I Built an AI Board Member in Cursor. Here's How.

In an effort to receive honest and agenda-free feedback on monthly board updates, the author developed an AI board member using the Cursor platform, which utilizes markdown file-based rules to provide context and analysis. This AI setup includes three key rules files: "agent.mdc" for workflow management, "company-context.mdc" for business-specific information, and "review-format.mdc" for output structure, ensuring consistent and context-aware feedback. The AI operates without needing frequent briefings, instantly highlighting issues such as grammatical errors or unclear phrasing and posing critical questions to improve the board updates before they are sent. The AI's objective nature and persistent context retention enable the author to address potential board questions proactively, leading to better-prepared updates. By facilitating a stress-tested review process, the AI helps the author identify and fix weak spots, ensuring that board members' concerns are anticipated and addressed.