How to Manage AI Teams for Success

A few months ago, I had a conversation with several researchers from a prominent AI company in Toronto, and their company philosophy was that everybody should write production-grade code and even be able to deploy it. It made me think about a lot of stuff. AI teams are specifically interesting because they simultaneously require at least two disciplines: software/hardware engineering and scientific discovery. So how does one work towards success and creating a cohesive team, or teams, of researchers and software engineers who work together and create great products? The product being either pure research in the context of an enterprise trying to gain a competitive edge in terms of intellectual property, or applied research geared more towards a commercial product in a given vertical, or a hybrid of both.