What is Task Decomposition?
Task decomposition is the process by which an AI agent breaks a complex goal into smaller, manageable sub-tasks that can be executed sequentially or in parallel.
WHY IT MATTERS
No agent solves complex problems in one step. Task decomposition transforms high-level goals into executable actions: check allocation, calculate trades, get quotes, execute sells, execute buys, verify results.
Effective decomposition requires planning ability — understanding dependencies, identifying parallelizable work, and handling individual step failures without losing overall progress.
For financial agents, decomposition quality directly impacts outcomes. Poor decomposition might execute trades in the wrong order or miss critical validation steps.
HOW POLICYLAYER USES THIS
When an agent decomposes a financial task into sub-steps, each sub-step involving spending needs independent policy validation. PolicyLayer evaluates every transaction in the chain — ensuring cumulative spending doesn't exceed budgets.