In this presentation, Yashar outlines a strategic framework for market prioritization aimed at early‑stage AI companies. He emphasizes targeting industry leaders to create halo effects, using small niche markets as dominoes to tip into larger markets (illustrated with Tesla’s early focus on sports‑car enthusiasts), and seeking open lanes rather than crowded spaces. He cites Amazon’s initial 100% solution for books as a model for owning a high‑value vertical before expanding. Yashar stresses the importance of leveraging partners such as AWS for visibility, validation, and introductions. The company’s mission—building more capable, ethical, human‑centered AI that limits bias, preserves privacy, and democratizes access—guides the choice to focus on consumer‑centric devices (smartphones, smart home, teleconferencing, driver monitoring) rather than the highly competitive autonomous‑vehicle space. During the Q&A, he addresses how to navigate latent demand when decision‑making is distributed, recommending identification of both technical advocates and business drivers to create a bottom‑up/top‑down influence chain. The talk concludes with a recap of staying true to mission, leveraging core strengths, and using domino effects and open lanes to accelerate adoption.
Questions this video answers
Identify signs of latent demand such as internal teams building solutions. Find both a technical advocate and a business driver within the organization. Use a bottom‑up approach to influence technical users first, then let them influence the business buyers.
Chapters
with that base, but also helped establish an elite brand and ultimately drove strong network effects. But the team early on was also full of technologists, so they focused on the stability of the technology, stability of platform, and that allowed them to differentiate their offering from others in the space. As we— as you enter new markets, it's important to kind of look across and identify dominoes that may exist to drive kind of favorable adoption dynamics. So in AI, it's, it's, it's that space that we play in. It's a lot of majority of companies follow industry leaders. So it's important to target those industry leaders. It's important to showcase success in a couple of the verticals and there's kind of halo effects that then drive adoption. To go back to a familiar example, let's look at Tesla. When they started, they realized to get to low-cost mass production, their ultimate vision, they first have to change the perception of electric cars. It targeted a very small group of sports car enthusiasts to ultimately help make the electric cars cool. This helped propel the brand in the mainstream, tip the dominoes into a larger market with the Model S, and a larger market with the Model 3. So they use these small markets to tip into larger and larger markets, setting up the dominoes for more mass adoption. Also, I think it's important in the early stages to really look for open lanes around competition. Instead of chasing the largest space, which oftentimes has the most competitors. It's tempting to chase a large opportunity, but I think oftentimes, you know, there are a lot of white space opportunities that are strategic that allow you to ultimately build a more interesting solution. And I think one of the questions we always ask ourselves is, can we provide 100% solution for a particular high-value vertical? Can we own the whole market for this particular niche? I think a great example of this, a classic example of this is Amazon. They focused initially on selling books online, but they provided 100% solution for books before they even thought about doing anything else. And this really allowed them to understand and validate the online channel to consumers. They built capability they were able to leverage into other domains and other types of products. And ultimately, they built strong customer relationships that allowed them to cross-sell and build these longstanding relationships. It's important that you don't work in isolation and that you leverage your network and your experience of your partners. We've had a lot of support from AWS, outside support. You know, as a small company, they've provided us great kind of visibility across current and future needs and trends, allowed us to leverage the ecosystem to validate our assumptions and ultimately gain introductions to key clients. So it's important that You don't work in isolation and you really lean on your partners and their experience to gain that insight. Kind of to summarize, you have to identify and stick to your mission, identify your North Star, stay true to your DNA and leverage your core strengths to compete in the marketplace, identify dominoes to drive faster early adoption, and look for open lanes around your competition to help differentiate and scale faster. Where we ultimately landed is we have a mission statement, as I mentioned, to build more capable and ethical AI. This relates to limiting bias, preserving privacy, and democratizing access to these AI systems. We identified certain dominoes within the industry around certain types of products and use cases and leveraging halo effects from other industries to ultimately drive us to human-centered AI systems working with smartphones, smart home, teleconferencing, driver monitoring, and AI systems in this space. Well, I wanted to thank everybody. For kind of listening to me at 7 o'clock in the morning on a Monday morning, and I'm happy to kind of open it up to questions. All right, okay, so one question I think that often comes up is, I think, in these kind of markets is, you know, why not chase the largest, largest opportunity? And let me kind of maybe speak to our particular use case and kind of why we decided to go kind of a different route initially. So the, I think, the tempting thing in computer vision, and a lot of companies have gone this route, especially with synthetic data simulation in computer vision, is to look at autonomous vehicles, right? Lots of consumption, lots of investment, you know, a place where it seemed obvious to go with the technology. But when you look at the space, from a 20,000-foot level, there's a lot of competition, a lot of not only from external vendors that we may compete with, but also with internal teams, right? So if you look at Tesla or Waymo or others, you know, they're building these internal capabilities. And so for us, it was important to find an area that we can potentially own moving into kind of more consumer-centric devices. And also this aligned much more with our mission, which is to create more ethical AI systems. Deal with some of the issues around human-centered data that exist— privacy, bias, and other elements.
Feel free to drop any additional questions in the Q&A or in the chat below.
Okay, we have a great question coming in here. What should one focus on when there is latent demand and there's no single owner in decision-making? Yes, it's a great question. I think one of the signs we always look for is that there is latent demand. Oftentimes you'll see internal teams trying to build solutions, which is a great kind of indicator that there's something there that you need to build. Now, identifying a decision-maker in an organization is completely, you know, it could be a whole 50-minute talk onto itself. But ultimately, it's— you have to find someone who's going to be an advocate for you. We find that there's usually a technical advocate and a business driver advocate. So depending on the product, you may have to go bottoms up through the developers or come top down to the business heads. We found the kind of the right mix for us, at least in our product, was to find and influence kind of the technical buyers initially, or the technical users, and have them influence the business buyers.
Awesome. If there are no more additional questions, thank you so much, Yashar, for that great session. We'll have a lot more content throughout the day. Thanks for joining SAS early.
Well, thank you. Thanks, everybody. I appreciate it.
