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It's hard to take a lesson from this without hearing why you think that happened. Do you think the product got so big because the team applied AI usefully and y
by roryokane 6y ago
It's hard to take a lesson from this without hearing why you think that happened. Do you think the product got so big because the team applied AI usefully and your initial evaluation was wrong? Or do you think they gained customers because there is not much competition in that niche and customers were drawn to the sales team's claims of AI despite the AI not being very good?
- draw_down 6y agoThe lesson is just because we think, with our big wonderful brains, that something isn’t going to work in the market, doesn’t mean we’re right. Or to say it another way, the lesson is that business people have jobs for a reason too. Or: if your job is computers, focus on the computers. For me, I don’t go around my company telling everyone whether their projects are going to take off or not. I assume the research a team did prior to starting gives them a familiarity with the problem space that I lack. Crazy thought, I know. The amount of “told ya so” in this thread is really something, so I appreciate GP’s post. Humility is good.
- linza 6y agoMy personal takeaway was that I don't know as much as I think. I didn't produce any data at the time to prove my point (not that I would have known how to), and because of that it's hard for me to analyse the situation more meaningfully as to why I was wrong. Why they were successful in the end: the team struggled for some time before they got momentum with a single really large customer that put in resources, and made other customers follow. It's not that the tech got better that much, customers were just more willing after they saw one of the leaders in that space invest in that approach, and they were afraid of falling behind. It was not because of machine learning, but despite of it.