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AI as a Business OS: Advanced Claude
Complete Courses 1 to 3 before starting here. This course assumes you have spent time with Claude Code, built some skills and hooks, and now want to understand the system you are working inside.
Lesson one maps the four layers: API, CLI, MCP, and skills. Knowing where each layer sits helps you make better decisions about where to do your work. Lesson two is about frameworks, specifically when to ignore the popular AI productivity frameworks that circulate online.
The last three lessons are the most technical in the series. What to do when a project grows past what you can hold in your head. How to turn any documented API into a working Claude command in under five minutes. And how to build your own multi-agent harness from scratch.
Five lessons. The deepest part of the series.
The deepest part of the series. For operators who have completed Courses 1 to 3 and want to understand the architecture they have been working inside. Lessons on the four layers of Claude (API, CLI, MCP, skills), when to ignore popular AI frameworks, scaling projects past what you can hold in your head, and building your own multi-agent harness.
What you will achieve
Outcomes
- Map the four layers of Claude (API, CLI, MCP, skills) and decide where each piece of work belongs
- Recognise which popular AI productivity frameworks are worth ignoring, and why
- Manage projects that have grown past what you can hold in your head
- Turn any documented API into a working Claude command in under five minutes
Inside the course
Lessons in this course
Course Outline
- The layers of Claude in plain English
- When to ignore the popular AI frameworks
- When the project gets too big to hold in your head
- From API documentation to a working command in five minutes
Common questions
Frequently asked questions
Who is the Advanced Claude course for?
Operators who have completed Courses 1 to 3, spent time with Claude Code, built some skills and hooks, and now want to understand the system they have been working inside. This is the deepest part of the series. It is not a sensible entry point.
What are the four layers of Claude, and why do they matter?
API, CLI, MCP, and skills. Each layer suits a different kind of work. Lesson one maps where each one sits so you can stop forcing every problem into a single tool. Knowing the layers is the difference between making good architecture decisions and writing brittle workflows.
What is a multi-agent harness, and will I build one?
A multi-agent harness is a small system that runs multiple Claude agents in parallel, each with its own role. Lesson five walks through building one from scratch, including how to give each agent its own context, how to pass results between them, and how to keep the whole thing observable.
How current is this material?
The course covers the architecture of Claude as of 2026. The underlying patterns (layers, agents, orchestration, MCP) are stable. Tool-specific details (commands, exact flags, MCP server names) shift as Anthropic ships updates. Where lessons touch on fast-moving surface, we say so and link to the current docs.
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