ModelRefs / Task Decomposition — AI Glossary
Task Decomposition — AI Glossary
Breaking a complex high-level goal into smaller, actionable sub-tasks that an agent or agent network can execute sequentially or in parallel.
Overview
Task decomposition is a core planning capability: the agent generates a task list or directed acyclic graph of subtasks before execution. Methods: Plan-and-Execute (LangChain), LangGraph state machine planning, tree-of-thought branching. Quality of decomposition determines agent success on complex multi-step problems.
Reference details
| Topic | agents |
|---|---|
| Last reviewed | 2026-06-24 |
Related terms
Commonly confused with
One step within planning: turning a goal into a set of sub-tasks, often as a list or a dependency graph. It is not the same as the plan being good — a correct decomposition executed in the wrong order, or never revised, still fails. Where the output is a graph, it is a DAG, which is what makes independent branches parallelisable.
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Frequently asked questions
What is Task Decomposition?
Breaking a complex high-level goal into smaller, actionable sub-tasks that an agent or agent network can execute sequentially or in parallel.
What concepts are related to Task Decomposition?
Closely related concepts include dag, parallel execution, least to most prompting.