Foundations
Planning and Reasoning in AI Agents
When agents need explicit plans, how plans change, and why execution feedback matters more than elegant reasoning.
Plans reduce ambiguity
For multi-step work, a short plan gives the agent a sequence of verifiable milestones. It also gives users and developers a visible structure for reviewing progress.
Plans should stay editable
Tool results can invalidate an assumption or reveal a shorter path. Strong agents revise plans when evidence changes rather than following an outdated checklist mechanically.
Reasoning needs grounding
A persuasive explanation is not proof that a task succeeded. Reliable agents connect claims to observations such as test output, retrieved records, or explicit confirmations.