{ "item_title" : "Mastering Google ADK", "item_author" : [" Nathan Steele "], "item_description" : "Mastering Google ADK is the first deep-dive guide that shows developers-today and in the years ahead-how to design, build, and deploy production-ready AI agents with Google's Agent Development Kit (ADK) and the latest Gemini 1.5 / 2.5 models. Written by cloud-architecture specialist Nathan Steele, this book strips away hype and teaches a proven, modular workflow that leading engineering teams are already using to automate research, customer support, data analysis, and more.Why This Book Stands OutEnd-to-End Blueprint: Learn every stage-from local prototyping to secure cloud deployment-so your agents run reliably at scale.Tool-First Methodology: Schema-driven tools and the AgentLoop replace brittle prompt chains, giving you deterministic, traceable results.Multi-Agent Orchestration: Design collaborative or competitive agent teams with the A2A protocol and Agent Engine for real-world complexity.Gemini Expertise: Practical guidance on streaming output, vision inputs, and model tuning-perfect for both Gemini beginners and power users.Enterprise-Ready Patterns: CI/CD pipelines, observability, safety filters, auto-evaluation, and cost controls ensure you meet production SLAs.Future-Proof Content: Covers the 2025 ADK roadmap, Java bindings, and integrations with LangChain, AutoGen, DSPy, Neo4j, and Vertex AI.Inside the BookPartKey Topics & Skills You'll Gain1 - Foundations: Core concepts, ADK vs. LangChain/AutoGen, high-value use cases2 - Environment Setup: CLI, folder structure, Gemini config, Google Cloud keys & billing3 - First Agent Build: Tool schemas, AgentLoop execution, debugging with traces4 - Multi-Agent Design: Role assignment, memory sharing, task routing, collaboration vs. competition5 - Gemini & Tools: Streaming, tool calling, vision, external APIs, cloud functions, RAG pipelines6 - Advanced Features: State management, evaluators, adapters, export & deployment7 - Agent Engine Deployments: Tracing UI, scaling sessions, secure API gateways, CI/CD8 - A2A & MCP: Secure messaging, identity, cross-agent governance9 - Real-World Recipes: Doc-parser notifier, research team, internal support agent, Neo4j graph app, custom modular assistant10 - Evaluation & Ethics: Auto-scoring, success metrics, hallucination handling, content moderation11 - Troubleshooting & Optimization: Latency, quotas, observability, anti-patterns, Gemini performance tuning12 - Looking Forward: ADK roadmap, open-source templates, fully autonomous systems, staying currentAbout the AuthorNathan Steele is a veteran solutions architect who has helped Fortune 500 companies modernize data pipelines and deploy large-scale AI systems on Google Cloud. His workshops on agentic workflows and Gemini best practices have trained teams across five continents. In this book, Nathan distills years of hands-on experience into a pragmatic playbook any developer can follow.Perfect ForPython engineers and ML practitioners who want to move beyond prompt hacking.Cloud architects seeking a secure, observable framework for AI automation.Product teams aiming to embed intelligent, tool-calling agents into SaaS or enterprise apps.Consultants and tech leaders tasked with future-proofing their organization's AI strategy.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/9/79/828/859/9798288593918_b.jpg", "price_data" : { "retail_price" : "18.00", "online_price" : "18.00", "our_price" : "18.00", "club_price" : "18.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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