Agentic workflow patterns integrate modular software agents with structured large language model (LLM) workflows, enabling autonomous reasoning and action. While inspired by traditional serverless and event-driven architectures, these patterns shift core logic from static code to LLM-augmented agents, providing enhanced adaptability and contextual decision-making. This evolution transforms conventional cloud architectures from deterministic systems to ones capable of dynamic interpretation and intelligent augmentation, while maintaining fundamental principles of scalability and responsiveness.

In this section

• From event-driven to cognition-augmented systems

• Prompt chaining saga patterns

• Routing dynamic dispatch patterns

• Parallelization and scatter-gather patterns

• Saga orchestration patterns

• Evaluator reflect-refine loop patterns

• Designing agentic workflows on AWS

• Conclusion