Publisher's Synopsis
Practical Agentic AI: Workflow Strategies and Patterns for Modern AI Engineers
At its core, Practical Agentic AI equips engineers with battle-tested workflow patterns to build reliable, scalable AI agents. From setting up your first "HelloWorld" agent to orchestrating multi-agent pipelines in Kubernetes, this book transforms fragile prototypes into production-ready systems.
What you'll gain:
Rock-solid foundations: Master environment setup, dependency management, and your first agentic workflow (Chapter 1).
Persistent memory & context: Choose between in-memory caches and vector databases (Weaviate, Pinecone) for seamless state management (Chapter 2).
Tool integration made simple: Define JSON schemas for tools, register them at runtime, and handle errors with retry logic (Chapter 3).
Automated task planning: Generate structured plans with LLMChains, decompose complex goals, and distribute subtasks to worker agents (Chapter 4).
Self-healing pipelines: Build validator agents, implement self-correction loops, and fall back to backup models when things go wrong (Chapters 5).
Multi-agent collaboration: Leverage RabbitMQ or Redis Streams for event-driven communication and orchestrate parallel workflows with fan-out/fan-in patterns (Chapters 6).
Production readiness: Containerize agents with Docker, deploy on Kubernetes with ConfigMaps and health probes, and automate CI/CD via GitHub Actions (Chapters 7-9).
Observability & security: Instrument with OpenTelemetry, expose Prometheus metrics, enforce OAuth 2.0, encrypt data at rest, and maintain audit trails (Chapters 8-9).
Testing & optimization: Unit-test with pytest, run integration tests via Docker Compose, validate contracts with JSON schemas, and profile workflows using cProfile and Py-Spy (Chapters 10-11).
Each chapter delivers clear, copy-paste-ready code aligned with official docs, practical analogies that clarify complex concepts, and checklists to keep you on track.
Take control of your AI workflows today. Grab your copy of Practical Agentic AI and start building robust, efficient, and maintainable agentic systems now.
