Pstrucha (@grichadev)OpenJev inside a security pipeline (X) on x.com83k viewsCost vs prior model 5x lower
Ran 14 yes/no questions per post, such as whether the hook opens a loop or whether a claim is proven, over 100,000 X posts in 20.4 seconds for 67 cents, then compared which hook types actually beat the viral baseline.
Movez (@0xMovez)OpenA viral post analyzer for 100,000 X posts (X) on x.com82k viewsFull run 20.4s, $0.67vs Opus 5 per post ~680x cheaper
A video demo of Jev playing Tetris in real time, with the model's response speed fast enough to push blocks down during play.
A Cline plugin, installed from its desktop app's plugin marketplace, that gives Jev a background Chrome browser to complete tasks; needs a Vercel AI Gateway API key saved to the plugin's config file.
Video Tetris benchmark: Laya-MLX runs fast on a MacBook at about 84ms per decision but loses to Jev in all three rounds.
Tony Dinh (@tdinh_me)OpenTetris Bench: Jev vs Laya-MLX on x.com73k viewsLaya latency ~84 msResult Jev won 3/3
A video demo of a calorie-tracking app kitze built with Jev.
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
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
Walks through the launch video, why decision models need to exist, and how they differ from LLMs in use. 15 minutes.
An open source framework for running end to end tests with agents, built with Jev, covering web and mobile targets.
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
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
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
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.
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