Publisher's Synopsis
AI Agent Engineering with LangChain and MCP: Production Patterns
Struggling to build reliable AI agents that scale in the real world?Core Promise
"AI Agent Engineering with LangChain and MCP: Production Patterns" shows you how to move beyond prototypes and deploy full-fledged, production-ready AI agents. You'll master the tools, architectures, and workflows that power resilient, maintainable systems using LangChain and the Messaging Contract Protocol (MCP).
Key Learnings & Benefits
Discover actionable patterns and hands-on guidance to:
Architect Robust Agents: Grasp core abstractions-chains, agents, memory-and design workflows that handle complex tasks and multi-agent coordination (Chapter 3).
Integrate LLMs & External Tools: Build and secure API adapters, implement prompt engineering, and manage rate limits for rock-solid integrations (Chapter 4).
Implement RAG Pipelines: Ingest data, choose the right vector stores, and fuse context with LLMs for accurate, up-to-date retrieval-augmented responses (Chapter 5).
Deploy & Scale: Containerize with Docker, orchestrate on Kubernetes or serverless infrastructure, and leverage spot instances and autoscaling to optimize costs (Chapters 6 & 10).
Automate MLOps & CI/CD: Craft end-to-end pipelines with GitHub Actions or GitLab CI, enforce testing, version models and data, and manage infrastructure as code with Terraform and Helm (Chapter 7).
Ensure Observability & Security: Define metrics, instrument with Prometheus and OpenTelemetry, set up Grafana dashboards, and implement secrets management, encryption, and bias auditing (Chapters 8 & 9).
Each chapter combines clear explanations, production-tested examples, and personal insights-such as real-world pitfalls and recovery strategies-so you can confidently build AI agents that delight users and withstand the demands of live environments.
Equip yourself with proven production patterns for AI agent engineering-get your copy of AI Agent Engineering with LangChain and MCP: Production Patterns today!
