Books

Build and operate LLMs on-premise environment that stay reliable, auditable, and compliant — not just after launch, but continuously. Closed-Loop LLMOps is not another framework for building models — it is a practical system for operating them reliably at scale. It treats language models as living, evolving capabilities rather than static artifacts. This is practitioner’s guide with RAG Ready appendices , to closed-loop LLMOps for regulated and on-prem environments.

AI agents introduce new security risks that traditional approaches often fail to address. This handbook shows you how to identify threats, build effective sandboxes and enforce least-privilege access. With practical examples and production-ready implementations, it gives you the tools to build AI systems that are secure by design.

Building multi-agent systems is one thing. Making them reliable in production is another. This book takes you from core architectural concepts to working implementations, covering the patterns, techniques and operational practices needed to coordinate agents, handle failures and build systems that hold up under real-world demands.

Building AI-powered software takes more than plugging into an LLM. This book explores the engineering principles and architectural patterns behind reliable, secure and scalable AI systems. Learn how to move from prototypes to production with practical techniques that stand the test of time, even as models and frameworks evolve.

What if your AI agents could learn from their mistakes instead of repeating them? Discover how to build systems that remember past experiences, adapt to new challenges and improve with every task. From memory architecture to practical implementation, this book shows you how to create agents that get better over time.

Building reliable AI agents takes more than connecting an LLM to a few tools. This book takes you inside the Cursor Agent SDK, showing you how to build, test and deploy agents that hold up in production. Learn the APIs, understand the architecture and turn agentic ideas into systems you can trust.

In this 2nd edition, I'm going to be working with you on a single app called OrderDesk. We'll build its inventory, roles and secrets, and then we'll patch its servers, provision its cloud resources and deploy it to Kubernetes. Later, we'll watch it with Prometheus, heal it with Event-Driven Ansible and diagnose its failures with playbooks that collect evidence in seconds. Then, in the last few chapters, we'll start inviting AI agents through tools and MCP servers, while approvals and check mode make sure that everyone keeps control of the decisions. You don't need to be a pro programmer to follow along.

Add Gmail search, reading and drafts to an existing OpenAI Agents SDK agent on Windows, with explicitly authorized sending.

Configure Artemis shared memory, documents and local work continuity for an OpenAI Agents SDK agent on Windows.

Install the Artemis HDSM/HDSD gateway on Windows and connect ChatGPT to external memory records and documents.

Persistent memory, hooks, permissions and token cost: what worked when using Claude Code every day in a real small-business operation.

Ready to put Hermes Agent to work? This practical guide takes you from the basics to real-world automation, covering setup, architecture and workflows for research, writing, development and operations. Learn how Hermes works, how to configure it for reliable results and how to make it a useful part of your daily work.

Ready to build AI systems that work beyond the demo? This book takes you from the fundamentals to production-ready AI, covering everything from neural networks and LLMs to RAG, agents, optimization and deployment. Learn the theory, understand the code and gain the skills to build reliable AI systems from the ground up.

Build an AI coding agent through clear concepts, practical quizzes, and working code—from the agent loop to crash recovery.

AI can write code, create images and make decisions, but do you really understand what happens behind the scenes? This book cuts through the hype to explore how AI works, where it falls short and what it takes to build reliable systems. If you want to understand AI beyond the chat window, start with the code.