Planning (AI)

Planning is the cognitive capability that enables AI agents to decompose complex goals into manageable sub-tasks, sequence those sub-tasks appropriately, and adapt the plan as new information becomes available. It is the process by which an agent figures out how to achieve its objective. When given a goal like 'prepare a competitive analysis report', a planning-capable agent might decompose this into: identify key competitors, gather financial data for each, analyse market positioning, compare product offerings, synthesise findings, and format the report. The agent determines which tools to use at each step and what information to carry forward. Planning approaches range from simple (single-pass plan generation) to sophisticated (iterative replanning based on results, tree-of-thought exploration of alternative approaches, and hierarchical task decomposition). More capable planning produces more reliable and efficient agent behaviour, particularly for complex, multi-step tasks.

Planning capability determines the complexity of tasks an AI agent can handle reliably. Simple agents without planning can execute single actions. Agents with strong planning can tackle the kind of multi-step, open-ended tasks that constitute valuable knowledge work. For businesses, planning-capable agents can handle tasks like: researching and compiling reports, investigating customer issues across multiple systems, preparing meeting briefings from various data sources, and coordinating multi-step approval workflows. These tasks previously required human judgment about sequencing and approach. The quality of planning also affects efficiency and cost. A well-planned approach completes tasks in fewer steps with fewer wasted tool calls. Poor planning leads to unnecessary actions, redundant information gathering, and higher latency and token costs.