Genial 👍
The anatomy of an AI agent, explained simply:
1. Perception: Receives input from users, APIs, files, or sensors.
Example: You ask an agent to summarize your emails.
2. Reasoning: The LLM understands the request and decides what to do next.
3. Planning: Breaks a complex task into smaller steps.
Example: Find emails → identify important ones → summarize them.
4. Memory: Stores conversation context and retrieves relevant past information.
5. Tool execution: Uses APIs, MCP, databases, browsers, or code to perform actions.
6. Guardrails: Controls permissions, checks risky actions, and requests human approval when needed.
7. Observability: Tracks logs, errors, latency, and costs so developers can debug the agent.
How it works:
Input → Reason → Plan → Use tools → Check results → Repeat until the task is complete.
An AI agent isn't just an LLM. It's a system that combines models, tools, memory, and control mechanisms to get things done.
