Today, Madrona Managing Director Soma Somasegar talks with Typeface Founder and CEO Abhay Parasnis. Typeface combines generative AI platforms with its own brand-personalized AI, so all businesses can create content that is multimodal and on-brand. Typeface just announced $100 million in new funding, and Madrona couldn’t have been happier to participate in the round.
Abhay and Soma have known each other for almost 20 years from their time at Microsoft. But In 2022, Abhay left Adobe, where he was CTO and CPO, because he saw an inflection point coming that he wanted to be a part of. This was, of course, before ChatGPT and all the other popular GenAI tools that we’ve all been playing with this year even came out. Typeface has made waves quickly, attracting Fortune 500 customers and partnering with Salesforce and Google Cloud.
In this week’s episode, Abhay shares about the need to balance your passion and recklessness for going after a dream with a product that you know will resonate with customers. He explains that people relationships are the real currency when launching a new company, and how advisers are just as important as what he calls the flag planters and road builders that founders need to seek out, to help them on their startup journey.
These two industry veterans share all of this and so much more.
This transcript was automatically generated and edited for clarity.
Soma: Good afternoon. This is Soma, and I’m a managing director at Madrona. Today, I’m really, really excited to have this conversation with Abhay. Somebody that I’ve known for the last 20 years or so, and I’ve had the fortune to work alongside at Microsoft for many years.
More recently, Abhay has started a new company in the generative AI space called Typeface. He’s the founder and CEO of the company. This is really a great opportunity and something that I’m looking forward to, to having this conversation with Abhay. Welcome, Abhay.
Abhay: Thanks, Soma. Great to be here.
Soma: Great to have you on our Founded and Funded podcast series. But before we dive into the great work that you are doing with Typeface, you had a pretty successful career at Microsoft. Then went on to Oracle and did some great work in Oracle Cloud.
Then more recently, you were at Adobe as their chief technology and product officer. Great experiences across what I call amazing companies in the technology space. How did your experiences at these organizations shape and prepare you for launching your own company?
Abhay: I think, as you know, first of all, when you look at those journeys in the moment, there are different lessons. When you look back, there are different things you take away. I think if I had to synthesize across all those years, and amazing companies and different experiences, probably three or four things that come to mind. First, certainly with Microsoft and Adobe, it always starts with the product.
Building that deep technology moat, deep product moat, products that resonate with users. It is something maybe you and I maybe take for granted, having spent years in these world-class companies. But I think having that long-term orientation around building products and experiences that customers actually really care about, and building defensible IP and moats in them that can last decades.
As you know and from your journey, there are products that Microsoft has had 2, 3, 4 decades later that are still very relevant at Adobe. There are products like Photoshop and Acrobat that are 30-year-old products that are still at the gold standard. That’s amazing in an industry that changes every six months. I think having that long-term orientation product at the core moat, it’s probably the first lesson, I would say.
As we think about building a long-term business, is what are those long-term moats that customers are going to value and care about? The converse of that, which may seem a little bit contradictory, is that this is an industry that doesn’t really respect your yesterday’s success as much. Unless you really reinvent yourself today and tomorrow, what you did yesterday doesn’t really mean much, and so,
That second contradictory lesson, which is you got to go through a cycle of reinvention. Over my last two/three decades in these companies, some we got it right, some we didn’t do it in time. But I do think that notion of reinvention and facing disruptions in the industry that are bound to happen every five, 10 years, is probably the second lesson. Both, some we did right and some painfully we got wrong, and I think that teaches you as much.
Then maybe the last thing I’ll say is I think maintaining a beginner’s mind, where you’re constantly willing to learn new things. Because one of the challenges as you work in these big companies, you have amazing products, amazing successes, and amazing talent all around you, but sometimes that can get you very myopic. I think maintaining a beginner’s mind to keep looking around the corner and reimagining what the new world could look like, is probably, in some ways, the third big lesson, I would say.
Soma: That’s fantastic, Abhay. One thing that you mentioned and that resonated with me a lot is this notion of unlearning and learning or reinventing kind of thing. The good news is now you had the fortune to go from Microsoft to Oracle. Back then, it was a smaller startup called Kony and then to Adobe, so you had a variety of experience. Every time you go from one environment and one culture to another, there is some amount of reinvention.
You’ve gone through that multiple times, but all of these are what I call established companies in some way, shape, or form. Going from that to saying, “Hey, I’m going to be the first guy, and I’m going to start building everything from scratch.” The beginner mindset that you talked about, how easy or hard was it for you to go through the transition, particularly as you left Adobe and you decided to get on the Typeface journey?
Abhay: I would say this in two parts. There are things that you think you know when you are about to make a decision like that, and then there are things that you actually every day live through as you go through that journey. Hopefully, there is enough overlap between the two, but there are also things you can never anticipate. First, I would say for me, Adobe was an amazing journey, amazing company, amazing products.
The reason for me to start this company was this extreme burning desire that there is an inflection point coming in the industry. I’m sure we’ll talk about it. It’s interesting sitting here today when GenAI is all this rage in the market and I left Adobe and started this company. None of the ChatGPT, Stable Diffusion, DALL-E, none of those things had happened.
But there was a deep desire and conviction that there is a shift coming. I didn’t want to have any regret of not having participated in that in a deep, meaningful way. I would say that overriding desire almost makes you not really be very thoughtful about all the other dimensions you have to go through if you’re really passionate about something. I do think a little bit of that recklessness actually helps, if I can say that.
That said, I think when you do start as the first person, and when you are the person having to figure out how to do payroll, and how to actually register a company, and every state has a different law, there are a lot of things you take for granted that these big companies and platforms offer. I do think there is an amount of learning new things that you just don’t anticipate.
I won’t lie and say all of that is enjoyable or some of that I wish I didn’t have to go through, but it’s all actually good learning. I would say it’s been a fun ride. What’s been really gratifying so much, is that the people relationships you accumulate and build over the years, ultimately that is actually the real currency. In fact, I remember calling you when I was starting the company.
I think there are an amazing number of people around the industry, such as yourself, who actually just helped me quite a bit at no level of involvement and interest. I remember talking to you over breakfast before I had registered the company. I think that’s been the other incredible journey of entrepreneurship. In big companies, you have lots of people around you anyways.
But here, you really value the relationships and all the advice and perspective that others bring to you, as you go on that journey.
Soma: I think that’s a fantastic point, Abhay. Relationships matter, and you never know when they come in handy, but normally people say that as a founder and CEO, sometimes you are in a very lonely job. It’s really, really important to have the right support structure around you, in terms of people and relationships and how they can be helpful to your networking.
I think that’s a fantastic point. Let’s maybe now switch a little bit of focus and talk about Typeface. We know that Typeface is focused on delivering some valuable service to enterprise customers. Talk to us a little bit about, like, “Hey, what is the genesis of Typeface, and what unique challenge is it looking to address for enterprise customers?”
Abhay: If I step back and even before we get to all the exciting things happening with GenAI, and why that represents a unique moment in time in our industry and for Typeface. If I just zoom out, one of the amazing things that Adobe and my role at Adobe gave me a perspective with a lot of customers who were in the world of data, in the world of content and creativity. I would say one of the observations I had that led to the Typeface genesis, was you look at the last decade or so with all the transition to the cloud.
The data architecture in a typical enterprise has gone through a pretty big transformation. All the things around big data and ecosystems like Spark and amazing companies like Snowflake and Databricks and others, amazing innovation has happened in that ecosystem. You guys obviously have participated in quite a few of those companies. The key insight, Soma, in some ways, was correspondingly, the content stacks in most companies, have not yet gone through that reinvention and reimagination in the last couple of decades.
Yes, the mobile shift has happened. Yes, platforms like TikTok, YouTube, Instagram, Netflix, and Amazon have happened, but they all have their proprietary content systems. Unlike data, which went from those companies to open source into enterprise architectures, content had not had its inflection point driven by fundamental architecture change. The key idea was is there a step function change coming.
I think that’s where generative AI dialogue will come in, where there was an architectural shift coming, that allows you to reimagine the entire enterprise content lifecycle. Specifically, what Typeface.ai wanted to address is — most companies, when you look inside their content systems, today they will describe a content paradox. Either they can produce extremely personalized, high-quality content where they hire professional creatives or agencies, the marketing department leads.
That’s very much on-brand personalized content, but it’s not very fast and cheap to produce. Or you can do extremely high-speed, high-velocity content creation using modern tools, but you don’t get a lot of the personalization that you want. The unique thing we wanted to solve with Typeface, is can we finally bring the world of personalization and the world of content velocity into one unified stack?
That’s really the origin of where we started. Unfortunately, GenAI was the technology fuel, if you will, that allows us to reimagine that.
Soma: You mentioned this earlier, Abhay. Sometimes we are so caught up in things today, that you forget what the world was like even 12 months ago kind of thing. As you said, the world hadn’t heard about ChatGPT, DALL-E, Stabile Diffusion, or any of these other large language models. I remember when you and I first started talking about this where you talked about, “Hey, that is the modern data stack and everybody’s talking about data.”
What is the modern equivalent of that for content? I at least didn’t realize that we are right around the cusp in terms of large language models taking the world by storm. Thinking about, “Hey, where technology is evolving, though we necessarily did not at that point in time realize that large language models were going to take off like wildfire in this timeframe kind of thing.”
But I think being there at the right time with the right idea, is always helpful, and I think it has given you a fantastic start thus far.
Abhay: Yeah. No, you’re absolutely correct. As much as I would like to claim I had a complete insight into exactly how this was. But if you had asked me back last May, which you did, I would’ve probably said this is still three to five years out, and it’s going to take us a while to get AI systems.
By the way, it still may take us that time for enterprises to fully get there. But clearly, what happened with ChatGPT, it has accelerated this into the broader consciousness at a much faster rate than I would’ve thought. It is exciting, but I don’t think we should short change still the road ahead. It is a long road. There’s a lot to do to make this a mission-critical fabric for companies.
Soma: Completely agreed, Abhay, completely agreed. You and I have been in the technology industry in some way, shape, or form for many decades now. We’ve seen the advent of client-server computing at Microsoft. We’ve seen the advent of the web, and we’ve seen the mobile platform taking off amazingly well. Then more recently, the cloud has taken the world by storm. Each of these platform shifts has been progressively and almost exponentially becoming larger and larger and larger.
When we looked at cloud computing, we felt like, “Hey, for the first time, this could be a multi-trillion dollar opportunity for those who decide to play versus not kind of thing.” You fast-forward 10 years or 12 years later, we are now at the cusp of what we call the AI revolution, and some people call it like generative AI, but it’s broadly AI. In your opinion, what distinguishes generative AI from previous technological waves, such as whether it’s an internet or mobile or cloud thing?
Then, more importantly, do you see generative AI being a key differentiator and an opportunity for enterprises, and for how enterprises and the future of work happen for people in a variety of ways?
Abhay: If I had to distill this maybe into a couple of frameworks that I use right now to think about what’s happening with generative AI, first of all, I think you will agree that the rate of change in this particular wave is unlike anything else we have seen before. I think we are fortunate, you obviously, with the desktop shift at Microsoft. But then, even the cloud shift or mobile shift that I was fortunate enough with Adobe and others, they were amazingly profound.
But the rate at which right now generative AI is shifting all layers of the stack simultaneously. There is a foundational platform being built by big players like Microsoft, OpenAI, Google, and others. There is workflow-level innovation being driven by existing companies, and, hopefully, new companies like Typeface.ai. Then there is an experience-level breakthrough right in front of our eyes where natural language becomes the new experience.
But if I had to give you three things in why this shift is different, I think in technology, the role of computers is going to change and evolve from machines that were just computation or automation machines in our lives.
They will do number crunching, they will drive productivity. To then, as soon as with these AI models, computers become machines that can see, hear, sense, and understand the world around us. These machines go from just being computational, number-crunching devices, to true personal assistants in our personal and work life. I think that the change of role of computers in our life, I think is going to be very, very profound, number one.
The second thing I would say is what I call escaping the glass, which is, for the first time, we are going to get to a much more natural way of interacting with these devices and computers. As you remember, when iPhone came out, multitouch felt like such a profound change because it was direct manipulation versus indirect with a mouse and keyboard. Now, imagine escaping the glass entirely, and being able to use natural language in your voice or in how you express.
If you could communicate with machines at that high fidelity, it’s going to feel as big a jump as multitouch was, if not bigger. I think to me, that escaping the glass is the second change that generative AI is going to drive. The last one is what you asked, is what I call rewiring the enterprise. Which is as profound as these GenAI systems will be in our personal lives, like ChatGPT shows, I think the real profound impact is going to be in how entire industries and economies and companies get rewired.
If I had to just succinctly say today — if you look at most companies and the role IT systems and cloud systems play, they are a bunch of siloed, computational apps and systems. Then we, as users, knowledge workers, extract information from one system, and we do the job of brokering and connecting across six systems, and synthesizing insights out of it. I think I imagine a world with GenAI, where enterprises will become extremely fluid knowledge fabrics.
Where the entire fabric of systems in the natural language layer will let you tap into any application, any system. The marginal cost of getting insights and telling stories and expressing yourself in compelling ways, is going to go down so much. That we will look five to 10 years back at what the first-generation SaaS applications looked like, and they will look far worse than what green screens look like when you compare it to iPhone.
Because I think they’re fundamentally going to change the semantic understanding of how we communicate with these applications in enterprise.
Soma: I love the thinking and the articulation, Abhay. Particularly when you think about enterprises having the layer of the knowledge graph, for lack of better words, and then being able to tap into it using natural language. I think even just thinking about it, the opportunities are boundless kind of thing. I’m sure what we are going to see and what we are going to experience in the coming years, is going to be fascinating here. Abhay, before I forget, let me congratulate you.
Recently you had a bunch of phenomenal announcements that all came together. On the one hand, you announced $100 million of new funding in a funding round, which is fantastic for a company of your size, scale, and your aspirations. On the other hand, you also announced the launching of your product, so congratulations on that. But then the thing that also caught my attention was some strategic partnerships that you announced with industry leaders like Google Cloud on the one hand, and Salesforce on the other hand.
Congratulations on all these things coming together. Looks like great building blocks for what is potential and possible in the future. But the thing I want to ask you specifically is, how do you envision these strategic partnerships helping you or accelerating your company’s growth and success in the market?
Abhay: Yeah. First of all, thanks for that and kind words. Before I answer your question, also great to have you, as Madrona and you personally have been involved in my journey with this company from day one.
It was exciting to have you guys officially also join that round. I think you guys have been incredibly helpful to us, even before you were investors.
Soma: Thank you, Abhay.
Abhay: It’s a pleasure to be part of this journey. Thank you. Look, at the end of the day for us, as you said, the investment is a great milestone, but really the bigger one is what you said, which is some of these partnerships and strategic partnerships. The way, Soma, we think about this is in a couple of dimensions. On the product front, a big shift like this GenAI that is happening at the industry level, you are not going to be able to go alone.
You really have to find ways to partner with other players in this industry that have strengths at different layers of the stack. One way we look at these partnerships, and we have a deep partnership with Microsoft as well in the work we do with Microsoft and OpenAI. With Google, we announced a partnership with their AI models. One way we think about it is can we stand on the shoulders of giants? They’re doing some amazing work at the platform layer of the GenAI stack.
We don’t really want to be building that capability. Having deep collaboration, and deep access to what they’re building, allows us to innovate faster at our application tier. That’s number one. Number two, as I talk to a lot of users of GenAI use cases, they want these GenAI capabilities like Typeface to be delivered in the flow of the work where they already are. That they don’t want to go to some new application every time they want to use some new generative workflow.
The second part of these partnerships for us with Google announced, for example, we are going to bring Typeface right inside your Google Workspace application. Or if you’re a Salesforce Marketing Cloud user, we want to be able to bring Typeface content generation right inside your email marketing application, so you don’t have to go. I think in the flow of work is a key strategy for us as a company, and these partnerships accelerate that.
But lastly, I would say probably the most exciting from a business standpoint, is there is an incredible opportunity, as you know, with GenAI. Every enterprise around the world is starting to actually ask the question around who are the partners who have best-in-class solutions. For us, a big part of these partnerships was how can we rapidly scale Typeface.ai to the opportunity that exists in the market?
If these large ecosystems and companies like Salesforce, Google, and Microsoft, if they can help us scale the company and get in front of a lot more customers a lot quicker, then that’s actually incredibly not just exciting for us. But frankly, we think it’ll accelerate the overall adoption of generative AI in the marketplace.
Soma: Absolutely, absolutely. One of the other things that you guys announced recently, is that you launched the product, and you’ve got a set of customers now using your product day in and day out kind of thing. I’ve always been fascinated by when you’re going through the early days of designing a product, you want to have customer input.
You want to have early design partners working with you to say, “Hey, what is working? What is not working? What is good? What is not good?” Can you talk a little bit about that iterative process that you went through this past year to get the product to where it is today?
Abhay: I agree with you. That’s been one of the most fascinating aspects of both the entrepreneurial journey because when you have big companies with big ecosystems, that’s a little bit different. But also when you’re on a bleeding edge like GenAI, there is a lot of stuff happening not just with technology, but how these companies adopt new tools, their processes, their culture. I would say maybe if I had to give you my introspection on last year with customers.
First, the level of excitement and interest from customers around generative AI is just off the charts. I know you know that with all the investment and activity going on. But a little bit of what’s different, Soma, in my mind, is this is not just blind interest in terms of just some cool demo or let me just put a cool app out there. There is a real value orientation even in these early days that I’m finding.
For example, they all love the promise of these GenAI systems being capable of generating amazing content, but they’re asking, “Okay. Tell me how it’s going to help my top line, either customer acquisition or retention goals.” One, I actually think that value orientation is a good thing in the long term for both customers and startups. But frankly, is a little bit different than some of the maybe other hype cycles where sometimes you are looking for a use case, you don’t really know what exactly this thing is going to be.
One, I think from day one, and when we engaged, customers pushed us very quickly towards, “Hey, here are the three use cases that we would like to get some major ROI in. Can Typeface and GenAI help there?” That’s going to be number one. Number two, while the interest has been there all the way from C-level audiences in every company, a lot of the practitioners are already out there trying out these tools on their own. We have all seen that. Our kids are using ChatGPT for their homework assignments.
This is one of those where the collective awareness of these techniques, do mean that enterprises are more inclined to figure out how to really safely adopt this. That’s been the second thing. But I will say maybe the third thing, which has been extremely instructive for us, and we are actually positioning Typeface to do this, that this kind of change is not just about technology. There is a whole process, culture, organizational change, rapid re-skilling safety and compliance issues around AI.
I think there is a full 360 dialogue that we are finding we are having with customers. In some ways, Soma, even as a startup, we are not just playing the role of a technology provider, which we obviously are. But they are really looking for a thought partner who’s going to shape their generative AI strategy and evolution within their own business. I would say maybe the third thing, which is still early, is developing a maturity model for generative AI.
Which is how do you adopt, and what are the stages of maturity a typical company goes through? I think that’s been fascinating to jointly work with a lot of our customers.
Soma: That’s a good set of things to hear about, Abhay. Thank you. As an investor, I get asked a lot about this, “Hey, what do you focus on when you decide to make an investment?” I always say, “For me, it starts with the team, it starts with the people.” Because I truly believe that building a world-class team is absolutely crucial for any successful and durable company. You put together, you grow rapidly when this past year in terms of your early team kind of thing.
Can you talk a little bit about, “Hey, how did you pull together your team?” What are some of the attributes or qualities that you’re looking for in your founding team and in your early team members? Then equally importantly, culture is something that everybody talks about, culture is important. Are there specific things that you had to do to get the right culture from day one, or how is that coming along for you?
Abhay: First, I would just start by acknowledging how fortunate and lucky I feel — this is one of those where I can’t sit here and tell you that I planned this exactly this way, and this was all exactly choreographed. But as you know, especially with inspiring and attracting and getting people on a journey, especially world-class people, they all only do this when they believe deeply in a shared mission and shared conviction, and shared values and culture, as you talked about.
First, it’s been incredibly gratifying to see back to our earlier discussions around the relationships you build over the years. One of my litmus tests in my career, Soma, and I know you share this in your own career quite a bit. Is how many people across different stages of your career would be willing to blindly follow you down a dark alley without knowing where it leads? In a very fortunate way, a lot of the early team are people actually I have been fortunate enough to work over the decades either at Microsoft or at Adobe, or at Google, LinkedIn.
First, it’s been incredibly lucky in terms of how people actually joined early on. I do think there are some things we have been very intentional and thoughtful about, and we remain so. Which is first, for a journey like this, you really want people who are deeply, deeply passionate about technology and building breakthrough products, because different people are wired for different kinds of journeys. This is one that’s super exciting, but it’s also full of ambiguity. People who are going to thrive on ambiguity.
Then one terminology I use sometimes, Soma, internally is there are two kinds of people you want to bring on a journey in at least a software product. There are flag planters, who are going to plant new flags around new ideas, new innovations. Then there are road builders, which is once you know where you are going, you need a very systematic operational excellence. I think for us in the first year, certainly, we needed a lot more of flag planters, because it’s a space that’s so new and dynamic.
We wanted to make sure there are enough people who are scrappy and have an agile mindset, who will thrive on ambiguity — but are really inspired by exploring ideas that nobody else has explored. I think that’s been one of our core tenets is can we bring people? One of the interesting balancing acts for us is to find people who are that scrappy and nimble, and these agile mindsets and are willing to go on journeys like that. But if we could also then find people who are at the same time seasoned in the enterprise software, and understand the world of enterprise. Understand the experience of working at large-scale companies like Microsoft and Adobe, and Google, and we have been very fortunate to find that rare breed of talent.
You know quite a few of the team members, but we have folks like Vishal Sood, who is our head of product. He is an amazing leader with large-scale experience in big companies like Microsoft, but is as startup wired as any. I think finding those people has been extremely gratifying. Maybe the last thing I’ll say, a lot of people think about team building as who are the members of the team which matter, but I actually think it’s equally important around who are the advisers.
Who are the people you surround yourself with? Again, I’ve been very fortunate. You were one of the first people I had called on, and I think those people help quite a bit in your formative stages because they’ll warn you around the blind spots you may not see. Or they have seen the pattern matching across many other companies or ventures. I think finding enough sounding boards and people who are really invested in your success is as much a part of team building as the core team itself.
Soma: That’s cool. That’s great to hear that, Abhay. This last year has been fascinating, as you’ve seen a number of what I call generative AI applications coming into existence. I can’t talk to a company anymore without them talking about generative AI in some way, shape, or form, whether they’re an existing company or a new company. But as you very well know, Abhay, developing generative AI applications is a complex task.
Okay. You got all kinds of different large language models to think about, which off-the-shelf models to use versus not. Which one do you take a bet on for which use case or which scenarios, keeping costs and performance in mind? Furthermore, while applications like ChatGPT engender what I would call general-purpose solutions, enterprise customers often want customization and personalization.
So on the one hand, the world of generative AI is going through what I call a rapid cycle of innovation. What stood six months ago may or may not be standing today, and what is standing today, may or may not be standing six months from now. The rate of innovation is very rapid. From a Typeface perspective, how do you stay ahead of these advancements, these innovations, these changes?
How do you make sure that Typeface.ai is A) on the leading edge of technology adoption? And B) marrying that with, “Hey, what do my enterprise customers need in terms of personalization, customization? How do I bring that all together?” How has it been for you?
Abhay: That’s a great question, and in fact, I would say it’s a constant tweaking and learning journey, as we said at the beginning. But I do think there are a few principles we have evolved over the last year or so. As you said, it’s only a year, so it’s still early days. But first, in this space, if you’re trying to be a leader in your category, you have no choice but to be very close, I would even say dangerously close to bleeding edge.
There’s so much stuff happening every day, and you have to have these lightning rods in your team that are going to constantly stay close to where the bleeding edge is. Now, the trick in generative AI is so much happening in ecosystems — open source, proprietary platforms — you cannot chase every single idea. I think the trick becomes which of these are fundamental shifts that you should pay attention to, and which of these are okay for you to just ignore?
In fact, saying no to some really good ideas becomes actually quite an important skill in this space, because there’s just so much happening. You could easily get distracted with 10 new, shiny objects every Monday morning, and you can’t really build a business that way. I would say one, I think I’m fortunate enough, we have people who are what I would call our GenAI scouts. That they are out there. They are in the ecosystem. They are hanging out in all the Hugging Face and all the community papers.
They will bring back in some ways the signal versus noise around, “Hey, LangChain is worth paying attention to, but maybe this other thing is not right now worth paying attention to.” We do that, and I think we do that reasonably well, but we obviously need to keep at it because it’s every single day thing. I think the second thing we are trying to do is constantly remind ourselves and the team that our job is not to just exercise these cool, new frameworks and technologies and models for the sake of it.
But it’s the product and experience centricity in what the enterprise customer is actually going to want. In fact, one of the things I’ll share as an example. When we started adopting generative AI models for some of the marketing use cases, turns out we could use a lot of the classical computer vision models to do a lot of other things that customers wanted, that had nothing to do with generative AI. But when combined with generative AI, they become a lot more interesting.
Being able to maintain that experience and product centricity so that you don’t get enamored with, “Now, there is a 50 billion parameter model, and now there’s a 300 billion parameter model, but does it matter? Does it matter to the customer and the use case?” Then maybe the last thing I’ll say, this is especially important for enterprise. Not every single thing enterprise customers care about is the most flashy, glamorous, sexy demo of a new GenAI feature. They do care a lot about compliance and security, and governance, and IP leakage.
We try to make sure that while we innovate on the GenAI side, you also innovate on bringing that into the existing “meat and potatoes,” if you will, of their existing environment. That’s been great. Maybe I’ll say one last anecdote. One of the things that’s been fascinating — the team actually just organized a hackathon. I know lots of startups do hackathons. But the team just, without asking anyone of us, they planned it, and 48 hours later, basically, they showcased six or seven projects that came out of those 48 hours. I mean, I was blown away by not just the sheer pace of innovation that they were able to bring with GenAI, but then they had a lot of ideas around how to deliver it as a value to enterprise customers. I think fostering maybe, that harnessing that energy is probably the ultimate answer to your question. How does the team go innovate in that space?
Soma: I’m glad you guys are doing that because these hackathons in my mind, and we’ve done this at Microsoft, we’ve done this in other companies. Hackathons give people a chance to show what is possible. The energy that people bring to the table and what they walk away with is transformational.
It’s a transformational kind of thing, so glad that you guys are doing that. Before we wrap up, I thought we’ll close with one little fun thing here. The next three or four questions I’m going to ask you, let’s do it in a rapid-fire format. I’ll ask the question. You don’t need to think too much, just like whatever comes to your mind, boom. Okay?
Abhay: That’s dangerous.
Soma: But I got four questions here, so let me go through them one by one. The first one, besides Typeface, which company building an intelligent application are you most excited about today?
Abhay: Yeah. There’s a lot going on, as you know, and I do try to stay by using lots of applications. It’s dangerous to call out one. I would just say in my personal workflow, there are lots of companies and tools I’m excited about, but there’s a company called Perplexity, which is building a very interesting hybrid of search with a Q&A. I’m finding that very useful and insightful in a daily workflow that I’m spending some time with new modalities, like what’s next with video and 3D.
A company like Common Sense Machines I’m experimenting with what comes next with generative AI, being able to generate entire games, if you will. That’s been exciting. But even then in the market, companies like Runway, they’re doing some phenomenal work in reimagining video workflows. I’m very excited with the new modalities around video, audio, 3D and how that changes all the workflows.
Soma: That’s great. That’s great. Next question. In your opinion, what would be the greatest source of technological disruption over the next few years?
Abhay: I would say the notion of natural language as a way to manipulate software, is going to actually change what we consider the role of software in our life. In fact, they’re going to probably start feeling more directly embedded into various industries and workflows like biology and health.
Soma: If you look at the last 15 months, Abhay, since you started Typeface, what is the most important lesson you’ve learned, and how has it shaped your approach to entrepreneurship?
Abhay: That’s a big one. I know you said one. I’ll give you two that are probably close. First, I would just say adaptability in the face of change. I know lots of people say it, but I’ll just share maybe 10 seconds anecdote. We had come out of stealth, lots of positive reviews. We had raised some significant capital back in February, and then everything was looking great. Customers were excited, and two weeks later, the Silicon Valley Bank crisis hits.
As a startup, you never know what’s going to hit you from what angle. I think the notion of adaptability, if you can master it, that becomes your single biggest strength against big guys, which is the speed with which you can adapt and move. I think that probably is something I’ve definitely appreciated in the last year. The second would be individuals and teams are capable of fundamentally incredible things when they’re truly bought in and aligned. I think if you can get to that point, you can just do amazing things.
Soma: I think two great pools of wisdom there, Abhay. For my final question, how do you personally use generative AI to enhance your productivity on a daily basis? Are there any specific tools or techniques that you find particularly useful in your day-to-day work?
Abhay: Yeah. You said productivity in work, but I’m going to broaden that a little bit to you in my hobbies. I would say I don’t spend as much time these days, but I love landscape photography. The photography workflow is just undergoing significant change powered by AI tools, and I’m loving that because it makes me a lot more productive in a limited amount of time. I would say that’s one area. By the way, Adobe tools and teams are doing amazing work.
I’m a longtime user, so that’s exciting. Part of my daily workflow is getting AI enriched if you will. Maybe one thing I’ll say, I have a 17-year-old son who’s a junior, about to go to college. One of the things we are spending a lot of time on various research and college applications and all that. What I’m finding is it used to be Google Search and YouTube were the two places you would go. I’m increasingly so much starting in these Q&A research type of tools like ChatGPT and Perplexity.
That’s actually starting to occupy more and more of my starting point of my workflow of information assimilation, knowledge, and understanding. I just think that’s early days, but it’s very exciting because you start with a very different frame when you start with those tools.
Soma: I should tell you recently, I was going to give a speech in some context kind of thing, and I was really tired, and I said like, “Hey, let me maybe get AI to help me.”
I wrote a couple of sentences about what the intent was. I was blown away by the caliber of output that I got back.
Abhay: I hope you use Typeface to do that. If not, it’ll get you even further.
Soma: Absolutely. But it is just amazing to see what is possible with generative AI. Yeah. Then I think just sharing about what people are doing day in and day out, I think it’s fascinating, and I think there is so much more to learn and experience for all of us.
Abhay, I do want to say a big thank you again, both for us being a part of your Typeface journey and, more importantly, for the last 45 minutes or so here, having this conversation with us as part of our Founded and Funded podcast series. Thank you so much.
Abhay: Thanks so much. It was great to be here.
Coral: Thank you for listening to this week’s episode of Founded and Funded. If you’re interested in learning more about Typeface, please visit Typeface.ai. Thank you again for listening, and tune in a couple of weeks for our next episode of Founded and Funded, where we’ll bring in new VP of Google Cloud James Phillips – and former head of Power BI at Microsoft – and former CEO of Tableau Mark Nelson. These two former competitors talk about product-led growth, data & analytics, and scaling in the face of stiff competition.