.svg){kind=small}
01 / 05
What are AI Agents?
Understanding the difference between chatbots, copilots, and autonomous agents.
Key takeaways
AI agents are LLMs that can reason and take real actions through tools
They combine a system prompt, tool access, and guardrails
Unlike chatbots, agents complete multi-step tasks autonomously
Modern models are now reliable enough for production use cases
Beyond chatbots
A chatbot responds to questions. An AI agent takes action. Powered by large language models like GPT, Claude, and Gemini, agents can reason through multi-step problems, decide which tools to use, and execute tasks — calling APIs, querying databases, sending emails, updating records — all from a natural language instruction.
How agents work
At the core, an agent is a language model paired with a system prompt (its instructions and persona), a set of tools (APIs and functions it can call), and guardrails (rules about what it can and cannot do). When given a task, the model reasons about which tools to use, calls them, interprets the results, and decides what to do next — repeating until the task is complete.
Why now
Language models have reached a level of reasoning ability where they can reliably follow complex instructions, use tools correctly, and handle ambiguity. Combined with frameworks for tool-use, tracing, and evaluation, it's now practical to deploy agents for real business workflows — not just demos.