Planning Agent
An agent specialized in creating structured plans for accomplishing complex goals, including task ordering, resource allocation, and dependency management. Planning agents define what to do before execution begins.
Planning agents separate the strategy phase from execution. Given a complex objective, a planning agent analyzes requirements, identifies subtasks, determines dependencies between them, estimates resource needs, and produces a structured execution plan. This plan is then handed to execution agents or workflows that carry out the individual steps.
For growth teams managing complex initiatives, planning agents can accelerate project kickoff. A product launch planning agent might decompose the launch into marketing, engineering, support, and sales workstreams, identify cross-team dependencies, and propose a timeline. The plan serves as both an execution guide and a communication artifact. The key to effective planning agents is grounding them in realistic constraints: available resources, timeline boundaries, and organizational capabilities. Without constraints, planning agents tend to produce idealized plans that do not survive contact with reality. Feed your planning agent context about team capacity, budget limits, and historical velocity for more actionable plans.
Related Terms
Model Context Protocol (MCP)
An open standard that defines how AI models connect to external tools, data sources, and services through a unified interface. MCP enables agents to dynamically discover and invoke capabilities without hardcoded integrations.
Tool Use
The ability of an AI model to invoke external functions, APIs, or services during a conversation to perform actions beyond text generation. Tool use transforms language models from passive responders into active problem solvers.
Function Calling
A model capability where the AI generates structured JSON arguments for predefined functions rather than free-form text. Function calling provides a reliable bridge between natural language understanding and programmatic execution.
Agentic Workflow
A multi-step process where an AI agent autonomously plans, executes, and iterates on tasks using tools, reasoning, and feedback loops. Agentic workflows go beyond single-turn interactions to accomplish complex goals.
ReAct Pattern
An agent architecture that interleaves Reasoning and Acting steps, where the model thinks about what to do next, takes an action, observes the result, and repeats. ReAct combines chain-of-thought reasoning with tool use in a unified loop.
Chain of Thought
A prompting technique that instructs the model to break down complex problems into sequential reasoning steps before producing a final answer. Chain of thought significantly improves accuracy on math, logic, and multi-step tasks.