A small game to show how fast TypeSafe's Jev actually is. Try to beat it at detecting a spam message beatjev2it.jlamberts86.workers.dev
Patterns
Intent routing
Classify intent with a Choice and complexity with a Score, then send each branch to deterministic code, a specialist model, or a person.
- Category
- Patterns
- Also known as
- —
- Related terms
- 5
- Directory entries
- 37
- Docs
- docs.typesafe.ai
- Added
- 2026-09-24
Definition
The example asks one Choice over order status, product questions, returns, and complaints, plus a Score for complexity. Intent confidence below 0.5 routes to a human agent, order_status goes to deterministic code with no LLM involved, and complaints escalate when complexity exceeds level 1 or its confidence falls below 0.5.
The routing rule is on the pair of answer and confidence, not either alone, so confidently-misrouted requests do not slip past review.
Tagspatternsroutingclassification
Related terms
Definitions that connect to this one.
Confidence-gated routingUse the answer to decide what to do and confidence to decide whether to act, with per-action thresholds set by the cost of being wrong.PatternsChoicePick one option from a set you define; returns the selected option, a probability for every option, and confidence.PrimitivesScoreRate the state against 2 to 10 ordered levels; returns a probability-weighted position, per-level probabilities, and confidence.PrimitivesConfidence floorA baseline below which code never acts on an answer, regardless of what the answer says.Answers & ConfidenceAgent loopA control pattern where the model chooses its next step repeatedly; TypeSafe's guidance is to prefer a code-owned workflow instead.Core Concepts
From the directory
Classify intent with a Choice and complexity with a Score, then send each branch to deterministic code, a specialist model, or a person, with a 0.5 intent-confidence floor.
Practices & PatternsDocs#official#patterns#routing
Official
Architectural patterns for System One systems: speculative fan-out, confidence-gated routing, composite scoring, and intent routing.
Practices & PatternsDocs#official#patterns#architecture
Official
302GitHub stars
A TypeScript layer beside an LLM: JevSift selects approaches, JevLoop audits progress with typed actions, and JevLong watches sessions for stalls without steering them.
Tools & Integrations#community#typescript#coding-agent
Community
Alex314618-create/JevRevTypeScript
Alex314618-create/JevRevTypeScript4GitHub 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.
Repos & SDKs#community#sdk#csharp
Community
Hawxy/TypeSafeAI.NetC#
Hawxy/TypeSafeAI.NetC#0GitHub stars
A community Rust port of the official Python SDK with the same primitives, wire format, retries, and error semantics, plus derive macros for typed questions and answers.
Repos & SDKs#community#rust#sdk
64GitHub stars
A Home Assistant integration that turns Jev questions about entity state into sensors and automation actions, with an Assist conversation agent and a daily token budget.
Repos & SDKs#community#python#home-assistant
Community
AboveColin/HA-JevPython
AboveColin/HA-JevPython31 more matching entries in the full directory.
From the community
Posts from builders shipping with Jev right now.
A game where you race Jev at spotting slop
Jev plays itself at 3D chess
got access to jev and instead of doing anything useful i made it play itself at 3D chess same model on both sides, slowly developing beef with itself you can watch jev vs jev or jump in and ruin its day chess-jev.loomens.com
@CompleteSkeptic
After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x
dmx.to reshapes the timeline in plain language
the next version of dmx.to will let you fully customize the timeline both with dumb rules (how did i not think of these until now lol) and smart rules using Jev (BYOK also supports vercel gateway) 🤓 you can filter 3 lvls of usefulness, tweet types, topics, etc
GPT and Jev compared live
Built a live tool using @typesafeai JEV ! See live comparison btwn GPT & JEV at gptvsjev.vercel.app Get benchmarks like Money Spent ! Time Taken ! Tokens Used!
LitJev: Jev-style decisions on any local LLM
开源了 LitJev：我们对 Jev 类型化决策 API 实现方式的猜想，可接入任意现成 LLM。 小测试：Qwen3.8-27B，10 道 MMLU-Pro 一次完成，0.3 s。比让模型只生成答案快 2.9x；比生成完整 schema JSON 快更多（显然）。更多测试马上来。 非官方，基于公开信息。
Secret detection with Jev, tested
Built a quick Secret Detection Test with Jev by @typesafeai Results seem promising so far, ran it a few times and it's pretty consistent as well. github.com/teyhouse/jev-s…
