The problem of failed learning existed long before AI. The information comes from multiple sources like Slack conversations, customer support cases, and sales calls, but there is no process in place for filtering out patterns. Speed of development wasn't the issue. Figuring out which features should be developed is the issue. With AI, it takes three days to deliver new features instead of three weeks, but you still may spend those three days on something not worth building.

The loop closes only when customers' insights have a proper place to go, where duplicates can be filtered out and priorities set. This isn't happening for many teams, and the acceleration of code generation will only make things worse.