AI in App Development: Where It Helps, Where It Fails, and What Teams Should Prioritize
Most conversations about AI in app development begin in the wrong place. They lead with capabilities and demos, then work backward to use cases. The teams that get burned usually followed this path: they approved budget for an AI feature, watched it perform well in staging, and then discovered post-launch that the surrounding workflow was wrong, the model behaved differently under real load, or no one owned the process of reviewing and correcting AI outputs before they reached users. ...