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 |