From Poc to Production : AI Agents in Action

Omtale

Your agent demos well. It answers cleanly in the notebook, handles the cases you thought of, and earns the budget to build the real thing. Then you try to ship it. Where does its memory live once the process exits? Who authorized the tool call it just made? None of that showed up in the demo. This book is about the second half of that story. It's the distance between an agent that runs on your laptop and one a business can depend on. You start at setup and work toward the parts that decide whether an agent holds up under load. You'll structure agents you can see into, build with Strands Agents, LangGraph, and other SDKs, wire in real tools, and handle the errors those tools throw back. You'll coordinate more than one agent and keep the whole thing from getting brittle. By the time you reach MCP and Agent-to-Agent communication, the interesting question isn't what the protocols are. It's which one a given job needs, and how to run both together without the seams showing. The rest runs on Amazon Bedrock AgentCore. A hotel concierge agent remembers a guest's preferences from one call to the next, because its memory outlives the session that created it. Tools and servers become callable endpoints through Gateway and get cataloged in Registry. AgentCore Identity authenticates every call, in both directions, with OAuth-based on-behalf-of tokens. OpenTelemetry traces land in CloudWatch, so when something breaks, the trace is there. By the end you will have carried one system all the way across. It's deployed on AgentCore, monitored, and standing on the memory, identity, and gateway layers built earlier in the book. Whether you're moving an existing agent into production, starting from nothing, or building infrastructure a team will run, the work that keeps these systems alive is here. You Will: Build and coordinate multi-agent systems with Strands Agents, LangGraph, MCP, and A2A, and know which protocol a given job actually needsStand up production infrastructure on Amazon Bedrock AgentCore, with persistent memory, two-way OAuth identity, Gateway-exposed tools, and traces you can read in CloudWatchKeep the system alive after launch: watch its behavior, respond when it breaks, control what it costs, and stay compliant as load grows.This Book Is For: For engineers and architects building agentic systems. You should be comfortable with Python and have basic familiarity with LLM APIs. Some of job families include full-stack engineers, Data/Applied Scientists, AI Engineers, Enterprise Architects.