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Jev AI examples, page 2

407 real Jev AI builds and public demos, updated daily. Original text, metrics, and a link back to each source.

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Public Jev AI examples and demos, not official TypeSafe docs. Clients and SDKs are in the Jev GitHub projects. Paths for jev-latest, Vercel, and OpenRouter are in the September 2026 channel map.

Agent-skill repositories are listed on Jev skills on GitHub.

OpenRouter model ids recorded for Jev AI are on Jev AI on OpenRouter. Rubric and eval posts are on Jev as a judge. How the company and the model fit together is on TypeSafe AI. The pricing calculator uses the published input rate.

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Genkit Go 1.14 is out! - Typed human-in-the-loop tools - Improved model recovery from tool errors - New usage budgets and context compression - Decision model s…

Infrastructure

Genkit @GenkitFramework

EN

@GenkitFramework ships Genkit Go 1.14 with decision-model support for fast classification and routing (preview), plus HITL tools and budgets.

Genkit Go 1.14 is out! - Typed human-in-the-loop tools - Improved model recovery from tool errors - New usage budgets and context compression - Decision model s…

Poster from ikki 🇵🇸🇸🇩 (@ikkistan)

Benchmarks

ikki 🇵🇸🇸🇩 @ikkistan

EN

@ikkistan benchmarks guest-photo moderation for Candids on UnsafeBench: Cloudflare clef-flash, TypeSafe Jev, Claude Haiku 5.5, and Amazon Rekognition.

I’m building Candids, an app for wedding and party guests add photos to one shared album from their phones. Guest uploads need moderation, so I benchmarked four…

Poster from Anshumani Ruddra (@baboonzero)

Guides

Anshumani Ruddra @baboonzero

EN

@baboonzero uses Jev, TypeSafe's System 1 model, to decide where a teaching explanation starts, ends, and stands alone, in a Super IC write-up.

I have more than a hundred hours of recorded teaching. Finding useful two-minute clips means deciding where an explanation starts, where it ends and whether it…

Poster from Miguel Ríos Berríos (@MiguelriosEN)

Agents

Miguel Ríos Berríos @MiguelriosEN

EN

@MiguelriosEN open-sources Pi-vision: TypeSafe Jev analyzes images/video/docs while a Pi agent orchestrates, cutting frontier-token spend.

A few weeks ago, we built a new harness, AgentRun, which turns repetitive steps into workflows and code using Jev. This week we're open-sourcing its best featur…

If you have @typesafeai Jev or any decision model configured in term-llm, you will get smart reranking of ag results starting today: https://github.com/SamSaffr…

Apps

Sam Saffron @samsaffron

EN

@samsaffron: with Jev or any decision model configured in term-llm, ag results get smart reranking (PR #1267).

If you have @typesafeai Jev or any decision model configured in term-llm, you will get smart reranking of ag results starting today: https://github.com/SamSaffr…

Poster from Tony Simons (@tonysimons)

Apps

Tony Simons @tonysimons

EN

@tonysimons ships Verdict: a second AI on Grok Bot that uses TypeSafe Jev to rank X posts and drafts against your criteria.

🚨 I gave my Grok Bot a SECOND AI. Its job? Judge my shit. 😂 📢 Meet Verdict: Grok Bot + Jev, the decision model from @typesafeai, run by @CompleteSkeptic, who he…

Poster from m (@lotusfracture)

Apps

m @lotusfracture

EN

@lotusfracture demos multi-object detection using Jev loops with feedback.

multi-object detection using Jev loops with feedback

Poster from Josef Richter (@josefrichter)

Apps

Josef Richter @josefrichter

EN

@josefrichter demos genUI "app in the app" using Jev and Mercury for quick organic UI inside existing apps.

Some more #genUI experiments. This is sort of an "app in the app". Using #Jev and #Mercury for very quick "organic UI" within existing apps. The idea is that th…

Jev, Haiku and clef-flash rank unsafe images about equally well (AUROC 0.86 to 0.87, Rekognition 0.70) at 4 to 18 cents per 1,000 images vs $1. Code, per-image…

Benchmarks

ikki 🇵🇸🇸🇩 @ikkistan

EN

@ikkistan: Jev, Haiku, and clef-flash reach AUROC 0.86 to 0.87 on unsafe images, Rekognition 0.70, at 4 to 18 cents per 1,000 images versus $1.

Jev, Haiku and clef-flash rank unsafe images about equally well (AUROC 0.86 to 0.87, Rekognition 0.70) at 4 to 18 cents per 1,000 images vs $1. Code, per-image…

Poster from Xavi Portilla (@Xavidop)

Agents

Xavi Portilla @Xavidop

EN

@Xavidop built a Kubernetes software factory: Gemini and Genkit build each stage, and Jev gates ship, rework, or ask a human.

I built a software factory on Kubernetes 🏭 Feature request in, tested and reviewed Go module out. Gemini (@googleaidevs) builds each stage as a @GenkitFramework…

we made our agent browser test runs faster by 90-95% using Jev previously: an agent would navigate through the page using chrome-devtools-axi. the way that work…

Apps

Luv Agarwal @luv_agarwal_

EN

@luv_agarwal_ cut agent browser test runs by 90-95% with a Jev-driven YAML step runner (ck-browser).

we made our agent browser test runs faster by 90-95% using Jev previously: an agent would navigate through the page using chrome-devtools-axi. the way that work…

Been editing my TikToks this way since January. What I've learned and built along the way: - Have a decision model like @typesafeai Jev pick the retake winners…

Apps

Kevin @KevinMagnan

EN

@KevinMagnan has a decision model like Jev pick the retake winners from the transcript while editing TikToks.

Been editing my TikToks this way since January. What I've learned and built along the way: - Have a decision model like @typesafeai Jev pick the retake winners…

Quoted @petergyang

My experiment building a skill router plugin for Claude Code with Jev: https://abgregs.github.io/jev-skill-router/ How it Works Before the model sees your promp…

Agents

abgregs @abgregs

EN

@abgregs built a Claude Code skill router plugin: each skill scored with a Jev Noul before the model sees the prompt.

My experiment building a skill router plugin for Claude Code with Jev: https://abgregs.github.io/jev-skill-router/ How it Works Before the model sees your promp…

Quoted @CompleteSkeptic

Poster from Shahrukh Siddiqui (@Shah1337L)

Apps

Shahrukh Siddiqui @Shah1337L

EN

@Shah1337L says Jev now plays Snow Bros with an LLM and a local controller. In that minute, levels 61–62 were cleared, 63 was reached, and no lives were lost.

I used to play Snow Bros on my PC in Karachi. Now Jev plays it with an LLM + local controller. This minute: levels 61–62 cleared, 63 reached, zero lives lost. C…

Poster from Suleiman (@Su1eyman11)

Agents

Suleiman @Su1eyman11

EN

@Su1eyman11 tries reasoning plus inverse kinematics with no learned motion policy: Jev as System 1, Astra as fallback, IK for motion, fruit into a tray.

How far can we get with reasoning + inverse kinematics, without a learned motion policy? I built this small experiment with Jev as System 1 and Astra as the fal…

Poster from localix.ai (@localixai)

Agents

localix.ai @localixai

EN

@localixai explains decision models (Jev from TypeSafe) and shows where they built them into a pet project.

Decision models (Jev from TypeSafe) are a relatively new class of models: they don't write text, they make decisions. I built them into my pet project in a few…

Poster from Andy Gao (@instantricecook)

Benchmarks

Andy Gao @instantricecook

EN

@instantricecook runs 66 Where's Waldo scenes across decision models; Jev 1.14 is quickest, with a public Waldo bench site.

I wanted to see how well decision models are at... Finding Waldo. After 66 scenes, here are the results: - @liquidai d1-ultra found the most Waldos - @typesafea…

Poster from Ajit Datar (@ajitomatix)

Apps

Ajit Datar @ajitomatix

EN

@ajitomatix tests TypeSafe Jev 1.14 experimental image support on SOS Draw, comparing text, image, and hybrid against a handcrafted stroke-to-text pipeline.

When @typesafeai AI released #Jev 1.14 with experimental image support, I had to test it on SOS Draw! Can @typesafeai recognize a player's raw canvas drawing be…

Poster from GC AI (@gcai)

Benchmarks

GC AI @gcai

EN

@gcai: GC AI Engineering built 38 projects in 12 hours with TypeSafe Jev while @ChrisDzoba tried to break it.

GC AI Engineering built 38 projects in 12 hours with TypeSafe's Jev, a classification model. Director of Engineering @ChrisDzoba spent the day trying to break i…

Poster from Daniel Wright (@b1gdan)

Apps

Daniel Wright @b1gdan

EN

@b1gdan uses Jev on an inbox: 263 emails sorted into piles in 2.0 seconds, labeled client, lead, needs a reply today, or needs acting on.

I'm using Jev with my inbox, and it sorted 263 emails into piles in 2.0 seconds, then tells me if each one is a client, a lead, needs a reply today or needs act…

Poster from Rohde Builder (@felipe_rohde)

Apps

Rohde Builder @felipe_rohde

EN

@felipe_rohde built MenuBlip: a digital menu that understands orders in any language and recommends dishes in real time on Jev.

I built MenuBlip, a digital menu that understands orders in any language and recommends dishes in real time. It runs on Jev, the first System One model by @type…

Poster from Aras Kavakli (@araskavakli)

Apps

Aras Kavakli @araskavakli

EN

@araskavakli built a contact-form screener with Jev and Claude Haiku: legitimate enquiries pass, the rest wait, about $1 a month, no captcha.

A client's contact form was being used to phish and harass their team. We built a screener using Jev and Claude Haiku. They read every message first. Legitimate…

Poster from Pial (@SaadMRP)

Benchmarks

Pial @SaadMRP

EN

@SaadMRP: Jev diagnoses SREGym-Lite faults; LLM review lifts pass rate 78.1%→89.5% across 21 faults, ~38s avg.

1/8 In our latest experiment, we let Jev, a decision model, investigate system failures and asked an LLM to check its diagnosis. Across 21 SREGym-Lite faults, r…

Poster from Peter Cruckshank (@PeteCapeCod)

Agents

Peter Cruckshank @PeteCapeCod

EN

@PeteCapeCod ships npm dev-orchestrator: Jev/OAI Decisions/CF Clef drive Codex CLI or Claude Code instead of expensive reasoning tokens.

I've been working on a new thing! It's a cli that uses other clis, basically you can use Jev (or OAI decisions, or CF's Clef/flash) to make calls either codex c…

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