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Multi-Agent Classification Framework

Reusability

A workflow design pattern that uses a classifier agent to route users to specialized agents based on their type or intent, rather than using one general-purpose agent for all tasks

How It Works

Input flows to a classifier agent that analyzes the request and determines user type, then routes to appropriate specialized agents (e.g., support vs sales) with specific training and tools

Components

1

Create classifier agent with clear examples of each user type

2

Build specialized agents for each user category

3

Define routing logic based on classifier output

4

Connect specialized agents to appropriate tools and data sources

5

Implement feedback loops for classification accuracy

When to Use

When you have distinct user types with different needs, when tasks require specialized knowledge or tools, when you want to optimize agent performance for specific scenarios

When Not to Use

For simple single-purpose applications, when user types overlap significantly, when the classification logic is too complex to be reliable

Anti-Patterns to Avoid

Making the classifier too complex with too many categoriesNot providing enough examples for classification trainingCreating overlapping agent responsibilitiesSkipping classification validation steps

Example

A SaaS company chatbot that classifies visitors as existing customers (routes to support agent with knowledge base) or potential leads (routes to sales agent that collects qualification data)