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Planning component

As explained in Introduction to Generative AI, Second Edition

A planning component is an agent subsystem that constructs a trajectory or sequence of actions for completing a task.

A planning component is an optional agent subsystem that constructs a trajectory—a sequence of actions—for a complex task. Instead of reasoning through one tool call at a time, an agent can plan subtasks first, then execute them. This can reduce sequential delays and support parallel work, while dependencies between subtasks still limit what can run simultaneously. section 8.12

Planning addresses several weaknesses of a simple action loop:

  • It can prevent an agent from becoming stuck in repeated reasoning or action cycles, although execution still needs an action limit. section 8.12
  • It can divide a larger task into independent subtasks and send those subtasks to multiple tools simultaneously. section 8.12
  • It works best when tasks contain parallelizable work; steps that depend on earlier tool results must remain sequential. section 8.12

Complex software work

For a task such as code generation evaluated through SWE-bench, an agent may first plan its trajectory, separate independent activities, execute them concurrently where possible, and then review the result through reflection. section 8.12

Figure 8.8 A sample execution flow for a task with planning and parallelization
A diagram of a diagram

AI-generated content may be incorrect.

A flow diagram can clarify how planning precedes execution and enables parallel actions. section 8.12

How Introduction to Generative AI, Second Edition covers it

How deep it goes
Explains the role, benefits, and limits of planning but stops short of implementation details.
Examples
Uses SWE-bench, code generation, multiple searches, and dependent tool-call sequences as examples.
What you can do after
Apply it to structure multistep agent work and identify opportunities and limits for parallel execution.
How it connects
Connects planning with agent architectures, tool calls, parallelization, memory, and reflection.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Introduction to Generative AI, Second Edition. The section links point to the parts of the book it draws on.