5 AI Automation Patterns Every Developer Should Know

AI agents are not magic. Under the hood, they follow repeatable patterns that you can learn, combine, and apply to your own projects. Here are five patterns that I have seen work across dozens of real-world implementations. Pattern 1: The Triage Router Instead of building one monolithic agent, create a lightweight router that classifies incoming requests and delegates to specialized sub-agents. User Request → Triage Agent → [Support Agent | Sales Agent | Technical Agent] When to use it: When your agent needs to handle multiple domains. A customer might ask about billing, technical issues, or product features — each requires different context and capabilities. Implementation tip: Keep the router simple. It only needs to classify intent, not solve problems. The specialized agents handle the heavy lifting. Pattern 2: The Retrieval-Action Loop The agent retrieves relevant context from a knowledge base, reasons about it, takes an action, then checks the result. Query → Retrieve Context → Re