Chaos Engineering for Agentic AI + Interview Prep

Book prev: https://drive.google.com/file/d/1ck6GO055hJcL_Cw8g0DxxOVqFJI-vhYn/view?usp=sharing

Most agent tutorials show you the "happy path"—how to chain prompts, attach tools, and watch an LLM answer queries. But what happens in production when an upstream model times out, an MCP server drops out mid-execution, a RAG retriever injects poisoned context, or a self-reflection loop spirals out of control?

In classical software, failures throw exceptions. In agentic AI, failures are silent, confident, and expensive.

Chaos Engineering for Agentic AI bridges the gap between toy prototypes and resilient production architectures. Written by Lamhot Siagian (AI Engineering Insider), this book guides you through a progressive 15-chapter laboratory where you inject deterministic faults into every boundary of an agent system: LLM gateways, reasoning loops, tool side-effects, MCP protocols, durable checkpoint state, multi-agent teams, and security filters.

Packed with 15 runnable Python labs, an interactive Streamlit control plane, and 30+ senior system design interview case studies drawn directly from real-world postmortems, this is the definitive playbook for AI engineers, SREs, and architects building the next generation of reliable autonomous systems.