The AI Feature Maturity Ladder
I keep seeing the same story play out. A team spends three months iterating on prompts for their AI assistant. They rewrite the system instructions a dozen times, tune the retrieval pipeline, test two different models. Eval scores look strong. The CEO loves the demo. Then someone checks the analytics: barely any users have tried it more than once. The team's response? Go back and rewrite the prompt again. Nobody thinks to check where in the product the feature actually lives. When someone finally does, it takes four clicks to find it.
The numbers back this up. MIT researchers studying 300 enterprise AI deployments found that 95% of generative AI pilots fail to deliver measurable impact. The culprit wasn't model quality. It was what they called a "learning gap" between the tool and the organization around it. Teams assume low adoption means the prompt isn't good enough, or the retrieval needs work, or maybe they should switch models. So they keep iterating on the technical side. The technical side was never the issue.