What a Microsoftie Learned at MSFT

December 14, 2009

I wish this were a hypothetical. A “hypothetical” is one of those law school or business school conventions. Essentially, the players discuss an imaginary scenario, usually anchored tenuously to facts. “Stuff I’ve Learned at Microsoft” by Sriram Krishnan is not hypothetical. My hunch is that the blog post is a version of reality through the eye balls and other senses of the author. The core idea is that whilst working at Microsoft, practical knowledge moved from the company to the author of the Web log.

Just for fun, let’s take the learnings and then map them to some recent Microsoft products, actions, and services. This, of course, is a hypothetical, and I want you to enter into the spirit of the exercise. Put out of your mind the realities that make up * your * learnings about Microsoft. In the table below, the Sriram Krishnan’s learnings are in the left hand column and the addled goose’s learnings in the right hand column:

Krishnan’s Learnings Goose’s Learnings
Ask for forgiveness, not for permission At least try it at European Union hearings.
(Most) Screw ups are OK Consider Bob. Consider Vista.
Look for the line at your door What if the person is In when she is out and out when she is in?
Code is king What about the auto numbering feature in Word?
Lone wolf syndrome Group-think produces products like SharePoint
Try out stuff Hard to do when Apple products are not in favor
New team? Pick people over products What if the people you want now work at Google?
Get out of your comfort zone Create the Xbox and not address hardware failure rates
Ask the uncomfortable questions Why did MSFT pay $1.23 billion for Fast Search & Transfer when actual revenues were in question
Go say ‘Hi!’ If people are “in”
Praise in public, pull down pants in private Comments about killing Google in the Kai Fu Lee affair
Best things are taken, not given STAC compression
Don’t be an a**hole See my write up about MSFT PowerShell cmdlets for Fast Search which is a dead link.

I like these hypotheticals. We need more of them in search and content processing. For example, Microsoft’s enterprise search system scales in a cost effective manner.

Stephen Arnold, December 14, 2009

I wish to disclose to the Department of Commerce that I was not paid to write this goosely article. The commerce associated with products that do not work at advertised does generate a lot of dough. Too bad the goose does not know how to ride a gravy train without becoming the main course.

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