sure, Absolutely. So Aziz. Probably aware. I've spent most of the first phase of my career a data scientist, first as an individual contributor. Eventually the manager, uh, most recently as a executive and then in the last several months have started doing the best thing on the side as well. Um, that is a pretty unusual trajectory. I got here through a pretty weird path. I was originally a nuclear physicist by academic training. Way back in the day, um, and I got to nuclear physics, mostly because I was studying to be a physicist, and I realized I had the neck for computer program, and I really liked kind of sitting at this intersection of physical on numerical simulation, intersecting computer programming, available products. Um, after I left academia, I realized that that basically what the industry calls data signs on bond and I kind of came in industry before data signs was the term. But what we have now come to call data science, actually, what I was focused on, um, so I got my start in industry in uber was very early on in the process, I was basically hired as a software engineer who was responsible for Building Network, which was two mathematically and sort of numerically complex for your typical Python developer. And I really like that in that gave me an opportunity to do a lot of data sign and was a lot of data work, but was always kind of grounded in a product that people could like use every day. But there was sort of, I mean, feedback loop. Um, over time realized that I was shipping a lot of the early features of the uber experience. I felt the very first versions of dynamic pricing research price being uber and that you kind of became a cornerstone of uber's ability to optimize the marketplace became sort of critical of the business. That strategy and I ended up working on the exclusively for several years. Um, you know, after a couple of years, I was basically managing a team. Uber at the time, was pretty flat, you know, sort of not formally hierarchy. But I realized I really loved managing that one of the fundamentally true things about my career. Instead, I like to coach and I like to mentor, and I just sort of grow people. I felt sort of called the People Management. When I was in academia, I felt sort of called the Teaching was sort of one career about everything about in the industry. The involved was was management on DSO. Spend a lot of time building out data signs as a function with a number. Spent a lot of times sort of building organizations, you hiring out like the 1st 50 people and bringing in like a more seasoned executive because I was still fairly early on in my career of that point, Um, and then you executive just sort of followed from that. I've always I've realized that I've sort of this knack for early stage data at the early stage companies, So it's been kind of a repeat trajectory of kind of higher. The 1st 50 people you know, uber. And then I went to tall. I did something very similar, Uh, and that sort of continued that path. What

good question. So why didn't cover in? My story is kind of on nights and weekends. I've been doing an angel investor. Um, working as an angel investor in the last year or so have transitioned much more of a full time investor, Um, in the areas. So why I say that is the areas I tend to invest in and the stages I tend to invest in our the stages that I always felt like I have a lot of experience in as an operator. One the value proposition is much more directly is much more clear. The founders that my experience is very directly a but the wrestling with what they're working on. Um, but also I feel like just my expertise will give me an unfair advantage to recognize really great opportunities that maybe the rest of doesn't see eso with the maps to members of answering the question directly, I'm looking for a i companies and ML companies at the earliest stage. You know, the really rough strike zone for what a I company is is You know, if the data side just quit the company folds is kind of the rial. What I tend to look for it. Um, industry domain. I don't have a narrow aperture. I consider most most industries. Um, I fundamentally believe that ai as a domain has always been theoretically applicable to farm or than just enterprise sas or, you know, or sort of consumer mobile app. Uh uh. And but I think that a lot of work in the last several years on the both in terms of the state of the art of a I research as well as data infrastructure and data platforms have been turning theory into reality that, you know, some of the best investments I've made our AI for fish farms or a I for, you know, uh, convenient story. So, uh, any industry really intrigues me, but always at the earliest agent, I'm looking for founders who really benefit from somebody was sort of bottoms up operational experience, Um, in opportunities that I feel like I'm the first to really see in the formal investing industry.

um, I think that that one of the most common mistakes founders tend to make eyes. They probably over estimate the degree of sophistication, at least in my domain and ai them up. They overestimate How much is it necessary to start reaching out to investors? So the theme I've seen with a lot of B. C s that I subscribed to, there's no such thing as too early. I'm often talking to people while they're at their last job or where they've got kind of half of a business. Um, so I would say an incomplete sort of structure makes sense. Probably speaking, you know what I'm coming to look for? Um, in the first email is sort of a little bit about the founder, and usually some of it is sort of your career path. But what I'm really trying to figure out is it's sort of why this company, why this problem and why do you feel like you have conviction that you're the right person to solve this problem? And so you kind of want to see a little bit of like, Hey, I'm working on a company in the space I'd love to understand, like the sort of domain or problem you're chasing and then a little bit about you just sort of, you know, really? For example, like, I'm really interested in optimizing the transportation and logistics layer of, you know, trucking in the Midwest. You know, I grew up in a family of truckers, just graduated with a PhD in computer science, Uh, and feel like, you know, I'm seeing whatever the opportunity you feel like you're seeing is like, Would you like to talk with me about it is like a perfectly wonderful first thing.