Video summary

How to Build Your GPT-6 Astra OS

Main summary

Key takeaways

Educational

Main Ideas / Lessons

  • Organize your AI “operating system” with a clean folder/workspace structure so you can run tasks in isolated areas (e.g., YouTube vs. newsletter vs. client work) without loading irrelevant context.
  • Use a single top-level agents.md as a “router” that controls overall behavior and routes the model into the right departments/rooms, rather than creating many separate agent instruction files.
  • Create layered context that scales:
    • Company-wide context (shared identity, priorities, rules)
    • Department context (e.g., Brand, Agency, Ventures)
    • Room context (specific ongoing responsibilities like YouTube, Newsletter, Support, Delivery, or specific client work)
  • Decide between “rooms” and context.md files based on what changes and how much responsibility differs:
    • If something is an ongoing responsibility with meaningfully different context, give it its own room (and likely its own folder and context files).
    • If something is reusable facts/instructions that support an existing room, use a context file.
  • Maintain accuracy over time by keeping contexts current and performing audits (daily/weekly/monthly depending on your needs) to prevent “context bleed” and misrouted workflows.

Recommended Methodology

1) Top-Level Structure (the “Company Folder”)

  • Create a single main folder for your AI OS (e.g., your company / LLC / operator workspace).
  • Inside the top level, include:
    • agents.md
      • Acts as system instructions and a router for the whole operation.
      • Should set the model’s working role, decision/approval expectations, and routing behavior.
    • Shared company context files (stored in a dedicated context area)
      • Identity & priorities that apply across the entire business.
      • Shared rules that should be consistently enforced.

2) Break Down into Departments

  • Under the main folder, create subfolders for major business functions/departments, such as:
    • Marketing / Brand work
    • Agency / client operations
    • Ventures / separate projects/publications

3) Break Departments into “Rooms” (Specific Responsibilities)

  • Within each department folder, create “rooms” representing distinct ongoing responsibilities or workflows.
  • Example rooms mentioned:
    • Brand department: YouTube room, Substack room, LinkedIn room, byline/guest-writer room
    • Agency department: client operations room, deployed SaaS/tool repo location
    • Ventures: separate publication projects

4) Add Context Files at Each Layer

  • Company-wide context files
    • General who-you-are/what-you-do/rules/audiences.
  • Department context files
    • Explanation of that department’s purpose and responsibilities.
  • Room context files
    • Room description (e.g., a room.md explaining what the room is)
    • Room-specific workflows and constraints
    • Additional context such as audience/ICP specifics per channel or publication

5) Implement Routing Behavior via agents.md and Boot Sequence

  • In agents.md, instruct the model to:
    • Start in an “executive partner” mode (example role: CEO as decision maker; AI surfaces facts/evidence/opinions/recommendations).
    • Stay at the root of the company folder and route into branch rooms.
    • Do not spawn separate operating sessions purely because a task belongs to a particular department folder.
  • Add a boot sequence in agents.md that at the start of each session:
    • Forces Code(s) to read the key company-wide context files (e.g., a user/profile file, business overview, and ICP/audience profiles).

6) Work Example (How a Session Routes)

  • When starting a fresh session in Codeex with GPT-6 Astra:
    • The system starts at the company root
    • Loads agents.md + root context
    • Detects the task (e.g., “create a YouTube video”)
    • Routes into the correct department (Brand) and room (YouTube) context
    • Executes using only the relevant loaded context

7) Room vs. Context File Decision Rule

  • Use a room when:
    • The responsibility is ongoing
    • The context/rules differ meaningfully from other responsibilities
    • Examples: channels (YouTube vs. Substack), clients (each client likely gets its own room), products/ventures
  • Use a context file when:
    • The information is reusable facts/instructions
    • It supports the existing room’s mission/workflows
    • Examples: a specific workflow inside a department (e.g., a cross-channel repurposing contract for YouTube → Substack)

8) Keep Context Organized and Prevent “Context Bleed”

  • Ensure clients/channels/products have separate context boundaries (rooms) to avoid mixing instructions and audience/rules.
  • Run periodic audits (daily/weekly/monthly) so workflows and context don’t drift into the wrong places.

Concrete Example of the Creator’s Setup

  • Main folder: one company-wide workspace (named like “Alex McFarland” in the example).
  • Departments inside the company:
    1. Brand work (audience + educational content)
    2. Agency (client work + developing a SaaS tool/repo)
    3. Ventures (building separate publications/projects)
  • Rooms under Brand:
    • YouTube, Substack, LinkedIn, and byline/guest-writing
  • Creator Studio:
    • A locally deployed dashboard in Codeex for tracking competitors/creators and building content packages (mentioned as something built alongside the brand work).

Speakers / Sources Featured

  • Speaker: The video narrator / author speaking throughout (no name explicitly confirmed in the transcript, but the example “Alex McFarland” appears to be the speaker’s company/operator name used for the folder template).

Original video