[ska]

This is a classic problem that shows up equally with lots of related areas: numerical work, statistics, ML, signal processing etc.

"just compose a team" sounds easy, doesn't it? Unfortunately there are lots of failure modes involving different parts of the team not really understanding what each other are trying to do, let alone what they are doing, and subtle errors getting by people who don't know what to look for. So, you can find such teams and some of them work well but a lot of them don't.

So an alternate is to try and find or create domain experts who mix all the appropriate skills, but this is hard and in the extreme case involves chasing down unicorns.

Companies and industries flop back and forth between preferring different approaches - right now a lot of people are talking about "data scientists" as one of the latter, but it will likely change over time as it always does.

It's a hard problem, and it shows.

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As an engineer, I usually know better than to use the phrase I hate to hear: "why don't you just..."

[pbhjpbhj]

Surely "Why don't you just... ?" is an exceptionally good phrase to use. In practice people mean "Just do ... !", which is very different. The why question, however, gets to the heart of an issue, it's a short hand for "The obvious solution appears to be that ... but I imagine you tried that and have a reason not to do things that way, what are those reasons?". It's a direct learning-centred enquiry that ekes out the kernel of complexity of a situation relying on the wisdom of the person it's aimed at.

So why don't you just use the phrase "Why don't you just ...?"?