Guia prático para desenvolvimento agêntico com Claude Code, MCP, Claude API e Agent SDK. De modelos mentais a arquiteturas de produção — tudo que um dev experiente precisa para trabalhar de forma agêntica, não apenas usar ferramentas de IA.
A hands-on guide to building with Claude Code, MCP, the Claude API, and the Agent SDK. From mental models to production architectures — everything an experienced developer needs to work agentically, not just use AI tools.
As the author, I (Anshuman Mishra) have written this book with the spirit of mentorship — not just to explain how chatbots work, but to help you build one confidently and ethically. I have taught AI, programming, and computer science for nearly two decades, and I have seen countless students struggle to bridge the gap between theory and implementation.This book closes that gap. It teaches you what to do, why to do it, and how to do it right. It’s not just a manual — it’s a journey from curiosity to mastery.You are not just learning to build a chatbot; you are learning to create intelligence — responsibly, creatively, and with purpose.
As the author, I (Anshuman Mishra) have written this book with the spirit of mentorship — not just to explain how chatbots work, but to help you build one confidently and ethically. I have taught AI, programming, and computer science for nearly two decades, and I have seen countless students struggle to bridge the gap between theory and implementation.This book closes that gap. It teaches you what to do, why to do it, and how to do it right. It’s not just a manual — it’s a journey from curiosity to mastery.You are not just learning to build a chatbot; you are learning to create intelligence — responsibly, creatively, and with purpose.
Build MCP servers from scratch — from protocol to production deployment. Learn Tools, Resources, Prompts, HTTP transport, authentication, testing, and server composition. 14 chapters, one real project, complete TypeScript code.
How to put AI agents in production without ending up in the news. A field guide to bounded AI autonomy, MCP security, and AgentSecOps.
Construa servidores MCP do zero — do protocolo ao deploy em produção. Aprenda Tools, Resources, Prompts, transporte HTTP, autenticação, testes e composição de servidores. 14 capítulos, um projeto real, código TypeScript completo.
Construa um AI agent completo do zero — de uma chamada simples à API até um sistema multi-agente em produção com memória, planejamento, RAG, segurança e deploy. 15 capítulos, um projeto real, código Python completo.
What if agentic AI was less about hype and more about work you can actually inspect?OpenClaw and Hermes for Agentic AI is a practical field guide to building with local agents, memory, tools, sessions, cron jobs, and ACP bridges. It shows how to turn fuzzy ideas into reliable workflows with clear boundaries, real artifacts, and human review where it matters most.If you want a grounded look at how agent systems really operate, this book starts there.
Most senior engineers don't fail AI systems interviews from lack of ability—they fail because they sound like builders when they need to sound like staff. This book gives you the answer flow, the system deep dives (RAG at billion-doc scale, agentic pipelines, token-cost tradeoffs), and the behavioral stories that earn L5/L6 offers at AI-first companies. Built for senior engineers targeting Staff AI Systems roles in the next 8 to 12 weeks.
88 per cent of AI agent projects never reach production, not because the model failed, but because the harness around it was never built. This is the practitioner's handbook for engineers who deploy AI inside real organisations, covering the complete journey from discovery to handover with harness engineering as the core technical discipline.
You have been using AI as a faster keyboard.The engineers who will define the next decade are using it as a cognitive workforce they direct, constrain, and govern. The gap between those two practices is not a matter of better prompts. It is a matter of an entirely different mental model.This book is that mental model. Built from first principles. Illustrated through 28 chapters of real architectural decisions, real failures, and real production systems.From execution to orchestration. The complete practitioner guide.
Most writing about AI and infrastructure stops at the demo. This book starts on the day the model is confidently wrong at 3 a.m. and an auditor asks who authorised the action it took. Seven working labs — MCP servers with real identity and audit, closed-loop remediation behind a reversibility gate, and autonomy that can be revoked — for platform engineers in safety-critical and regulated industries.