Artículo: AMZ-B0FBX9VQR3

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

Disponibilidad
Sin stock

Peso con empaque
0.20 kg

Devolución
No

Condición
Nuevo

Producto de
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).