#llm

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](https://docs.aws.amazon.com/prescriptive-guidance/latest/agentic-ai-patterns/from-event-driven-to-cognition-augmented-systems.html) - [Prompt chaining saga patterns](https://docs.aws.amazon.com/prescriptive-guidance/latest/agentic-ai-patterns/prompt-chaining-saga-patterns.html) - [Routing dynamic dispatch patterns](https://docs.aws.amazon.com/prescriptive-guidance/latest/agentic-ai-patterns/routing-dynamic-dispatch-patterns.html) - [Parallelization and scatter-gather patterns](https://docs.aws.amazon.com/prescriptive-guidance/latest/agentic-ai-patterns/parallelization-and-scatter-gather-patterns.html) - [Saga orchestration patterns](https://docs.aws.amazon.com/prescriptive-guidance/latest/agentic-ai-patterns/saga-orchestration-patterns.html) - [Evaluator reflect-refine loop patterns](https://docs.aws.amazon.com/prescriptive-guidance/latest/agentic-ai-patterns/evaluator-reflect-refine-loop-patterns.html) - [Designing agentic workflows on AWS](https://docs.aws.amazon.com/prescriptive-guidance/latest/agentic-ai-patterns/designing-agentic-workflows-on-aws.html) - [Conclusion](https://docs.aws.amazon.com/prescriptive-guidance/latest/agentic-ai-patterns/conclusion.html)