knowtheworld

I do feel that. Another way to view this is that programming sometimes is like solving a math problem. A top-tier mathematician can solve a difficult math problem 100x faster than an average person. 100x is even a bit understatement because most people can’t even come up with any solution given long enough time. For sure, programming is not solving math problems, but they have some similarities. But this is a way to conceptualize it.

There is not a straightforward way to measure it. It’s highly domain dependent. There are some general directions though. Deep understanding of domain knowledge, clear logics, excellent programming ability, and ability to frame a problem in the right way and break it to smaller problems. It’s vague I know, that’s why it’s not trivial to see it though.

Another way to view this is that programming sometimes is like solving a math problem. A top-tier mathematician can solve a difficult math problem 100x faster than an average person. 100x is even a bit understatement because most people can’t even come up with any solution given long enough time. For sure, programming is not solving math problems, but they have some similarities. But this is a way to conceptualize it.

I would argue that making efficient and reliable software products is a very crucial factor for a software company to bring more revenue. It’s just not as straightforward to measure this.

I agree that 10 engineers can’t do everything 10x. Even 10x engineers can only let 10% of the code 10x faster, it might have a deciding impact on the end result. if a software product is all written by 10x engineers, it might turn out to be 2x as fast as the one done by average engineers.

And in software optimization, speeding up a program 2x usually requires 10x more resources. This is why I think the 10x concept still makes sense here.

Programming itself is a super lever. That's probably why the productivity among software engineers can be so extreme.

It might be hard to build an unicorn with a single super developer. But he/she might build a great product to get the company enough funding to grow to an unicorn.

Around 5% of MLB players can get $20M a year, which is around 5x to the average. But I am not sure there are 5% of engineers at the Bay Area can more than $1M

I read this article before and I think this might apply to a 5-10 person startup. An engineer’s ability might be easily measured there. But the problem is startups at that scale usually don't have that much money to pay engineers. That’s probably why you see the reverse.

I think "N"x is just a hypothetical number. It can be 1x - 50x depending on the individual

The difference is a sports team has at most 30 team members but a company can have 1000+ engineers, which makes everything tangled together

I thought most stock options are worth like x% of your base salary. They usually can boost the total salary on a certain level but not a crazy amount?

But the problem is the software industry is hype complex. Thus is almost impossible to measure your real revenue contribution.