What AI gets wrong outside software

The author tests AI on two physical projects—kitchen shelves and a cheap ROS robot—and catalogues failure modes such as poor reasoning about physical constraints, guessing instead of looking up current data, and writing hacky rather than production-quality systems. He concludes AI is best used for learning, generating reference-based images, and iterating against measurable loops rather than making decisions, and notes it fixed his Home Assistant setup with minimal input.