Independent field guide
Jev returns decisions, not text.
Here is how to use it well.
TypeSafe AI’s System One model answers typed questions against a state and hands back calibrated probabilities. It is fast, cheap, and genuinely different. It also has documented sharp edges that cost people accuracy in production. This site covers both.
- Input price
- $0.042
- per Mtok
- Output price
- Free
- no output cost
- Primitives
- 3
- choice · score · noul
- Context
- 64k
- tokens per request
Start here
What Is Jev? A System One Model, Explained Without the Marketing
Jev returns typed decisions and probability distributions instead of text. Here is the mental model, what actually comes back, and who should care.
9 min readFundamentals'It Can't Hallucinate' — What That Claim Actually Means
Type safety guarantees schema conformance, not factual correctness. What Jev genuinely rules out, what it doesn't, and why the distinction matters.
8 min readEngineeringHow to Use Jev Correctly: 9 Documented Failure Modes
TypeSafe documents nine ways jev-1.13 gets things wrong. Here is what each one looks like in production and how to engineer around it.
12 min readInteractive courses
Three courses, beginner to advanced, built around exercises you work through in the browser rather than code you read.
More guides
What Jev Actually Costs
Real pricing, real rate limits, the 64k/32k context budget, and why the headline 444.6x cheaper claim lands closer to 30x in practice.
Jev Is Not an LLM, and That's the Whole Point
No string output means parallel evaluation means free output tokens. The architectural tradeoff behind Jev, and where the story gets muddy.
Understanding Confidence and Calibration
Confidence is derived from the probability distribution, not reported separately. How it's computed, why Noul has none, and how to set thresholds.
Your First Jev Integration, End to End
curl to Python to TypeScript: the request shape, reading answers correctly, error handling with backoff, and why you should pin the version.
Four Architectural Patterns for Building with Jev
Speculative fan-out, confidence-gated routing, composite scoring, and intent routing, with working code for each.
Atomic Questions: The Skill That Decides Whether Jev Works for You
Decomposition is the whole job. Broad questions hide judgments; atomic ones expose them so your code can inspect, tune, and combine them.