When individuals and teams use AI tools with different underlying context, the result is inconsistent decisions and conflicting work. The new primary bottleneck for organizations is not tooling but creating a centralized, shared context layer that every person and AI tool can access to ensure consistent, aligned outputs across the company.

Avoid creating a single, massive context document that quickly becomes stale. Instead, maintain 3-5 small, focused, and dated files on specific topics (e.g., team, product). Treat context as an ongoing practice of curation: whenever you re-explain something to the AI, it should be added to a context file.

By creating a central repository infused with company strategy and market data, AI tools can help junior PMs produce assets with the same contextual depth as a 20-year veteran, democratizing product intuition and standardizing quality across the team.

The foundation of an AI-native company is a "brain"—a central context layer where all company information (SOPs, meeting notes, emails) is captured, curated, and structured. This makes the company's knowledge "readable" to AI agents, giving them the perfect vision to execute tasks.

Manage collective team context—docs, queries, research—in a version-controlled repository. Everyone, including non-technical members like ops and strategy, contributes via pull requests, creating a single, evolving source of truth for AI agents and humans.

Buzz positions shared context as its central engine, not just an add-on. Whether an agent is building a project, analyzing data, or participating in a call, it draws from the same persistent conversation history, making it a powerful foundation for all team activities.

Moving PRDs and other product artifacts from Confluence or Notion directly into the codebase's repository gives AI coding assistants persistent, local context. This adjacency means the AI doesn't need external tool access (like an MCP) to understand the 'why' behind the code, leading to better suggestions and iterations.

By organizing all product documents—PRDs, quarterly plans, research, and meeting notes—into a version-controlled GitHub repository, PMs create a single source of truth. This "product repo" becomes a structured environment that AI agents can easily navigate to access context and generate new artifacts.

Move beyond fragmented tools like Notion for PMs and Figma for designers. By using a single, shared GitHub repository for business context, product briefs, designs, and code, teams can create joint context and dramatically increase alignment and speed.