Leanpub Book LAUNCH 🚀 Claude Code: Building Production Agents That Actually Scale by Thomas De Vos
A Best-Selling Book on Leanpub for weeks since releasing. A mandatory guide for building Claude production AI agents.
Welcome to the Leanpub Launch video for Claude Code: Building Production Agents That Actually Scale by Thomas De Vos!
Thomas De Vos
About the Book
A Best-Selling Book on Leanpub for weeks since releasing. A mandatory guide for building Claude production AI agents.
This is a Claude Code production agents book for engineers who need agents that can run with tools, permissions, MCP servers, evals, observability, and cost controls in real systems.
Most Claude Code tutorials stop at "hello world." This book covers what happens after that: when your agent needs to run reliably in production, at scale, in environments where failure has real consequences.
Written by an AI engineer who builds Claude Code agent systems for regulated financial institutions, it walks through the full production stack.
Part I covers the agent loop, context management, and model selection.
Part II builds the primitive layer: tools, hooks, skills, MCP servers, and plugins.
Part III bridges the CLI to the Claude Agent SDK, covering the dispatch loop, session management, and tool registration for headless deployment. Part IV tackles governance: permissions, sandboxing, secrets, audit trails, and managed settings.
Part V covers evals, LLM-as-judge patterns, observability, cost engineering, and failure modes.
Part VI puts it together with team workflows, deployment patterns, multi-agent orchestration, and a full walkthrough of Anthropic's open-source financial services reference agents (the production-grade agent templates Anthropic released in May 2026).
Thirty-one chapters, five practical appendices (including a ninety-day production-readiness checklist, an eval starter kit, and an MCP server audit template), and code extracted from production systems.
If you are a senior AI engineer, technical lead, or architect evaluating Claude Code for production use, this is the reference that will save you months of trial and error.
About the Author
Engineer and AI practitioner with over a decade building production AI systems for global financial institutions. Focused on the intersection of autonomous agents, regulatory compliance, and operational reliability. Currently leading AI strategy for banking, insurance, and fintech clients across multiple continents.
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