Guide 01 / 10
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, such as calling APIs, querying databases, sending emails, and 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.