SKU/Artículo: AMZ-B0G4NR1XRW

Scaling LLM Agents: Distributed Cognition & Multi-Agent Ecosystems: A Practical Guide to Architecting Collaborative, Tool-Driven, and Self-Optimizing AI ... (The Agentic AI Engineering Series Book 2)

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Fuera de stock
Peso con empaque:
0.33 kg
Devolución:
No
Condición
Nuevo
Producto de:
Amazon

Sobre este producto
  • How to structure LLM agents into clusters with clear roles, capabilities, and communication protocols
  • Coordinator and scheduler patterns for robust multi-agent task execution
  • Decentralized routing fabrics for fast, scalable message passing
  • Shared vector memory systems for persistent state, grounding, and context fusion
  • Reflection and optimization loops that help agents correct themselves and learn from outcomes
  • Tool-driven orchestration using APIs, function calling, and external workflows
  • Monitoring, evaluation, and telemetry layers to keep your multi-agent system safe, reliable, and transparent
  • Scalable system topologies for production workloads, real-time reasoning, and enterprise automation
  • AI engineers designing intelligent, high-performance systems
  • Software architects modernizing applications with agentic patterns
  • Founders and CTOs building AI-first products
  • Researchers exploring distributed cognition and emergent behaviors
  • Developers wanting to go beyond prompts and learn real LLM engineering

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