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    AI harness

    An AI harness is the orchestrated rig around a model where governance actually lives — tools, memory, permissions, review paths, escalation, outcome boundaries. In Prompted LLC's usage, harnesses are the unit governed by Ubiquity.

    Plain definition

    An AI harness is the surrounding system that gives a model context, tools, permissions, memory, review paths, and outcome boundaries. The model reasons; the harness governs.

    Why it matters

    Most discussion of "AI safety" or "AI governance" targets the model. The governable surface is the harness, not the model. Naming the harness as a distinct architectural unit is what makes earned autonomy operational.

    What it is not

    • A Hugging Face model release format.
    • A Ray Serve deployment primitive.
    • A prompt template, system prompt, or persona.
    • A specific framework — harness is an architectural role, not a vendor SKU.

    Where it appears in Ubiquity

    Ubiquity governs harnesses. See /ai-harnesses for the full term page.

    Ladder context

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    Related terms

    Frequently asked

    What is an AI harness?
    The runtime apparatus around a model: orchestration, tools, memory, review surfaces, escalation paths. The unit governed by Ubiquity.
    How is a harness different from a model?
    The model reasons. The harness decides what the model can act on, what it must ask about, and what happens after action.
    How is a harness different from an agent framework?
    A framework is a SKU. A harness is an architectural role any framework can play with the right primitives.
    Why does governance live in the harness?
    Because the model is opaque, replaceable, and improving. The harness is where the organization actually decides what AI may do.

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