[Editor’s Note: On this week’s GeekWire Podcast, we’re featuring an episode of Shift AI, a podcast hosted by Boaz Ashkenazy, CEO of AI solutions provider Simply Augmented, with guest Matt McIlwain of Seattle-based venture capital firm Madrona Venture Group.]
A thriving tech hub requires access to ideas, people, and experiments that produce collective lessons sooner and with greater fidelity than anywhere else. This is what made the Seattle area the cloud capital of the world. It also positions the region as one of the world’s top centers of excellence for artificial intelligence.
That’s one of the insights from Matt McIlwain, managing director at Madrona Venture Group, on this episode of Shift AI, a show that explores what it takes to thrive and adapt to the changing workplace in the digital age of remote work and AI. We discuss Matt’s background and experience building companies and advising founders, and get his take on the future of AI.
Listen below, and continue reading for highlights from his comments, edited for context and clarity. Subscribe to Shift AI and hear more episodes at ShiftAIPodcast.com.
First paying job: I grew up in Miami, Florida, went to a big public high school, and worked as a front-end service personnel-man at Publix, the grocery store. And another name for that is bag boy. But they call it front-end service personnel because we were there to be customer service for our guests. That was my first job, when I was 16 years old.
Family and upbringing: My parents actually met in the military. My mom never went to college; my dad was the first in his family to go to college. And they met in the U.S. Army at Fort Knox. My dad had a business undergraduate degree, and he ended up in the technology world quite a bit, early modem companies and things like that. It was something that was in me, I guess genetically somewhere. I did have a fascination for entrepreneurship and innovation.
Seattle’s rise as a tech hub: I moved here in 2000. If it hadn’t been for a debt financing that Amazon raised as a relatively new public company that year, they may not still be around.
Microsoft was on top of the world then, but did go through some challenging times. If you look at just the past 10 years of Microsoft, since it’s almost the 10-year anniversary for Satya Nadella as CEO, their market capitalization has grown from $250 billion to $2.5 trillion.
This economic opportunity and value creation and therefore capital, people, and talent that can be reinforced into creating a flywheel in the Seattle innovation ecosystem is super exciting.
Madrona’s approach: Madrona’s strategy is to be really early stage. It cannot be too early for us. I actually prefer being involved in the company formation stage.
Then, over the last seven or eight years, we started a whole separate fund that is for more Series B and Series C rounds that will be new investments for Madrona.
As a venture team, we’re trying to get to know founders and develop what we call “prepared mind thinking,” thematic investing before the rest of the world has figured out that something is going to be one of the next big waves.
The path to AI: If you go way back to the consumer internet in the mid-90s, with Amazon and others, then turning into software as a service, then you got to the later part of the 2000s, and we were thinking a lot and doing a lot of interesting things in virtualization. We did an event in 2007 with the Amazon folks to launch AWS up on Capitol Hill in Seattle. And lo and behold, the last big piece, about a decade ago, we were making our first investments in applied AI, back in 2012 and 2013. That time seemed to be the first big turning point in applied AI.
The state of AI today: What’s different now, with some of these transformer models, large language models, and foundation models, is two-fold.
- One, we can interact with that predictive capability through natural language. We can just write or speak, and ask it to do something for us, versus it being embedded within the recommendation that Netflix gives us, for example.
- And secondly, those systems are appearing to and actually are generating things. So they’re not just giving the recommendations, predictive systems, but they’re actually generating something new.
Understanding the AI hype cycle: This is a recurring challenge for the venture world — not just the investors like ourselves, but the founders. My college soccer coach, when we would run a drill poorly, in his Scottish accent would say, “OK, lads, would you do the same thing, only different?” And what he meant by that was, do it better.
There was grid computing in the 90s. It didn’t work. But cloud computing clearly worked. AWS has a $100 billion business today. And so trying to understand why the same thing, only different, is going to work now — part of that is because it’s actually not the same thing. You learn things, you do things differently. But timing really turns out to matter.
In the case of AI, I think we’re benefiting from, once again, something that feels like an overnight success, but it’s actually decades in the making.
The coming wave of ‘personalized agents’: Generative AI and applied AI will be the major technological driving force of the next decade. I think the modern data stack is a big contributor. And I think one of the manifestations of all that, and it’s starting to get more conversation, is this notion of personalized agents.
Right now, we’re thinking about large language models as these monoliths. Soon, we’re going to be hearing more about domain-specific models. I don’t think we’re too long from having these customized personal agents that are not only relevant in our individual lives – I want a buyer’s agent that helps me plan my travel better, or buy a car better, or whatever that might be – but also in our business lives.
And I think you’re seeing lots of experimentation coming right now, it’s too early to know what’s going to emerge. But I think that it’s not just going to be the model side, but it’s going to be the agent side, and the agents often at the edge, on our phones, on our devices, that will become much more pervasive in the years ahead.
Listen to the full episode of Shift AI with Matt McIlwain here.
