Entries 337 to 384 of 638, in the hub's default order. The introduction is on page 1.
Showing 337 to 384 of 638
Hackathon project: 200 people versus one agent behind a typed System One action gate that learns from each breach, evaluated with W&B Weave and hardened by a defender loop. Playable at vnmoorthy.github.io/siege.
Five-task timed benchmark for browser agents plus almond-fastloop, a roughly 200-line agent wiring Chrome DevTools state to a bounded Jev decision and an executor. Leaderboard as of 2026-09-17 shows fastloop at 13.8s total versus Codex 66.2s and Claude (Cowork) 100.3s.
A speed layer for computer-use tasks on Solari: one structured observation, one Jev decision, and one verified action per step, for both browsers and Linux desktops, with no screenshots in the loop.
A Rust CLI that reads completed Claude Code and Codex sessions, scores them with Jev, and suggests specific changes to your agent instructions, skills and tools based on where work went well or got stuck.
Four Claude Code hooks that use Jev for cheap, calibrated judgment calls inside the agent loop: a danger gate that blocks destructive tool calls, a failure notice, a completion check, and a scope check.
Wikiracing solver that uses Jev to rank outgoing links by fewest expected remaining hops, scoring up to 128 candidate links per request with up to five concurrent requests, shown live in the terminal.
Searches an Obsidian vault locally and offline with a BM25 engine, then reranks the top results with Jev only after you approve exactly what gets sent to it.
A browser chess coach on Cloudflare where Stockfish owns the truth about the position and Jev makes the coaching judgment after every move.
Go 1.27 client with generic typed questions (jev.Noul, jev.Choice, jev.Score, plus jev.Raw). Supports batching, retries, and Vercel AI Gateway as an alternative backend.
A live, graphical demo of Jev covering routing, a Tetris-playing agent, parallel swarms and a Jev-versus-Claude gauntlet, built to show its accuracy and speed on real inputs rather than a pre-recorded video.
lafollett-labsOpenlafollett-labs/typesafe-jev-dojo on github.com
An independent, reproducible audit of how well Jev performs in Spanish, with a run of 19,200 calls across four datasets showing measurably lower accuracy when the same instructions are given in Spanish instead of English, plus a CLI to repeat the comparison on your own labelled data.
marcosmartinezOpenmarcosmartinez/jev-acento on github.comA pre-registered evaluation of Jev's pairwise hawkishness rankings of FOMC chair press-conference openings, checked against same-day federal funds rate changes and an independently published scoring project.
maybern-tripp-smithOpenmaybern-tripp-smith/fedjev-bench on github.comA stateless CLI for typed judgments with Jev, turning a state plus typed questions into JSON on stdout and exit codes a shell script can branch on.
model-clisOpenmodel-clis/jev on github.comAn MCP server that lets Claude hand a whole browser task to Jev, which makes each click, type or select decision in about 100ms while Claude keeps planning the task and verifying the result.
MSalvalaggioOpenMSalvalaggio/jev-reflex on github.comModeration for communities and apps that scores every message for spam, scam, harassment and other categories with Jev, with thresholds and actions you set. Ships as Discord, Telegram and Reddit bots plus a CLI, Python and npm packages, an HTTP API and an MCP server.
ohernandezdevOpenohernandezdev/jevmod on github.comA capability kernel that gates every agent tool call: the model gets canaries and placeholders instead of real secrets, and Jev is one of the sensors deciding block, ask, or allow.
A Chrome extension that sends LinkedIn feed post text to Jev with a rubric of narrow yes/no and rating questions, then blurs posts it scores as low value, with one-click reveal.
Scores Federal Reserve press conferences hawkish to dovish in real time: Jev rates every word the Chair says in about 150 milliseconds, side by side with a chat model scoring each caption line.
Unofficial typed Elixir client for TypeSafe AI and Jev with offline test stubs, concurrent fan-out and atom-keyed answers.
An adversarial evaluation of Jev with nine experiments and 28 predictions fixed before any data was collected. One run covered 123,805 requests over 138 minutes for $12.69, with five failures, plus a 13-rule prompting guide.
An Android system-wide overlay that reads on-screen text through an AccessibilityService, sends it to Jev, and shows a floating badge when a manipulative interface pattern looks likely, skipping password and card entry screens.
zohaib-mdOpenzohaib-md/UXRay on github.com
The founder's launch post, around 76k likes, arguing that RLCD-trained decision models are a shorter path to economic value than chat models. Submitted separately to HN as item 49716682.
Diogo Almeida (@CompleteSkeptic)OpenDiogo Almeida's Jev launch post (X) on x.com39M viewsSpeed 20-200x fasterCost 40-400x cheaper
A video demo pairs json-render with Jev to render generative UI components in milliseconds, using the viewer's own components, actions, and design system.
A video demo of copy and paste made 'smart' using Jev from TypeSafe, with no further detail on the mechanism given in the post text.
A demo breaking down 724 live ads from 37 brands in 40 seconds for 9 cents, covering hook, format, offer, CTA, funnel stage and landing-page mismatch for each ad.
Matthew Berman (@TheMattBerman)OpenBreaking down 724 ads from 37 brands with Jev (X) on x.com1.1M viewsSpeed 724 ads/40sCost 9 cents
A video demo has Jev read 586 pages of a site in 45.1 seconds and rebuild the internal link map, placing 584 links and refusing 139 pages where nothing fit, for $0.21 total. In the same time, Claude Opus 5 processed only 21 of the same pages for $1.43.
borja (@borjafat)OpenAn internal-link SEO audit (X) on x.com827k viewsPages read 586 in 45.1sCost $0.21
A video demo rebuilds a Tesla Full Self-Driving-style simulator controlled by Jev, built in under an hour.
Company launch post announcing early access to Jev.
A video demo of voice-controlled computer use on a Mac built with Jev: dictating a command such as opening the Notes app triggers the action before the sentence finishes.
A video demo of Jev playing Super Mario Bros. in real time, using its fast inference and structured output for moment-to-moment decisions.
A video demo of Jev V13 playing 5+0 blitz chess against Fable 5.1 and GPT-6 Astra, one move per API call, answering in about 2.6 seconds per move. Fable was ahead on material but lost on time; Astra mated Jev in 18 moves.
AI/ML API (@aimlapi)OpenBlitz chess against frontier models (X) on x.com559k viewsMove latency ~2.6 svs Astra mated in 18 moves
A video demo of Jev generating platformer game levels in real time, using fast structured output aimed at game development.
A short video demo asking whether Jev understands colour, posted by generative artist Matt DesLauriers, who calls the model a leap forward for building new UX and UI paradigms on top of language models.
A video demo of jev(), a PostgreSQL extension that filters rows with a natural-language condition inside a WHERE clause with no index or embeddings. It judged 129 rows in about 1 second for $0.0009, and 6 milliseconds on a cached rerun.
Zachi (@iam_zachi)OpenNatural-language queries inside PostgreSQL (X) on x.com478k viewsFirst run 129 rows/~1sCost $0.0009
Given 700 high-intent leads and personalized outreach messages, Jev predicted how each message would perform, assigned a confidence score and flagged lead-message mismatches in 40 seconds for $0.09.
Romàn (@romanbuildsaas)OpenScoring 700 leads and outreach messages with Jev (X) on x.com476k viewsSpeed 700 in 40sCost $0.09
Microsoft's launch post for Microsoft-Decision-1, a Qwen3.5-9B decision model on Foundry at $0.042 per million input tokens. Its vendor-run charts, run on an undisclosed 36-benchmark suite, now include Jev: 82.3% accuracy and 93.7 calibration against 83.5% and 92.2 for Microsoft-Decision-1.
Satya Nadella (@satyanadella)454k viewsOpenMicrosoft-Decision-1: Our model for fast decision-making on commandline.microsoft.com
A video demo of an email classifier built with Jev, tested on 1,500 of the author's own emails.
Demos a launcher that ranks results by alias, fuzzy match and habit; Jev reads typed intent so a query like 'the pdf I just downloaded' puts the newest matching file on top within about 100 ms.
nader dabit (@dabit3)OpenA predictive launcher powered by Jev (X) on x.com429k viewsResponse time ~100 ms
A video demo of Jev drawing pictures by predicting every pixel in parallel.
A video demo of a massively parallel, browser-based adversarial testing suite built with Jev that tries to break each software release, at a cost described as pennies per run.
A video demo controls a browser in real time by voice: the spoken transcript goes to Jev, which returns probabilities in about 300 milliseconds, and the browser acts on the result for roughly $0.0002 per decision.
Moritz Kremb (@moritzkremb)OpenReal-time voice control for a browser (X) on x.com368k viewsResponse time ~300 msCost per decision $0.0002
Describes an SEO/GEO agency workflow, auditing Search Console, PostHog/Mixpanel and AI citation data, that used to cost about $250 per client; each step now runs roughly 30x faster with Jev, cutting the total cost by 90%.
Ira Bodnar (@irabukht)OpenAn SEO/GEO agency workflow that cut costs 90% with Jev (X) on x.com366k viewsCost cut 90%Prior cost/client ~$250
A demo of Jev playing Subway Surfers at superhuman speed, including 50 games running at once, for under a cent total.
A video demo shows Jev returning 14 typed probability checks per pull request diff, such as hardcoded secrets and SQL injection, which code turns into a block, review, or merge verdict. Checks scoring between 0.35 and 0.65 confidence are escalated to a human or a larger model.
Paolo Rosson (@redp314)OpenFourteen checks for every pull request (X) on x.com357k viewsCost per PR $0.00007vs Opus, 1k PRs 7c vs $14.50
A video demo of Jev controlling all 4 characters in a Smash Bros match against itself, picking each next move within a fraction of a second; the match used over 22 million tokens for a few cents.
Mau Baron (@maubaron)OpenJev playing all 4 characters in a Smash Bros match (X) on x.com311k viewsTokens used 22M+
A video demo shows Jev classifying 500 emails in a few seconds for a total cost of 3.5 cents.
Riley Brown (@rileybrown)OpenClassifying 500 emails in seconds (X) on x.com296k viewsCost 3.5 cents
A video demo of computer-use automation built with Jev, said to run 155x cheaper and about 20x faster than Opus 5 while generalizing across operating systems.
aaron (@awlevin)OpenComputer use across operating systems (X) on x.com292k viewsvs Opus 5 155x cheaperSpeed vs Opus 5 ~20x faster
Hassan used Jev to sort 1,018 AI research papers into one of 24 topics for $0.08 in total, with a 256 ms median latency per paper, after DeepSeek V4 Flash wrote the summaries. He was still running evals before swapping them in for the topics on 1kpapers.com.
Hassan (@nutlope)Open1kpapers, AI research papers classified by Jev on 1kpapers.com286k viewsCost $0.08Latency 256 ms median
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