How I'm Scaling My CLAUDE.md Setup

I've been building an AI Workspace and Second Brain using Claude Code, VS Code, Obsidian, and GitHub. As my projects grow, I'm organizing them into separate contexts rather than loading everything into one session.

My setup:

AI-Workspace — My central Second Brain, learning system, and shared project instructions.
AI Employees — Rex and Piper, two AI agents that research potential customers and help prepare sales outreach.
RentalManager — Automates rental paperwork and lease preparation, with human approval before generating documents.

What each context includes:

AI-Workspace: A root CLAUDE.md that directs Claude to shared instructions, learning notes, and individual projects.
AI-Employees: Agent responsibilities, prospecting criteria, research workflows, and safeguards. Piper drafts emails but cannot send them.
RentalManager: Lease templates, workflow instructions, validation rules, and approval checkpoints.

I'm following three principles from the lesson:

One fact, one location: Each project has its own authoritative documentation. My Second Brain points to the appropriate sources instead of duplicating them.
Clean sessions: Claude loads only the context needed for the current task, keeping unrelated project information out of the conversation.
Team consistency: Shared Markdown instructions, project conventions, and GitHub version control make the workflows repeatable, whether I'm using Claude or another AI tool.

What I'm testing next:

I'm refining how Claude starts new sessions and picks up where I left off. My goal is to open a project and have Claude understand its structure, current status, and rules without having to explain everything again.

My biggest takeaway: Scaling AI isn't about loading more information. It's about making the right information available when it's needed.

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How I'm Scaling My CLAUDE.md Setup