Building AI Agents: Architecture Patterns for Production

What Is an AI Agent?

An AI agent is an AI system that can:

• Use tools (call APIs, run code)
• Maintain state across interactions
• Execute multi-step plans
• Make decisions autonomously

Core Architecture

1. The Loop

1. Receive user input
2. Decide action (think)
3. Execute action (tool use)
4. Observe result
5. Repeat until done

2. Tool Definition

Define what the agent can do:

{
  "name": "search_docs",
  "description": "Search documentation",
  "parameters": {
    "query": "string"
  }
}

3. Memory Management

• Short-term: Current conversation
• Long-term: User preferences, past interactions
• External: Vector DB for knowledge

Key Patterns

ReAct (Reason + Act)

Think about what to do, then do it. Most common pattern.

Tool Use

Let the model call functions. Essential for agents.

Planning

Break complex tasks into steps. Use structured output.

Reflection

Have the agent review its own work. Improves quality.

Production Considerations

• Reliability: Add timeouts, retries
• Observability: Log all decisions
• Safety: Limit destructive actions
• Cost control: Track token usage

Popular Agent Frameworks

Framework	Best For
LangChain	Flexibility
AutoGen	Multi-agent
OpenAI Agents	Simplicity
Claude Agent	Coding tasks