AI Agent Knowledge Library

Reasoning & Planning

How AI agents reason, decompose tasks, make decisions, plan actions, reflect on outcomes, and adapt their behavior.

3 Published resources

Explore: Foundations Memory & Context Tools & Actions Multi-Agent Systems

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An AI agent compares an action result with success criteria, identifies a gap, and sends a correction back into the agent loop.

Explainer Beginner

Reflection in AI Agents: How Agents Review, Correct, and Improve Their Work

Learn how AI agents use feedback, critique, and execution review to detect mistakes, revise their approach, and improve results without endless retry loops.

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3 published articles

An AI agent converts a goal into connected tasks, uses tools, and adjusts its route after feedback.

Explainer Beginner

Planning in AI Agents: From Goals to Adaptive Action

Learn how AI agents turn goals into ordered tasks, account for dependencies and constraints, use tools, track progress, and replan when reality changes.

Goal, context, constraints, and options flow into an AI agent reasoning core, which produces a decision and next action.

Explainer Beginner

Reasoning in AI Agents: How Agents Decide What to Do Next

Learn how AI agents interpret goals, break down tasks, handle uncertainty, choose tools, reflect on results, and decide what to do next.