As Descartes Labs grows rapidly, we’re constantly adding to the executive team to support our continued success. That’s why we’re proud to announce Gary Lang, as our new Head of Engineering.
Most recently, Gary was VP of Technology for Amazon Business. During his time there he grew the team from 0 to 450 engineers, worked on the Amazon HQ2 project, and was responsible for building the technology behind Amazon Business. Gary‘s executive career includes stints as the SVP of Product Development and Cloud Operations for Blackboard, running development at Microsoft for Visual Studio and .NET, and a career at Autodesk where he started as a programmer for AutoCAD for the Macintosh and ended up the Vice President of Platforms and Global Engineering leading a team of 1,100.
I am so excited to have Gary and his wealth of experience here at Descartes Labs, as we continue our ambitious plan to create a data refinery to understand the planet’s natural resources.
I sat down with him for an informal Q&A to dive deeper.
Mark: How do you think technology can help companies with traditional physical businesses?
Gary: The history of software has always been one of automating previously manual processes. We’ve done well in enabling humans to do more in a set amount of time, particularly for functional parts of businesses that are outside of their core missions, which in many industries are physical products and services. Now, we are able to automate the actual mission of these companies in ways that these physical businesses can use to deliver on their core mission or to transform that mission to address new opportunities.
Mark: What was your first job? How did the experience inform the executive that you are today?
Gary: Newspaper carrier. I found a way to identify new arrivals to the city and then cold-called every potential new subscriber, rather than just new arrivals on my five-block paper route. No one, including my manager, could figure out how I did this, and I wasn’t about to tell anyone. Because of this, I won an absurd number of prizes and trips. This experience taught me that prospecting for sales in unique ways can differentiate a business and create a competitive advantage for a business of any size. Since then I’ve always looked for an analogous opportunity to drive sales in ways that help my companies win customers.
Mark: Tell me about how your experience at Amazon changed the way you look at technology and the customer?
Gary: I have always been customer focused/human-centric with respect to products, but everything at Amazon starts with the customer and works backward. This simple operational tenet institutionalizes product and user empathy, just to name two benefits. From spending money on furniture to selecting product features we should always ask ourselves how customers will benefit.
Mark: Do you see any similarities between Descartes Labs and Amazon as far as category creation, back-end technology, etc.?
Gary: Amazon is well-known for applying machine learning towards product recommendations, fulfillment, and cloud-based platforms and services for facial recognition, natural language processing, and other enablers for customers. Descartes Labs is where the rubber provided by those kinds of services meets the road, which often requires deep innovations that platform companies aren’t positioned to address.
Mark: What drew you to the role at Descartes Labs?
Gary: The Descartes Labs opportunity seems to be as new as deep learning’s moonshot success with AlphaGo. It could not have been done more than 5 years ago. When I ran product development of geospatial software for Autodesk, our customers asked for analysis at the intersection of satellite data and LiDAR data, but we had no practical infrastructure to provide it. While still difficult, Descartes Labs seems poised to do these things.
Mark: What are your impressions of the team and company so far?Gary: This is a labs team in the strictest sense. We are doing the seemingly impossible here. Having recently seen the Apollo 11 documentary, I see parallels between the ambition and noble pursuit of that moonshot, and the moonshot of actually understanding what the planet is doing in real-time.
Mark: In a high growth startup, deciding where to focus and what to say no to is critical — how do you keep a team focused and help them know what to say no to?
Gary: It’s often the case that being customer-obsessed leads to good decision-making here. The best companies use that as one of their simplicity drivers. There are others as well. But parsimony is to be valued across the board at startups, for both financial- and implementation-reasons.
Mark: What do you find more exciting about relocating to Santa Fe?
Gary: As a native San Franciscan, I think we’ve reached peak Silicon Valley at the same time that persistent, high-definition comms systems and ubiquitous cloud collaboration came along just in time to ameliorate its effects. In a global economy for products, it’s now a requirement, not a feature, to be able to conduct global business from anywhere. Why not do it from the most beautiful state in the US, New Mexico?
Mark: What are you excited to bring to Descartes Labs and what will you focus on this year?
Gary: Having studied neural networks in college and having been told that it was impractical then, I became excited about them again after AlphaGo beat Ke Jie, the world’s champion Go player because it was clear that Moore’s Law had made them not only practical but game-changing. From then on I became very focused on applications of machine learning at Amazon. I also ran geospatial product development at Autodesk, where I co-founded the OSGeo open source foundation for making geospatial tools widely available. I’m excited about applying those learnings to providing game-changing products and services to Descartes Labs customers.