Why most AI products fail: Lessons from 50+ AI deployments at OpenAI, Google & Amazon

Building successful AI products requires a different approach than traditional software development, focusing on managing non-determinism and balancing agency with control. Companies should start with high-control, low-agency systems, gradually increasing AI autonomy as trust and reliability grow, and calibrate AI behavior to avoid eroding user trust. Leaders must rebuild their intuitions about AI, empower subject matter experts, and prioritize understanding workflows over technology obsession. Evals and production monitoring both play crucial roles in ensuring reliability, but neither alone is sufficient. The future of AI products involves proactive agents anticipating user needs and multi-modal experiences enhancing human-computer interaction.