Workflow Design Patterns

Master proven patterns for designing scalable, maintainable agent workflows

Key Takeaways & Summary

You've explored how workflow design patterns provide proven solutions to common orchestration challenges. From fan-out for parallelism to event-driven flows for loose coupling to hierarchical structures for managing complexity—you now have a toolkit of patterns to draw from when designing agent systems.

📚

Patterns are Proven Solutions

Workflow patterns capture years of collective experience. Using established patterns saves time and reduces risk compared to designing from scratch.

Fan-Out Maximizes Parallelism

Distribute work to multiple agents, process concurrently, then aggregate results. Essential for high-throughput systems with independent tasks.

🎯

Map-Reduce for Distributed Processing

Specialized fan-out pattern: map chunks to processors, shuffle by key, reduce to final results. The foundation of big data systems.

📢

Events Enable Loose Coupling

Event-driven architectures decouple publishers from subscribers. Add/remove components without changing core logic—highly maintainable and scalable.

🔄

Async Beats Sync for Workflows

Event-driven flows are inherently asynchronous. Don't block waiting for responses—let components react independently and in parallel.

🏗️

Hierarchies Scale Complexity

Manager-coordinator-worker structures mirror organizational hierarchies. Each level abstracts complexity from the level above.

⚖️

Balance Depth and Breadth

Shallow hierarchies (few levels) communicate faster but risk manager overload. Deep hierarchies (many levels) add coordination overhead. Find the balance.

🧩

Combine Patterns for Real Systems

Real workflows mix patterns: hierarchical structure with event-driven communication, fan-out within pipeline stages, etc. Be flexible and pragmatic.

📊

Pattern Selection Depends on Context

Task independence → fan-out. Loose coupling → events. Complex systems → hierarchical. Analyze your requirements before choosing patterns.

🎨

Patterns are Templates, Not Rules

Adapt patterns to your needs. The "hierarchical pattern" doesn't dictate exact structure—it provides a mental model you customize for your domain.

🎓

What You've Learned

Three major pattern categories: structural, behavioral, and distributed

Fan-out/fan-in pattern for parallelizing independent tasks

Map-reduce specialization for distributed data processing

Event-driven architecture with publish-subscribe pattern

Hierarchical patterns for managing organizational complexity

How to select appropriate patterns based on requirements

💡 Final Insight

Patterns accelerate development, but understanding beats memorization. Don't just copy pattern implementations—understand why they work, when they apply, and how to adapt them. The best workflow designers know the patterns but aren't bound by them. They mix, modify, and invent when needed, guided by principles rather than rigid templates.

Pattern Selection Quick Reference

Use Fan-Out When:
Tasks are independent • Work can be parallelized • High throughput needed • Results can be merged
Use Event-Driven When:
Components should be loosely coupled • Async communication preferred • System needs to scale • Multiple subscribers to same events
Use Hierarchical When:
Complex goals need decomposition • Many specialized agents • Clear organizational structure • Quality control at multiple stages

Mark this module as complete