Artículo: AMZ-B0FC2M9NDG

Designing Agentic AI Systems: Patterns, Protocols, and Frameworks for LangGraph, MCP, and AutoGen (Agentic Systems & AI Pipelines)

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Amazon

Sobre este producto
  • Agent-Driven Workflows: Learn task decomposition, dynamic replanning, and error-handling strategies that keep your agents running smoothly, even under failure conditions.
  • Interoperable Protocols: See how MCP message schemas enable transparent, auditable exchanges between agents and external services, ensuring every API call is logged, validated, and retried if necessary.
  • Graph-Based Orchestration with LangGraph: Build, test, and deploy stateful workflows (Chapter 4). Define nodes and edges to link LLM reasoning, tool invocation, and memory layers into a cohesive pipeline.
  • Multi-Agent Coordination via AutoGen: Define roles, create task-handoff scenarios, and share memory across agents (Chapter 5). Implement KV and vector memory layers for persistent context.
  • Performance and Scalability: Explore horizontal versus vertical scaling strategies, GPU batching, and caching techniques to optimize resource usage (Chapter 11).
  • Security, Compliance, and Ethics: Protect agent-tool communications with authentication and role-based authorization, safeguard sensitive data, and implement bias-detection checks (Chapter 10).
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