AI Agent

An AI Agent is an autonomous system that perceives its environment, makes decisions and takes actions to achieve goals. Unlike a one-shot chatbot, an agent plans, uses tools, observes results and iterates until the goal is met.

How it works

1. 1Perceive: gather information from the environment (user input, web, APIs, databases).
2. 2Reason: understand the goal and decide what to do (the LLM is the brain).
3. 3Plan: break the goal into steps and choose tools.
4. 4Act: use tools and take actions in the world.
5. 5Observe: observe results and get feedback.
6. 6Adjust & repeat: learn from feedback and improve until the goal is achieved.

Key points

• Agent core = goal + reasoning (LLM) + planning + action + observation.
• Uses memory: short-term (conversation), long-term (knowledge base) and vector stores.
• Interacts with tools: web search, code, databases, email and more.
• Types include simple reflex, model-based, goal-based, utility-based and learning agents.

Why it matters

Agents move AI from answering questions to accomplishing tasks. By combining reasoning, tools and a control loop, they can carry out multi-step work like research, automation and coding.

Frequently asked questions

What makes something an 'agent' vs a chatbot?

An agent plans, uses tools, observes results and loops toward a goal, rather than replying once.

Why do agents need memory?

To keep context and task state across steps and sessions, so multi-step work stays coherent.