Agent Architecture Patterns

Learning Objectives Understand the four main agent architecture patterns Know when to use each pattern based on your problem Avoid over-engineering by choosing the simplest pattern that works The Architecture Decision The biggest mistake in agent development is reaching for complex architectures too early. A single agent with good tools handles 80% of use cases. Multi-agent systems are powerful but introduce coordination complexity that is hard to debug and maintain. Start simple. Add complexity only when the simple approach fails. Pattern 1: Single Agent (Start Here) What it is: One AI model with access to multiple tools, handling the entire task. When to use it: The task can be described in a single prompt All required tools can be given to one model The context window is large enough for the full conversation You are building your first agent Example: A research agent that searches the web, reads documents, analyzes data, and produces a report. One model orchestrates all of these tools. Strengths: Simple to build, easy to debug, low latency, predictable costs. Weaknesses: Can struggle with very complex tasks that require different "mindsets" (creative writing vs. data analysis in the same task). Implementation tip: Give the agent a clear system prompt that defines its role, available tools, and when to use each one. The better the system prompt, the less you need multiple agents. Pattern 2: Router (Add When Needed) What it is: A lightweight "triage" agent that reads the user's request and routes it to the appropriate specialized…