About this ebook
The book begins with the architecture of autonomy, explaining the components that turn a large language model into a functional agent, including reasoning, planning, tools, memory, perception, state management, and safety mechanisms. It then moves into the Gemini model family and explores multimodal capabilities, long-context processing, context caching, native reasoning, function calling, and real-time agent experiences.
You will learn how to design structured reasoning chains using techniques such as Chain-of-Thought, ReAct, Tree-of-Thoughts, and Graph-of-Thoughts, while addressing hallucinations, plan drift, and unreliable reasoning. The book also explains how function calling and Vertex AI Extensions allow agents to interact with APIs, databases, search services, and other external systems.
Memory and grounding receive particular attention, including short-term context, long-term memory, vector search, personalization, persistent state, and data privacy. The book then introduces Vertex AI Agent Builder, Playbooks, the Agent Development Kit, Agent Designer, grounding integrations, and Agent Engine for production orchestration.
The final chapters address the challenges that determine whether an agent is ready for real-world use: evaluation, red-teaming, safety guardrails, observability, reliability, cost management, security, data residency, deployment strategies, and human-in-the-loop workflows.
Whether you are a developer, AI engineer, cloud architect, or technology leader, this book provides a practical path from your first Vertex AI agent to scalable, secure, production-ready agentic systems.
