My AI's memory is a hint, not a truth. I wrote that rule after it lied to me.

My AI's memory is not a source of truth but a hint, as I discovered after it told me something that was not true. The AI confidently asserted the existence of a file in a specific location, citing a path that did not match the actual location. Despite its warm and assured tone, the error was glaring.

This experience taught me the importance of treating the system's memory as a suggestion rather than an unquestioned fact. Before the AI takes any action based on remembered information, it must verify the accuracy by listing the directory, reading the file, and running the necessary command. If the check fails, the memory is replaced rather than compounded with new facts.

I implemented this rule to enhance the system's reliability and to prevent the spread of misinformation. To ensure confidence in the system's integrity, any report stating that a file was published or deployed must include a receipt, such as an ID or a hash, directly provided by the tool itself. Without this verification, the claim is marked as unconfirmed, regardless of how convincing the statement may sound.

While this approach slows down the system's performance, it has been the first time I felt at ease leaving it unattended for extended periods. In my regular public demonstrations, I often showcase the AI's successes, but I believe it is equally important to share its failures and the rules that emerge from them. A system that admits, "I do not know," may lack the flair of a winning demo but is far more reliable and trustworthy when left to operate overnight.

The next time you interact with an AI assistant that possesses memory, I encourage you to ask one crucial question: "How can you be certain that you are not wrong?" This simple inquiry can lead to valuable insights into the system's verification process and its commitment to accuracy.