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Companies that sell shippable goods have grappled with spikes in demand since COVID-19 hit. Robots seem like an obvious fix, but putting them into production is a complex undertaking. Still, we can learn from the rare successes: Plug-and-play systems offer far greater returns than large-scale, custom installations. They can be rapidly set up to meet surging demand and rapidly reconfigured when needs change.

Although companies spend billions on formal training for employees, most of the skills needed to perform a specific job can be learned only by doing it. This on-the-job learning (OJL) has long depended on mentorship, with experts coaching apprentices. But today OJL is under threat from the headlong introduction of sophisticated analytics, AI, and robotics into many aspects of work. These technologies are moving trainees away from learning opportunities and experts away from the action. The author describes the "deviant," rule-breaking work-arounds--"shadow learning"--that surgeons in training, police officers, M&A analysts, and others are figuring out on their own to overcome these obstacles and suggests how companies can benefit from studying them.