Understanding AI Agents: Architecture and Patterns

What Are AI Agents?

AI agents represent the next evolution beyond simple chatbots. They can plan, use tools, and execute multi-step tasks autonomously.

Core Architecture

A typical AI agent consists of:

LLM Core — The reasoning engine

Tool Use — APIs and functions the agent can call

Memory — Short-term (conversation) and long-term (persistent)

Planning — Task decomposition and execution strategies

Common Patterns

#### ReAct Pattern The most popular pattern: Reason → Act → Observe → Repeat

Thought: I need to find the user's order status
Action: query_database(order_id=12345)
Observation: Order shipped on March 28
Thought: I can now respond with the status

#### Multi-Agent Systems Multiple specialized agents collaborating on complex tasks. One agent plans, another researches, another executes.

Building Your First Agent

Start simple. Use a framework like LangGraph or Claude's tool use API to build a basic agent, then add complexity as needed.

The Future of Agents

Expect agents to become the primary interface for software interaction within the next 2-3 years.