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AI Agents & Autonomy

Systems that plan and take actions toward goals — using tools, memory, and (often) other agents.

AI Agents & Autonomy is one of the core areas in the AI University map of AI. Explore the diagram, then dive into each topic — every subtopic grows into its own deep-dive over time.

flowchart TB
  G[/Goal/] --> PL[Plan] --> ACT[Act with tools] --> OBS[Observe]
  OBS --> Q{Goal met?}
  Q -- no --> PL
  Q -- yes --> DONE[/Result/]
  MEM[(Memory)] -.-> PL

Key topics

  • Agent architectures

    Perceive–reason–act loops, ReAct, and planner/executor designs.

  • Tool use & function calling

    Letting models call APIs, run code, search, and act in the world.

  • Planning & reasoning

    Decomposing goals into steps; reflection and self-correction.

  • Memory

    Short- and long-term memory, and retrieval to persist context across steps.

  • Multi-agent systems

    Orchestrating specialised agents that collaborate or debate.

  • Orchestration & safety

    Guardrails, sandboxing, and human-in-the-loop for autonomous systems.

NLP & Large Language Models · Reinforcement Learning · Building with AI · AI Safety, Alignment & Ethics

Learn this properly

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