Seven Engineering Lessons from Running AI in Production
AI systems often fail in production not because the models are inaccurate, but because the surrounding engineering lacks the controls needed for reliable operation. Moving from prototype to production requires clear boundaries around how AI is invoked, validated, observed, constrained and recovered when failures occur....