yes there are points under the curve out at 10X the mean but they are very, very rare. The normal distribution falls off a cliff. I don't have the reference in front of me but something like 99.6% of the population will fall within 2 standard deviations of the mean. This same issue comes up when people try and predict something like the daily fluctuation of the Dow Jones Industrial average using a normal curve. They think that there are random swings up and down but that large swings of 500 points are more are very unlikely. Then those large swings come along and show everybody that it isn't smart to use the normal distribution to try and model the absolute change in the closing price.
The main point here is that programmers who are 10X more productive than the average coder seem to be not so rare. Many people have stories about having worked with guys like this. Therefore I don't think you should use the normal distribution to model the distribution of productivity in programmers. I think there are many guys at the low end of the scale and it drops off slowly as you move into the higher productivity. And NO you can't include the negative x-axis to get a symmetric, "normal-like" distribution. In this model the negative values on the x-axis don't mean anything.
The main point here is that programmers who are 10X more productive than the average coder seem to be not so rare. Many people have stories about having worked with guys like this. Therefore I don't think you should use the normal distribution to model the distribution of productivity in programmers. I think there are many guys at the low end of the scale and it drops off slowly as you move into the higher productivity. And NO you can't include the negative x-axis to get a symmetric, "normal-like" distribution. In this model the negative values on the x-axis don't mean anything.