What you'll learn:
- Build a complete personal research agent that uses orchestration, memory, MCP, outcomes, and notifications.
- Build and run Claude Managed Agents using the Console, ant CLI, and Python SDK.
- Design effective agents with models, system prompts, built-in tools, custom tools, and MCP integrations.
- Configure cloud environments, files, vaults, networking, permissions, and safety controls for agentic workflows.
- Stream agent events, track tool use and cost, interrupt runs, and build clients that respond to agent activity.
- Create outcome-driven agents that use rubrics, iteration, memory stores, and dreaming to improve results.
- Orchestrate multi-agent systems for research, writing, fact-checking, coding, and production workflows.
- Integrate Managed Agents with GitHub, Google Docs, Linear, Slack, webhooks, and external APIs.
This course contains the use of artificial intelligence.
AI agents are becoming the next major layer of software development, but most developers are still stuck at the demo stage.
It is one thing to build a chatbot that answers questions. It is another thing to build an agent that can use tools, manage state, work in a cloud environment, interact with external services, follow safety policies, remember useful information, and complete real tasks reliably.
Claude Managed Agents: In Depth and Hands On! is designed to close that gap.
In this course, you will learn how to build practical, production-oriented AI agents using Anthropic’s Claude Managed Agents platform. You will go beyond prompting and learn how managed agents actually work: how they run, how they use tools, how they stream events, how they connect to services through MCP, and how to design agentic workflows that are useful in real applications.
This course deep-dives into Claude Managed Agents, one of the domains on the Claude Certified Developer (CCDV-F) exam, covering managed agent deployment, session management, and Anthropic-hosted agent architecture, useful supplementary prep, not a substitute for full exam study.
You will start with the foundations: what makes an agent different from a chatbot or copilot, how Claude Managed Agents fit into Anthropic’s agentic stack, and how the core building blocks, agents, environments, sessions, and events, work together.
Then you will build agents yourself using the Console and Python SDK. Along the way, you will learn how to:
Design effective agents with models, system prompts, tools, and versioning
Configure cloud environments with packages, networking controls, and least-privilege access
Work with the event stream to monitor tool use, cost, progress, interruptions, and agent state
Extend agents with custom tools, MCP servers, vaults, and per-user authentication
Apply permission policies and safety controls for human-in-the-loop agent workflows
Use Skills, files, GitHub resources, webhooks, and external integrations
Build outcome-driven agents that iterate against rubrics until the task is satisfied
Add memory stores and “dreaming” so agents can retain useful information over time
Orchestrate multiple agents for research, writing, fact-checking, coding, and production workflows
The course includes 15 hands-on labs, leading up to a capstone project where you build a personal research agent that uses orchestration, memory, MCP, outcome evaluation, Slack notifications, and Google Docs integration.
This course is designed for developers, AI engineers, software engineers, solutions architects, technical founders, and Claude Code users who want to move beyond basic prompting and build more serious agentic applications.
Your instructors bring deep real-world experience in AI, cloud architecture, and software engineering.
Frank Kane has taught AI and machine learning to over 1.2 million people around the world. He holds 26 patents in machine learning and spent 9 years at Amazon as a senior engineer and senior manager.
Puria Izady is former Solutions Architect at AWS specializing in Generative AI and Machine Learning, and is the creator behind Pumping Code and the agentic grocery solution Cocoduro.
By the end of this course, you will understand not just how to create a Claude Managed Agent, but how to design, extend, monitor, secure, and integrate agents into real applications.
