What is an AI agent?

An AI agent is a software system that uses a large language model (LLM) to autonomously perform tasks, make decisions, and interact with external tools and APIs. Unlike a chatbot that only responds to questions, an agent can plan multi-step actions, use tools, and pursue goals independently.

Architecture: an AI agent combines an LLM (the reasoning engine) with a set of tools (API calls, database queries, web searches, code execution) and a memory system (conversation history, retrieved context). The LLM decides which tools to use, in what order, and how to interpret results.

Examples: a customer support agent that reads tickets, queries the knowledge base, drafts responses, and escalates complex issues to humans. A sales agent that researches prospects, personalizes outreach, books meetings, and updates the CRM. A data analysis agent that writes SQL queries, runs them, interprets results, and generates reports.

What makes an agent different from a chatbot: autonomy (acts without step-by-step instructions), tool use (interacts with external systems), planning (breaks complex tasks into steps), and memory (maintains context across interactions).

Production considerations: guardrails (prevent the agent from taking harmful actions), human-in-the-loop (approval required for sensitive operations), cost management (LLM calls add up), latency (multi-step reasoning takes seconds), and evaluation (how do you measure agent quality?).

The technology is real but early. Voice AI agents for phone calls are production-ready. Fully autonomous business process agents still need human oversight for critical decisions.