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All Jev resources

This is the full index of everything Jev: 2231 entries for TypeSafe AI's flagship System One model, from official documentation, SDKs, and cookbooks to community-built clients, MCP servers, agent tools, and write-ups. Every entry is tagged by category, format, and topic, and sorted newest first.

Filter by category or tag, or search titles, descriptions, authors, and repos. Open any card for its detail page — most entries carry a verified deep dive with highlights, caveats, and a quickstart snippet.

Entries
2231
Categories
11
Official
93
Community
2138
Source sites
148
Deep dives
2231

Last updated . Entries are added as they appear and re-checked when they are touched.

Browse Jev by category

11 ways into the ecosystem. Each category page leads with its own shortlist of starting points.

All 2231 Jev resources

Search the full directory, or filter by category and tag.

Showing 14 of 2231 resources

TypeSafe AI's product site for Jev, its first System One Model: typed decisions with calibrated confidence, performance and pricing claims, a FAQ, and links to the docs, console, workflow evals, and launch post.
Jev Guides & ArticlesDocs#official#docs#models
Official
A TypeSafe blog essay arguing that in ML the order that matters is doing the right task, then data, then compute, then algorithms, using the InstructGPT result as its example.
Jev Guides & ArticlesArticle#official#article#models
Official
Cloudflare Workers AI's model page for typesafe/jev: run the structured evaluation model through an env.AI.run binding or the REST /ai/run endpoint, with typed Noul, Choice, and Score questions and worked examples.
Jev Tools & CLIsDocs#community#cloudflare#integration
Community
Wikipedia's article on Jev: TypeSafe AI, the September 15, 2026 early-access release of jev-1.13.0, the Choice, Score, and Noul primitives, RLCD training, and the unpublished weights and technical paper.
Jev Guides & ArticlesArticle#community#article#models
Community
The Register's launch report on TypeSafe AI's Jev: the $40 million raise, typed probabilistic decisions, the Doom demo, the 70-500 ms latency and $0.042/MTok pricing claims, and the structured-output caveat.
Jev Guides & ArticlesArticle#community#article#press
Community
Tom's Hardware's launch report on Jev, covering how the API takes program state and typed statements and returns yes/no answers, choices, or probability distributions with confidence values.
Jev Guides & ArticlesArticle#community#article#api
Community
Latent Space's AINews roundup of launch day: the Jev thread atop Hacker News, the RLCD decision-model framing, and community readings that compare it to DSPy-style typed signatures for routing and scoring.
Jev Guides & ArticlesArticle#community#article#models
Community
The Hacker News launch thread for Jev, with the CEO agreeing the shape is a zero-shot classifier and commenters mapping it to encoders, constrained decoding, and typed classification.
Jev Guides & ArticlesPost#community#models#evaluation
Community
News analysis arguing Jev's refusal to generate text is the feature, covering the $40M seed, the OpenAI-veteran founding team, and what structured, thresholdable decisions mean for agent pipelines.
Jev Guides & ArticlesArticle#community#article#models
Community
An independent benchmark of hosted Jev against six LLMs on PubMedQA, Banking77, and HelpSteer2, scoring decisions against human labels and reporting per-board results for each model.
Jev Practices & PatternsArticle#community#benchmarks#evaluation
Community
A Telegram channel X-ray that pulls up to 1,500 public posts from the past year and has Jev rate each one, tallying news, ads, jokes, and clickbait into a shareable card.
Jev CookbooksPlayground#community#playground#demos
Community
A semantic mapping playground where you choose any two concepts as axes, add words or phrases, and Jev places each one by how strongly it relates to both axes.
Jev CookbooksPlayground#community#playground#demos
Community
The model card for jev-1.13.0: $42 per billion input tokens with free output, a 64k context, 250k tokens per second, and how to list the models your account can call.
Jev Guides & ArticlesDocs#official#docs#models
Official
The idea behind Jev: models that return typed decisions and probabilities instead of generated text, named after Kahneman's fast-thinking System 1, with confidence to route around uncertainty.
Jev Guides & ArticlesDocs#official#docs#architecture
Official

Start here with Jev

Hand-picked entries the maintainers recommend first, from official primitives to community tools.

Published evaluations of four automation workflows, security incidents, agent trace observability, invoice processing, and customer service, comparing Jev and frontier LLMs as structured workflows versus single prompts.
Jev Practices & PatternsDocs#official#benchmarks#evaluation
Official
6GitHub stars
.NET SDK for the System One API with typed question sets, HttpClientFactory and dependency-injection wiring, plus Microsoft.Extensions.AI guardrail, routing, tool, and evaluator adapters.
Jev Repos & SDKs#community#sdk#csharp
A NativeAOT-ready .NET SDK generated from TypeSafe's OpenAPI definition, with typed question sets, batching, dependency injection, and Microsoft.Extensions.AI integrations.
Jev Repos & SDKs#community#sdk#csharp

Watch: Jev in action

Walkthroughs, tests, and demos from the community.

YouTube: KodeKloud's three-minute primer: what a System One model decides, and why it answers in milliseconds.

YouTube: Caleb Writes Code explains what Jev is and how to call it, in seven minutes.

YouTube: Greg Isenberg and Ryan Vogel on the businesses Jev unlocks, and a path in through the Vercel AI Gateway.

YouTube: CJ from Syntax demos browser use, classification, code review, a model router, and a chat bot with no LLM.

YouTube: Ryan Vogel runs Jev on 100 and then 1,000 emails: category, priority, spam, and reply predictions.

YouTube: AICodeKing tests support routing, refund detection, prompt-injection resistance, and browser automation.

Discussions about Jev

Threads from Reddit and Hacker News about building with Jev.

Hacker News: Show HN: Ad Spend Guard gates budget before the auction, not the creative after.

Show HN: Gating ad budget with a decision modelRead the thread on Hacker News

Reddit: Reranking rebooking options with a decision model, ranked with reasons.

Hacker News: Pick Verify: a single decision at the warehouse pick station catches confusable picks.

Show HN: Verifying robot picks with a decision modelRead the thread on Hacker News

Hacker News: Software Bombe and live Enigma demo where Jev ranks cribs and judges plaintext.

ag_212 pointsShow HN: Jev as the Bletchley Park Analyst: A Software Bombe on EnigmaRead the thread on Hacker News

Hacker News: Show HN for the decide CLI: brew install, file context, and multi-question shell scripts.

vsekhar2 pointsShow HN: Decide – Jev decisions in the shell, scripts, and agent skillsRead the thread on Hacker News

How entries are chosen

Every entry is hand-picked against the same bar, whether it comes from TypeSafe or the community.

  • Public and working — no paywalls, sign-up walls, or dead links.
  • Concrete — it has to be about Jev and the System One API, not generic LLM content.
  • Useful today — something a developer can learn from or use right now.
  • Distinct — if a similar entry exists, the description has to say what makes this one different: a different runtime, a cheaper path, a measured result, or a narrower focus.
  • Documented — repos state their license, and docs are in English or carry an English summary.

Spam, affiliate links, and thin AI-generated content are rejected. New entries are expected to ship with a deep dive: two to five highlights, caveats, a quickstart snippet where one helps, and a verification date. Star counts are refreshed when an entry is touched.

Common questions

Short answers about Jev and how this directory works.

What is Jev?

Jev is TypeSafe AI's first System One model. It takes a state plus typed questions and returns one structured answer per question — a choice, an ordered score, or the probability of yes — with calibrated confidence on Choice and Score answers, so code can branch on the result without parsing generated text.

What is the difference between Choice, Score, and Noul?

They are the three question primitives. Choice picks one of up to 255 options, Score rates on 2 to 10 ordered levels, and Noul answers yes or no. Choice and Score answers carry a confidence between 0 and 1; a Noul answer is the probability of yes.

Which Jev SDKs and client libraries are available?

TypeSafe maintains official JavaScript/TypeScript and Python SDKs plus a Python adapter. The community has built clients for Go, .NET, PHP, Laravel, Rust, Elixir, Ruby, and Scala, along with framework integrations such as DSPy, LlamaIndex, and Home Assistant. All of them are listed in the Repos & SDKs category.

Is the directory free, and is it affiliated with TypeSafe AI?

The directory is free to browse: every entry is hand-picked, and spam, affiliate links, and sign-up walls are rejected. JevDirectory.org is community-run and not affiliated with TypeSafe AI — Jev and System One are TypeSafe AI trademarks.

How often is the directory updated?

Entries are added as new resources appear and re-checked when they are touched. The directory currently holds 2231 entries from 148 source sites, last updated Oct 12, 2026.

What is a verified deep dive?

Most entries include a deep dive: two to five highlight bullets someone would only know from using the resource, a caveats note about limits and requirements, an optional quickstart snippet, and the date the link was last checked. 2231 of the 2231 entries carry one today.

For the canonical details, read the official TypeSafe docs and the API reference.

From the Jev community

Posts from builders shipping with Jev right now.

Follow @typesafeai