[koolmoe]

I don't think getting stuck in a local optimum is as important as the speed with which you get there.

Techniques for finding a global optimum of a numerical function are expensive, time-consuming, and often find worse solutions before they find the best one. Do this in a startup, and your local-optimum-seeking competition will crush you.

Seems to me that thinking there is a better solution that your users don't know about (which led you to the local optimum) is exactly the lack of humility that Paul was warning against.

[pmjordan]

Sorry, I didn't actually mean you should try to go straight for the global optimum (I'd argue there's probably no such thing) - I'm just wondering about known local optima. Solutions that already exist. I don't necessarily know about startups, but in open source software, it seems that a lot of the time, there's some slick and cool new take on a problem. As it becomes popular, it eventually just grows in the direction of all the other solutions that are out there, becoming yet another bloated clone. It seems to me that if you find yourself going down that road, you should steer against that trend. Or should you?