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The day began as every other, but as soon as I arrived at work, I received an email: “Happy One Year Anniversary!” I love working at Amazon Web Services because I am on a continuous learning path. I run the group that helps to migrate Enterprise workloads onto the AWS Cloud. I have the opportunity to work with some of our largest customers and partners like VMware, Microsoft, and SAP.

Learning is a core part of my role at AWS, but it is also about sharing those lessons. To celebrate my one-year anniversary, I want to share some of the things I’ve learned at AWS.

6 Lessons I’ve learned in the past year:

1.    Customers first. This lesson is still the most important in my journey at AWS. Customers are always first. I love the story of Low Flying Hawk. At AWS, we genuinely read the forums and listen to customers. A person with the alias of Low Flying Hawk was constantly suggesting new features in one such forum, and the team came to look forward to that feedback so much that they would ask in meetings “What would Low Flying Hawk say?” Low Flying Hawk didn’t spend a huge sum with AWS, but this person’s input was so valued that we recently named an Amazon building Low Flying Hawk to honor the importance of what those comments and requests represent to AWS. It is real and lived hourly. Great products and services come from deeply understanding your customer. If we jump straight to a solution without spending time thinking about customer needs, we limit our options for inventing a delightful experience for customers.

2.    Learn from others. At AWS, we don’t present PowerPoints but we read six-page written narratives. To learn more about this, Jeff actually discusses it in the Amazon Shareholder Letter here. It was a bit hard to get used to at first, sitting quietly and reading, but now I get the importance of this process. Once we are done reading, anyone and everyone can ask a question or make a comment. It is a conversation starter to achieve clarity and customer focus. We read, discuss, and debate. We revise and make the idea better with each iteration. We push ourselves to invent on behalf of the customer. It is a pure learning experience that makes the ideas better and stronger. For example, our team had dreamed big on a new approach, but through our narrative process we found out that the technical approach just wasn’t going to work. And that’s what you have to do. Dream big but iterate and go deep, get the data, and figure out if the idea really has legs

3.    It’s usually the second, or third idea. One of my customers, Bridget Frey from Redfin, shared with me an illustration and story from one of her favorite graphic novelists, Kazu Kibuishi. His drawings are haunting, beautiful and complex. But they don’t start out that way. In his creative process, he forces himself to use the least expensive notebook paper for his initial drawings, to remind himself that his early drafts are disposable. It’s a reminder that innovators can fall into this trap, where we’re too precious in our designs. We refine a single approach, rather than starting anew with different ideas on different sheets of paper. Innovation doesn’t usually feel like one inspiring idea after another. But as you experiment you test new theories. You fall in love with an idea, you give it everything. And then you realize you were wrong, and you have to be ready to pick yourself up and fall in love with the next idea.

4.    It’s ok to fail! My team had a tough problem to solve and at first, we took a pure tech approach. We tried to completely automate a migration task, thinking technology was all people would need to get the job done. We thought we were being innovative – but we were building something that our customers couldn’t leverage until the culture inside their organizations was addressed. So, we started offering Digital Innovation workshops. A big part of innovation is just getting really good at learning from the ideas that don’t work, so you have space for the ones that will.

5.    AWS democratizes technology! I knew that the AWS Cloud was very powerful but I had no idea how much it was impacting customers. Recently at the San Francisco Summit, I heard the story of how it is powering the leaderboard of Peloton, helping Cerner in healthcare, and even making it easier to use machine learning with Adobe. Things that AWS has created like Amazon SageMaker are just too cool! Amazon SageMaker removes all the barriers that typically slow down developers who want to use machine learning. Machine learning often feels a lot harder than it should to most developers because the process to build and train models, and then deploy them into production, is too complicated and too slow. Or consider the new launch templates developed from 100s of customers wanting to make it easier. Launch templates for Amazon EC2 have made it flexible and easy for our developers. With launch templates you can apply access controls, ensure tagging policies, and even make sure that developers in the organization are only launching the most recent, patched version of your AMIs.

6.    Make history. The Amazon mantra is work hard, have fun, and make history. I am motivated to help our customers make history. I’ve learned a lot as I have gained more experience working with a great team on great projects. For example, working on the partnership with VMware to reduce the cost of hybrid cloud while offering unparalleled access to the cloud will be one of those partnerships of a lifetime.

Sandy Carter is VP of Amazon web services and Forbe’s 2016 Digital Influencer & CNN’s Top 10 Most Powerful Women in Tech; recipient of more than 25 social media awards for innovative and successful implementation of Social Business techniques.  Invite Sandy to your next event!

I’ve taught at Stanford University for more than twenty-five years and it’s a privilege to “warp young minds.” You may not realize it, but not everyone wants to build a better smart phone app, a new way to talk to his or her friends, or another way to buy something. Many students want to do something meaningful—something that might change the real world. But, what might that be?

Let’s start by realizing the global economy is driven by developing economies. Developing economies are driven by population growth, which is why Southeast Asia, Latin America and Africa are interesting. Africa is expected to account for more than half of the world’s population growth between 2015 and 2050. Nigeria is projected to become the third most populous country in the world before 2050. Vietnam will soon have a population of 100 million with an average age being just 30 years old.

So what do developing economies need? They need infrastructure: power, water, agriculture, transportation, construction, healthcare and telecommunications. But will these be delivered the #firstworld way? Would you put up landlines for telecommunications in Rwanda? Of course not; instead you’d skip the old technologies and go straight to implementing a 4G cellular network.

What about electricity? Would you build giant, centralized, coal-fired plants and hierarchical power distribution networks? No, you’d build a distributed grid of solar, wind, battery storage, and hydroelectric generators all managed by software. You might even never go to AC and build a DC network on day one.

What about healthcare? There is no way for developing economies to build enough medical schools and hospitals to replicate a #firstworld healthcare system. But, maybe it’s an opportunity to re-think healthcare. Today, hospitals are buildings with expensive machines sitting next to the people that use the machines. In the world of computing, we used to do it the same way; people were located next to their compute and storage machines. But twenty years ago we discovered networks, and now the servers are centrally located and the people are all on the network. So why don’t we do the same thing with healthcare machines?

But this doesn’t have to just apply to developing economies. Today, there are about 500 children’s hospitals on the planet and on average there are 1,000 machines in each hospital. What if we could connect them all? The consumer Internet took off when 1,000,000 machines were connected. Maybe with 500,000 machines connected children’s healthcare could become dramatically different. Sadly, most of the attention today is on EMR/EHR applications, where doctors spend their evenings and weekends typing data into these pre-Internet applications. But the massive amounts of data, which will power AI applications is not there. The data is in the machines: the blood analyzers, gene sequencers, CAT scanners, and ultrasound machines.

These are just a few examples of the potential of software to change the planet. During the past 15 years, the Internet revolution has redefined business-to-consumer industries such as media, retail and financial services. In the next 10 years, according to the World Economic Forum, the Internet of Things will dramatically alter power, construction, agriculture, healthcare, textiles, mining, packaging, oil, gas, buildings, transportation, which together account for nearly two-thirds of the global gross domestic product.

Software has the potential to change the world—the real world. And unless we’re all moving to Mars—and I know some people are working on this—we’ll have to operate much more precisely. Next generation software can transform the planet in everything from power to healthcare, shrimp farming to textiles, and water to transportation. So if you’re a student at Stanford or any other university in the world, you can really change the world.


Timothy Chou has been lucky enough to have a career spanning academia, successful (and not so successful) startups and large corporations. He was one of only six people to ever hold the President title at Oracle.

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