Agent Scaffolding

Agent scaffolding refers to the software architecture and tooling built around a large language model to enable complex, goal-driven task execution. It places the model within a control loop that includes memory, tools, and decision logic, allowing it to observe context, reason through steps, take actions, and iterate until objectives are met. This approach relies on surrounding components such as prompt templates, retrieval systems, function calls, action handlers, and coordination logic to structure workflows rather than using single, free-form prompts. Agent scaffolding augments core model capabilities by enabling observation and action loops, tool usage, and stepwise reasoning, making agents more effective, reliable, and purpose-driven across complex tasks.