Home/Agentic AI/Workflow Patterns/Introduction
←
Previous Module
Orchestration Basics

Workflow Design Patterns

Master proven patterns for designing scalable, maintainable agent workflows

Your Progress

0 / 5 completed
1
2
3
4
5

Understanding Workflow Patterns

Workflow patterns are proven, reusable solutions to common design challenges in agent orchestration. Just as software design patterns help developers build better applications, workflow patterns help you build better multi-agent systems.

Why Patterns Matter

📚

Proven Solutions

Patterns have been tested in real-world systems

💬

Common Language

Team members understand "fan-out" instantly

⚡

Faster Development

Don't reinvent the wheel for every workflow

Interactive: Pattern Categories Explorer

Workflow patterns fall into three main categories. Explore each to see the patterns it contains.

CATEGORY: STRUCTURAL PATTERNS
How components are organized

Pipeline

Pattern 1

Linear chain of transformations

Example:
Input → Process → Transform → Output

Fan-Out/Fan-In

Pattern 2

Distribute work, collect results

Example:
Split data → Parallel processing → Merge results

Hierarchical

Pattern 3

Nested coordinator/worker structure

Example:
Manager delegates to team leads who delegate to workers

Pattern Selection Criteria

→
Task Independence
Can work be parallelized? Use fan-out/map-reduce
→
Coupling
Loose coupling? Event-driven. Tight coupling? Request-reply
→
Complexity
Many agents? Use hierarchical patterns for clarity
→
Latency
Need speed? Parallelize with fan-out or map-reduce

Combining Patterns

Real-world workflows rarely use a single pattern. You'll often combine multiple:

•Pipeline + Fan-Out: Sequential stages, with parallelization in the middle
•Hierarchical + Publish-Subscribe: Manager coordinates, broadcasts status updates
•Map-Reduce + Circuit Breaker: Distributed processing with fault tolerance

💡 Key Insight

Patterns are templates, not rigid rules. Adapt patterns to your specific needs. The "fan-out" pattern doesn't dictate how many workers or what they do—it just describes the structure of distributing work and collecting results. Your job is to fill in the details that make sense for your use case.