What I learned from Google - You Get Fifteen Years
four years ago I was in Mountain View, California, interviewing for a position with Google.
It was an odd sort of interview. Lots of puzzles, math-like challenges, and code. Lots, and lots, and lots of code.
No, what struck me were the people.
All of the people I met — and I mean all of them — had this sort of early-twenties look to them. Like the characters in Microserfs, these were “firstees”, young adults in the middle of the first things like life: First job out of college, first house, first child, first mini-van.
All of them.
The google t-shirts, while not universal, were ubiquitous; you couldn’t walk twenty feet without running into someone in Google-wear. Conversations about relocation tended to center on corporate housing, which sounded well … something between a good room and an apartment.
Well, I should be careful, here. Every now and again you’d run into someone in his early 30’s, trying to act inconspicuous, perhaps with a beard, glasses, or both.
These were the managers, almost certainly on their first management job.
I mean, these are people who refer to the extra weight you gain in the first six month as the “freshman fifteen.”
With my grey hair and, and, well, senior sixty, I kinda stuck out like a sore thumb.
This is what struck me: Where were the old dudes?
It probably makes sense
This is, after all, a company that grew from 800 employees in 2004, at their initial public offering, to about 16,000 when I interviewed. That’s about twenty-three new hires per business day - with an average tenure, at that point, of about 1.5 years.
Where did most of those employees come from? Certainly MIT, Carnegie-Mellon, and the University of California at Berkeley would be likely places for recruiters to hit; places with lots of about-to and recent graduates looking for cutting edge programming work.
For that matter, new graduates are easy.
They work really hard, they have few responsibilities and obligations outside of work, and often are at a place in their lives where relocation is no big deal.
If you’re trying to build a like-minded workforce, you might do well to recruit young bucks fresh out of school.
A grey-hair sportin’ a “senior sixty”? Not so much.
But what about the old dudes?
During my interview at Google, I realized something very important: You get fifteen years.
That is to say, your half-life as a worker in corporate America is about age thirty-five. Around that time, interviews get tougher. Your obligations make you less open to relocation, the technologies on your resume seem less-current, and your ability find that next gig begins to decrease.
Notice I said half-life. By thirty-five, half the folks who started in technology have gone on to something else — perhaps management, consulting, on to roles in “the business” or in operations. Some have had a full-on career change, got that MBA and gone into management consulting, or perhaps real estate, education, or, well … retail store management. Who knows? A few might go into journalism.
Yet a few stick it out. Half of the half-life is fifty, and, sure, perhaps 25% of the folks who started as line technologists will still be doing that when they turn fifty.
But by the time you turn thirty-five, you’d better have a plan.
That gives a new college graduate fifteen years to build some savings, to get the house paid off, and to find a second career. That’s plenty of time.
The good news
Is a different way to look at it. That twenty-one year old, fresh-faced kid we are all so jealous of with the great gig at happenin’ company? He isn’t really qualified to do anything else. He goes and gets a job by default, because it’s the easiest thing to do. He can’t consult, or at least he shouldn’t; you see, he hasn’t done anything yet.
That is where those of us in the middle of the half-life curve have an advantage.
Hitting half-life may be a shock, but it’s kind of same shock as a bird, kicked out of the nest by a parent.
You have to leave the nest in order to learn to fly.
And, surrounded by twenty-somethings talking about order-n-linear algorithmns and the efficiency of recursive vs. linear solutions, that is what suddenly hit me.
I didn’t fit in, and that was good. It was time to leave the nest.
Over the next few posts, I will be talking about people who are going against the grain, re-inventing themselves and their careers - often against startling odds and with two hands tied behind their backs.
Let’s learn from them.
More to come.
Wait! Which sort algorithm to choose? Quick sort? Bubble sort? Insertion sort? ....