Andrew Ng says bottleneck in AI startups isn't coding – it's product management

Perspectives from a 30 year career: The bottlenecks are always people and the false and artificial constraints they impose.

It doesn't matter what knowledge based industry it is either, its always people, communication and decision making (or lack of) that makes everything take longer.

Get a committee together to decide multiple products priorities, features, designs and you could be months away from having anything defined enough to code.

I have seen two sides of these artificial constraints people at their work impose. I am still not sure if these artificial constraints are good or bad.

On one hand, I see these artificial constraints making it hard for individuals of varying skill set (outside of the imposed constraint) to contribute better for a group of people working together. This is when startups say they are scrappier and ‘just do it’ instead of being bogged down by bureaucracy.

On the other hand, having these artificial constraints makes it very easy for hiring, training, communication and alignment, all which are also important in a functioning group.

I work at a place where I interact with customers of various sizes. Sometimes I wonder why larger companies come up with this weird bureaucratic political system of constraints limiting their employees.

Other times, I wonder why some smaller companies let their employees manager a critical system when they seem part expert but not really capable of handling it end to end yet.