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Knowledge mapAI and agents

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LEARN / AI and agents

From model capability to bounded action

Connect agents to identity, personal data, tools and execution, then explore applications and blockchain.

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  1. 01
    From AI to agents that act

    Explore agent systems through identity, data and execution.

    5 questions

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01

AI and agents

Concepts, products and related approaches

  1. AI, models and applications

    Separate a field, a model capability and a running application.

  2. How does an AI agent move from answers to actions?

    Understand goals, tools, feedback and stopping conditions.

    Builds on ↑AI, models and applications
  3. Are agent identity and permission the same?

    Separate persistent naming, proof of control and authority for an action.

    Builds on ↑How does an AI agent move from answers to actions?What does a DID identify?
  4. Who owns an agent’s memory?

    Distinguish personal records, task context and transient execution state.

    Builds on ↑How does an AI agent move from answers to actions?How does a personal data space differ from an app database?
  5. Why does an agent need an execution environment?

    A model proposes operations; the environment executes them and holds state.

    Builds on ↑How does an AI agent move from answers to actions?