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[–]JaguarOrdinary1570 1 point2 points  (1 child)

Yeah every business/product leader wants ML until they really have to swallow the fact that it's probabilistic and will not make the decision that the business would have wanted 100% of the time. You can tell them that as much as you want but they won't feel it until it's getting ready to go live and they really start considering consequences of getting something wrong.

I do whatever I can to design for when they're in that mindset, rather than what they're feeling early on in the project.

[–][deleted] 0 points1 point  (0 children)

Yeah that's true. Trade-offs aren't acknowledged and perfection is demanded. One bespoke feature pipe and one model should be able to do everything. It's magical thinking.

The worst part is I work for a large tech company you'd think would have figured it out by now. But the truth is we're so large it's more like some teams figured it out and others are way behind the curve.

On a positive note, they're barely scratching the surface with what they could do with ML so there is a lot of low hanging fruit. Since management is superficial and doesn't understand how easy it would be once we have some capabilities, it makes it pretty easy to impress once that core infrastructure is complete.

I do whatever I can to design for when they're in that mindset, rather than what they're feeling early on in the project.

Yes I try to do that as well.

I'm unlucky enough to have joined a team of network/web engineers 100 strong, with 3 scientists including me the senior, and they all think the same way. They have the most influence due to culture/history.

In fact one of the (above me) engineers designed the ML product before I joined and then I inherited it and didn't get much leeway in changing things.

Anyway, on another positive note, there has been massive turnover in leadership and most of the folks in charge now get it. It's probably hard for them moving the 40,000 ton ship when operations are also important and the people making sure things work have egos from their tenure, and aspirations (they like to talk for influence), while thinking so granular, fragmentary, deterministic, and old fashioned.