The Data Pipeline Behind Every AI Feature

AI features rely on a unified data pipeline consisting of eight distinct stages, from initial acquisition to final model citation. Errors typically occur at the joints between these stages rather than within them. Additionally, deploying AI features requires more than conventional boolean flags. Because AI failure modes vary—such as provider degradation or prompt regression—teams need flexible controls to switch models or revert prompts instantly without disabling the entire feature to maintain operational stability.