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Articles.

Field notes from the studio on applied AI, typed model judgments, and the tools we use to ship them into production software.

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  1. 7 min read

    What is Jev? TypeSafe's System One Decision Model Explained

    Jev answers typed questions about your data with calibrated probabilities, and never writes a word of prose. What it is, how it differs from an LLM, and where it fits in real software.

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  2. 6 min read

    Choice, Score and Noul: The Three Question Types

    Every question you ask Jev is a Choice, a Score or a Noul. Here is what each one returns, how to pick between them, and how to compose them into decisions your code owns.

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  3. 6 min read

    Decision Models vs LLMs: When Not to Generate Text

    Most AI features need a decision, not a paragraph. How decision models like Jev differ from LLMs, and a practical test for when to stop generating text.

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  4. 5 min read

    Confidence vs Probability: When to Let Jev Act and When to Escalate

    An AI answer is only half a decision. The other half is knowing when not to trust it. How Jev separates probability from confidence, and how we set the thresholds.

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  5. 6 min read

    Speculative Fan-Out: Ask Every Question in One Call

    Ask every question you might need, in one request, and let code ignore the rest. Why that is cheaper and faster than branching, and when a second call is genuinely required.

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  6. 6 min read

    Jev on OpenRouter: The Decisions API, Pricing and Latency

    OpenRouter serves Jev through a separate decisions endpoint, not chat completions. Here is the request shape, what it costs, and how fast it answered for us.

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  7. 6 min read

    How We Built a Claude Code Model Router with Jev

    Not every message to a coding agent needs the biggest model. How we used Jev to size each request and hand small jobs to Haiku and Sonnet, including the limits we hit.

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  8. 7 min read

    Picking the Right AI Agent Skill with Jev

    Agents pick skills from a cramped one-line index and often guess wrong. Here is how we put Jev in front of that choice, and what it costs.

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  9. 7 min read

    AI Guardrails and Citation Checks with a Decision Model

    A guardrail should hand you evidence, not make your policy for you. How we use Jev to screen LLM traffic and catch citations that do not hold up.

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  10. 6 min read

    Triage at a Fraction of a Cent: Sorting Emails, Leads and Tickets with Jev

    Sorting a pile of text is a decision problem, not a writing problem. Our Jev triage setup, what one email cost, and the rules we use when Jev is unsure.

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