Agent Loop
An agent loop is the iterative execution cycle of an AI agent in which it reasons about the current state, selects and executes an action (often a tool call), observes the result, and repeats until the task is complete or a stopping condition is reached.
Understanding Agent Loop
The agent loop is the fundamental unit of agentic AI behavior. Unlike a single LLM call that produces one response, an agent loop allows the model to take multiple steps, use tools, observe results, and adjust its approach based on what it learns along the way. A typical agent loop iteration follows the ReAct (Reason + Act) pattern: Thought (what does the current state tell me, and what should I do next?) → Action (execute a specific tool call or operation) → Observation (what did the tool return?) → Repeat or complete. Agent loops enable qualitatively more powerful behavior than single LLM calls. A single call can draft an email. An agent loop can: read your inbox, identify emails needing replies, check your calendar for meeting context, draft a reply informed by that context, create a follow-up task, and send the reply — all in sequence, with each step informing the next. The challenge of agent loops is reliability and cost. Each iteration consumes tokens and takes time. Loops can get stuck in error conditions or pursue incorrect paths. Robust agent systems include maximum iteration limits, error recovery mechanisms, and human-in-the-loop checkpoints for long-running tasks.
How GAIA Uses Agent Loop
GAIA uses agent loops for complex multi-step workflows. When you ask GAIA to handle your morning email routine, for example, GAIA's agent loop reads the inbox, triages each message, drafts replies for non-urgent items, creates tasks for action items, and schedules follow-ups — executing each step sequentially with the output of one step informing the next.
Related Concepts
Agentic AI
Agentic AI describes artificial intelligence systems designed to operate autonomously, making decisions and executing multi-step tasks with minimal human oversight.
Autonomous Agent
An autonomous agent is an AI system capable of independently perceiving its environment, making decisions, and taking actions to achieve specified goals without requiring human input at each step.
Tool Use
Tool use is the capability of AI agents to invoke external functions, APIs, databases, and services to retrieve information or take actions in the real world beyond generating text.
Function Calling
Function calling is a feature of AI models that allows them to generate structured, machine-readable invocations of predefined functions, enabling AI systems to reliably call external APIs and tools with the correct arguments.
Human-in-the-Loop
Human-in-the-loop (HITL) is a design pattern where an AI system includes human oversight and approval at critical decision points, ensuring that sensitive or high-impact actions require human confirmation before execution.
