Create a powerful "second brain" by consolidating your podcasts, newsletters, and other content into a single markdown file. This plain-text document is easily consumed by AI agents, training them on your specific knowledge, tone, and frameworks. This allows the AI to generate outputs that are filtered through your unique expertise.

A project-level instruction file serves as a central 'router' for your AI system. It briefs the AI on folder structure, context file routing (what information to use for which task), and tool routing (e.g., 'always use Ahrefs for competitive data'), ensuring consistent and predictable behavior.

To combat reliance on a single AI provider, users can build a personal context layer—a collection of documents, data connections, and skill playbooks. This system acts as personal "alpha," allowing any capable AI model to quickly understand a user's context and perform tasks effectively, ensuring portability and reducing vendor lock-in.

Relying on a local file system for your AI's context creates a single point of failure. By migrating context files to a cloud repository like GitHub, your 'AI brain' becomes portable, collaborative, and platform-agnostic, allowing you to plug it into any tool (Claude, Codex, etc.) or device.

The 'agents.md' file is an open format that functions like a README, but specifically for AI agents. It provides a dedicated, predictable place to store context and instructions, ensuring the AI consistently follows rules for commits, tests, and project setup across all your repositories.

Reusable instruction files (like skill.md) that teach an AI a specific task are not proprietary to one platform. These "skills" can be created in one system (e.g., Claude) and used in another (e.g., Manus), making them a crucial, portable asset for leveraging AI across different models.

Notion's journey to a working AI agent involved multiple failed attempts. Key lessons were to stop forcing models to use Notion-specific data formats and instead provide them with familiar interfaces like Markdown and SQLite, which they are pre-trained to understand well.

Chats in LLMs are temporary. To give your AI a permanent memory, store key instructions, playbooks, and processes as markdown documents within the AI's project files. This creates a stable intelligence layer that the AI always references, and the format is portable enough to be moved to other LLMs.

The underlying system of text files defining your identity, context, and skills is portable across different AI tools. As agentic tools converge in capability, this foundational 'OS' becomes your most valuable, enduring asset, making tool selection a less critical decision.