To prevent an AI agent from repeating mistakes across coding sessions, create 'agents.md' files in your codebase. These act as a persistent memory, providing context and instructions specific to a folder or the entire repo. The agent reads these files before working, allowing it to learn from past iterations and improve over time.

An agent's power comes from its deep context about a user's business and life. Maintaining a detailed, structured personal knowledge base in a tool like Obsidian, which can be fed to the agent, is the most critical step to creating an agent that feels like a "second brain" and can operate with genuine understanding.

To maximize an AI assistant's effectiveness, pair it with a persistent knowledge store like Obsidian. By feeding past research outputs back into Claude as markdown files, the user creates a virtuous cycle of compounding knowledge, allowing the AI to reference and build upon previous conclusions for new tasks.

Instead of manually organizing notes, delegate the task to your AI agent. After learning your habits and priorities over a few weeks, Hermes Agent can automatically create and update a personalized dashboard in Obsidian, making the knowledge base useful without the manual overhead.

Instead of using siloed note-taking apps, structure all your knowledge—code, writing, proposals, notes—into a single GitHub monorepo. This creates a unified, context-rich environment that any AI coding assistant can access. This approach avoids vendor lock-in and provides the AI with a comprehensive "second brain" to work from.

Relying on chat history for an AI's memory is fragile. A more robust method is to have the AI serialize key learnings into an external, structured file system (like an Obsidian vault). This creates inspectable, editable, and reusable artifacts that can outlive any single conversation thread.

The paradigm for AI delegation shifts from instructing an agent to curating a knowledge base. Your primary job is ensuring your Obsidian vault accurately reflects your thinking. An autonomous agent pulls from this "source of truth," and you correct its behavior by updating the vault, not the agent.

Provide AI agents with a structured knowledge base, like an Obsidian vault, to give them deep, persistent context on your business, people, and projects. This is faster and more reliable than having the agent constantly fetch information via APIs, making it a more efficient and knowledgeable worker.

A command like `/ideas` can prompt an AI to scan your entire life's context stored in Obsidian. It cross-references notes, relationships, and even disconnected "orphan" files to generate a comprehensive report with actionable suggestions, from new tools to build to specific people you should contact.