Planning and decomposition
A step-by-step agent is short-sighted. Planning writes the subtasks and their dependencies first — and treats the plan as a hypothesis, not a script.
A purely reactive agent chooses each step by looking only at what has happened so far — which is short-sighted. Planning asks the model to write the shape of the work first: what the subtasks are, and which ones depend on which. The plan is not the answer; it is a map the agent follows, checks against reality, and revises.
Start here
Decomposition is the whole game. A goal that is too big to do in one step becomes tractable once you split it into pieces small enough to verify — and the dependencies between those pieces tell you what can run at once and which step is on the critical path.
One goal, decomposed — then run the independent parts at once
scope the page
2u
write copy
3u
design layout
3u
build page
4u
test & fix
2u
deploy
1u
makespan
12u
A plan makes dependencies explicit, which is what lets the independent branches run together — and what tells you which step is on the critical path. It is also a hypothesis: when a step returns something unexpected, the agent re-plans rather than grinding through a stale script. Durations are illustrative.
Toggle sequential and parallel execution on the same decomposition.
Plan-and-execute
The pattern is two phases:
- Plan — the model produces an ordered set of subtasks, often with dependencies, before touching a tool.
- Execute — the agent works the list, and when a step returns something surprising, it re-plans rather than forcing the old script.
This separates "what should happen" from "do it", which makes the plan inspectable — a human can read and correct it before any action is taken.
How to decompose
- Least-to-most — solve the easiest sub-problem first, then use its answer to make the next one easier. Good when the sub-problems chain.
- Hierarchical — break the goal into sub-goals, then sub-sub-goals, until each leaf is a single tool call or a short thought.
- Dependency-first — identify what must happen before what; the ordering is often the hard part, not the individual steps.
Careful
A plan is a hypothesis about a task the agent has not done yet, so it can be wrong. Two failure modes: over-planning, where the agent spends its budget writing an elaborate plan for a task it could have just done, and premature commitment, where it grinds through a stale plan after the first step proved it wrong. The skill is a plan detailed enough to guide, loose enough to revise.
Check yourself
Eduspheria wiki · Agentic AI, Planning & reasoning
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Next: the reasoning that happens inside each step.