“Think of every venture round as the last capital you’ll ever raise. Spend it wisely.”
Mike Abbott is a partner at Kleiner Perkins Caulfield and Byers, a venture capital firm. As the former vice president of engineering at Twitter, he brought his experience to the firm in 2011 and now focuses on digital investments. He has a bachelor’s degree in biochemistry from California Polytechnic State University and has completed coursework towards a Ph.D. in molecular biology/pharmacology from the University of Washington. We asked him 10 questions about his accomplishments at both work and home. Find out below how he gets his news, his biggest missed opportunity, and what he would rather be doing in Argentina and Nepal.
Fortune’s annual Brainstorm Tech conference brings together the best and brightest minds in tech innovation. Fortune periodically turns the spotlight on a different conference attendee to offer their personal insight into business, tech, and entrepreneurship.
1. What is the best advice you ever received?
“Just keep pushing.” In short, it pays to be persistent. Life always presents challenges on many fronts, and focusing where you want to go can keep you stable when your world around you is spinning.
2. What was the last book you read?
Quiet by Susan Cain. Found it both helpful for areas that I struggle with personally, as well as to help me have more empathy.
3. What would you say to a group of young people looking to enter the tough job market?
Focus on just doing not talking. In the end, what matters are your core skills and how you communicate them to others. Go build things that help you in life – whether interacting with friends, family and/or co-workers.
4. What was your biggest missed opportunity?
My biggest missed opportunity was also the best decision I’ve ever made. I turned down the opportunity to be VP of engineering at Facebook several years ago in order to pursue the woman who is now my wife.
5. How do you get your news?
I primarily listen to folks that I have the privilege to meet with, the folks I follow on Twitter, and I read, in particular academic journals, blogs and the paper version of several periodicals. And then I contemplate while running and swimming.
6. What was the most important thing you learned in school?
The importance of intense focus. The ability to shut out external ‘noise’ and apply your mind to one problem/thought is incredible powerful. Frankly, I am finding this increasingly difficult to do in our attention economy.
7. If you could be anywhere in the world right now, where would you be?
Patagonia, Argentina. I had the opportunity to trek, mountain bike, and river raft there a couple of years ago – it is an amazing part of the planet! However, returning to the Buddhist monastery in Tengboche in Nepal also is quite appealing.
8. What is your greatest achievement?
Fatherhood – without a doubt.
Professionally, I’ve had the chance to be part of multiple teams that have built products now in use by both consumers and companies. From building an enterprise business out of my house, Composite Software, which remained independent with over 100 employees for 12 years until recently Cisco acquired, to helping redefine, build, ship webOS at Palm, and to rapidly expand the engineering team at Twitter to stabilize the infrastructure – I have been very fortunate to have had these opportunities.
9. What business or technology person do you admire most? Why?
Bill Campbell. [The chairman and former CEO of Intuit and current Apple board member.] Bill embodies deep empathy, deep experience, and deep care for people and companies. He is an amazing person and can provide insights and guidance unlike any other person that I have ever met. I am privileged to be able to call him a friend and mentor.
10. What technology sector excites you most?
Deep learning, which is a new approach to achieving artificial intelligence with applications in daily living, digital health, and other new use cases. Deep learning is a new area of machine learning research, which has been introduced with the objective of moving machine learning closer to one of its original goals: artificial intelligence.