Your Next Move - How to Lead on the Front Lines of the AI Boom

Episode Date: July 1, 2025

In this episode, Inc. editor-in-chief Mike Hofman chats with Isa Watson, the founder and CEO of Squad, and Jacqueline Samira, the founder and CEO of Howdy.com. They discuss how they're running their tech companies in the age of AI. Then Emmanuel Offiong, Capital One  VP and CTO of Business Bank Engineering, talks about how companies can use data to drive revenue growth. Offiong offers tips and reminders, like how companies need to regularly evaluate the quality of data they're using and ensure that their data ecosystems are well governed. And finally, Inc. recognition program manager Sarah Lynch explains the benefits of embracing the AI revolution by describing some successful use cases like Neptune Flood, Salesforce Einstein, and Tableau AI.

Hi, I'm Mike Hoffman, Editor-in-Chief of Inc. and welcome to your next move, produced by Inc. and Capital One Business. As we all know, tech is evolving faster than ever, and so are the ways we optimize our work. Today, we're joined by two incredible founders who took unconventional paths into tech. Jacqueline Samira is the founder and CEO of Howdy.com,

and Isa Watson is the founder and CEO of Squad. Isa, Jacqueline, welcome. Thank you. Great to be here. Yeah, thank you. Excited. So, Jacqueline, let's start with you. First of all, why don't you tell us what Howdy.com is? So Howdy.com is a platform for US tech companies to build their software development teams in South America.

We have offices all across Latin America, so everything you can think of from recruiting, vetting, HR, benefits, payroll, we are your outsourced logistics hub to build your team, build your office in Latin America. Issa, why don't you tell us what Squad is? Squad is a fan engagement and data analytics platform that's licensed to professional sports teams. Who are some of your customers, can you say?

Some teams in the NBA and WNBA to start. Very cool, and for howdy.com, is your typical customer a smaller mid-sized business or an enterprise? Most of our customers are tech companies. I'd say in the growth stage company or the later growth stage companies, it's people that have a team in San Francisco or New York and they're looking to build their second office

or their third office somewhere in the same time zone. So small enough to be able to manage that, but then also big enough to have multiple offices. And what markets in Latam are you active in? We are in many markets. So we are in Brazil, Argentina, Chile, Peru, Colombia, Mexico, and Santiago, Chile. So you're scaling your company, you're scaling your company too, and also helping other companies scale.

And I'm sort of curious about tech talent in this moment. What are the skills that people need to be successful, and what skills do founders need to bring into their organizations to grow their technology? So for us, one of the things that we're looking at is the way that we're thinking about this is to be a tech company is actually a little outdated now. Now you need to be an intelligence company. So what does that mean? Well first it starts with how you vet your technical talent. How are they thinking about coding? How are they thinking about doing documentation? If they're coding the way that they did six to 12 months ago,

then it's already outdated. What are the AI tools that they're using? How are they thinking about adopting and adapting in this new era? And that's really what we're looking for when we're vetting talent these days, versus than how we used to do it even just a year ago. Does that resonate with you? It does resonate with me. And also, tech is moving so fast and the deployment of new code

is moving faster now than it did 10 years ago. And so the ability to be scrappy in the way that you build a code and making sure you're not building up too much technical debt, 20 years ago, 10 years ago even, it was very common to build, build, OK, there's that debt. Build, build, there's that debt. And then you're like, wow, there's all that technical debt. But now, that creates a lot of issues, right?

And so the scrappiness, the ability to actually have very strong documentation, I think, is more important now than before. A lot of engineers like to skimp on the documentation, but it's incredibly important with how fast things are moving. And so then how do you develop those skill sets with the developers you have? So one of the things that's been really interesting for us, like you were saying, tech is scrappy,

but documentation is even more important now than ever before. And that's something we're seeing too, like the foundational principles, the basics of computer engineering, is more important now than ever before. So we're really looking into their background, their education, how they learned in a way so that we can supplement what they don't know.

Because of course, like today, we can hire anyone. Anyone can have any kind of education because it's so readily available. But where are the gaps and what are they missing? And so some of the things that we're doing is filling those in, whether it's, hey, how do we use these AI tools or let's give you the foundational principles of computer science. For me, it's really important to incorporate mentorship into some of the lives of these engineers right from a career development perspective, because engineers, when you think about it, they're not necessarily the first to say, hey, I need a mentor, or I need to

go find this person. And so I've been very intentional in making sure that I can provide our engineering team with the right mentors so that they can actually continue to iterate on their skillset, even beyond just the leadership that exists in the technology. For example, some of the earliest engineers at Snap have been very strong mentors of our engineering team. And that's been really, really helpful and game changing

in a way, right? To have people who were like the first 10 engineers at Snap who have still been iterating on their own skillset. You talked about the importance of documentation, you sort of talked about the importance of being mindful of tech debt. You also talked about the importance of being nimble and scrappy. So what does that look like in practice? How do you sort of interview someone for a job who you think would be set up to be successful,

and then how do you manage them? What do your mentors say to young developers to make sure that they're very attuned to these issues? I think part of it is the incorporation of certain processes, right? So every so often, right, for us is every few weeks or so, we're looking at the tech deck. We're sitting down and we're saying, hey, what are the things that we actually need to offload?

Is the documentation up to date? We are a platform that exists as an SDK slash API. And so our documentation doesn't necessarily have to be just great for us. It's also because it makes our customers that much more successful. And so we, you know, compared to a few years ago, we have check-ins where we are going over the documentation with a series of frequency. But I think that sometimes when you're growing super fast,

people don't like those processes because you're like, oh, that slows us down. And that feels like bureaucracy. I just wanna go ahead and get this done. But being very diligent and making sure that they adhere to the processes that we put in place to keep the code exceptional and to keep the code functioning well. I love that you said engineering mentors because that's actually something we do as well.

So we have a team of engineering mentors, not even managers, that their whole job is to mentor developers. So the fact that you said that just like warms my heart. One of the things that we realized is once people hit a technical bar, where there are mishaps is actually not technical, it's actually communication. And so a lot of our coaching and mentorship is how to have the courage to speak up and to say like, hey, something's wrong here, or you know what, we're not going to hit the deadline. A lot of times when people get in that flow state or they're working,

they don't want to let anyone down. So they would rather be quiet about something, maybe missing a deadline or about cutting corners than speaking up. And so so much of what we've learned over the years is how to give people the tools to be able to communicate properly, to alert us in advance so it doesn't fall down. And so that's been like really eye-opening. So when you go into a client or a client company and you sort of take a look around and something's not quite matching up in terms of what the engineering team is delivering

and the technology team is delivering and what management or other functions in the business are looking for, what typically is the cause of that delta or what are some of the causes? I would like to piggyback off what Jacqueline mentioned in the importance of communication. Because I find that it's more rare that it's actually something with the code base, right? There are things that pop up and you're like, oh, we have deploy fix for that very quickly. And those things happen, right? But it's more around the communication.

It's more around the engineers being siloed and not necessarily communicating with the business folks properly and vice versa. And so making sure we build not just the right processes within the engineering team, but for them to actually be able to communicate with the sales and marketing people from within our company. And also with our customers is really important because it generally boils down to the mismanagement of expectations. And we could actually proactively solve for that. And it's generally not an issue that's so big. It's just, oh, I thought you said the deadline

on that was this, but now it's something different. Oh, I talked to Bobby over there and Bobby said it was fine, but Bobby didn't communicate that over here. And so just having to manage that is more of a process thing than it is a technical thing. I'm curious, as founders and leaders yourselves, do you see other founders and leaders at client companies exhibit characteristics that you're like, oh, if you just tweaked it this way, or if you just reset your expectations this way, you would be happier and your team would

be more functional? Yeah, completely. I mean, I think, you know, going on what you're saying with mismatched expectations, when you think about the foundational principles of software engineering, you think of functional design, system design, and then you actually start coding, and then you actually start like putting things together. And if you're not, as the CEO or founder, deeply invested in the functional design and the system design, and, you know, we, every week we're doing wags and we're sitting there saying, okay, how long are we anticipating this to take?

And if the requirement was something that seemed pretty simple, I'm not a technical founder, but I know when something's simple or complicated, and they're sitting there saying, oh no, it's going to take two weeks. It's like there's something that happened here. There's a misunderstanding of the problem that we're trying to solve. And so digging in deeper and trying to understand

the misunderstanding of what was communicated. And we see that all the time with the customers that we work with. If you're not just in the weeds, I think there is this misconception as a founder or CEO that as your company gets bigger, you have people on your team to do that, and you have people on your team to manage that. But actually, like, I don't care how big your company is, if you're not in the details, things are going gonna fall down and it's actually worse for your business.

And the role of product managers or directors of product, we're supposed to fill some of this. There's been in some cases a move away from having product function. I'm sort of curious, what do you see in the world of product management right now?

I mean, for us, I think they are more important now than ever before. With AI as a tool, it's going to allow us to create more. And humanity, we're not the type of people when we have the ability to create more to be like, you know what, we're good, we're just going to chill for a little bit. So people are creating more and we need product managers to make sure that we're all staying aligned on what it is that we're producing, why we're producing. And we know there's the technical product manager and the non-technical product manager.

And at the end of the day, the best product managers, whether they're technical or not technical, have the best communication across teams, across the people that are requesting the features or requesting the various supplements to the product. And those that can really define what is being done, get everyone on board, get everybody agree. That's when you build really efficient, effective, clean code. We've talked about the speed at which technology is evolving.

Mm-hm. And we've also talked about the importance of communication within engineering a product, but even to other functions. And the product manager is generally the one that keeps a lot of that all together. And so when things are moving even faster, functions, and the product manager is generally the one that keeps a lot of that all together. And so when things are moving even faster, you know, you wouldn't be like, oh, shoot, I'm driving faster. Let me take my seatbelt off. No, no, no, no, no. Now you need your

seatbelt more, right? And so product management, it's moving faster. In fact, I think that what I've seen is an upscaling of product managers on average over the last five years because of the advancements in AI. Some of the people who got product manager roles five years ago may not necessarily get those same roles of interviewing today because the standard is higher, because the role is that much more critical to the business. That's interesting about product managers having sort of different standards today. What have you seen in terms of new standards?

What are new requirements or skills for being successful? There is a deeper technical expertise that's required. That doesn't necessarily mean you need a CS degree, but you have to have fluency and understanding a lot of tools, especially with the emergence and growth of AI and how they can actually integrate or impact the product that you're building and the product that you're scaling.

And the product that you're building and the product that you're scaling. And the product that you scale with and the tech stack that you scale with, is that the same tech stack that we need for the future, right? There's a lot of technical fluency and understanding that goes into that. And the other thing is just strategic thinking. With things moving as fast as they are, product is an alignment role, right? And so there is, you know, I kind of call product managers my visionaries, you know, my alignment visionaries, right? But, you know, Jaclyn and I have talked about the fact that

technology is evolving at speeds that we have not seen it evolve. I went to elementary school with the big Macs that had the big orange backs. Kids these days would never understand that we had to connect to a wire to get the internet and it kicked the person off the phone. Yeah. Right? So when you think about the speed at which things are moving, there's a level of being able to distill

a bunch of information into tractable components to make it digestible to both engineers and the business people. There's just so much more information. So there's a level of strategic thinking that I also think is really, really important. So are you AI? We've talked about AI a little bit. Let's dive in. Are you AI optimists or pessimists or somewhere in between? I'm an AI optimist. I mean, there was a moment in time where I was like, oh no, like what's gonna happen to the whole world? But then I just looked at history.

And when we see all of the evolutions that's ever happened, it's only created more opportunities. You know, when the printing press came about, everyone's like, oh my gosh, those scribes are gonna be all out of business. It's like, yeah, they're gonna be out of business, but if they change their skills, they can have a different job

and there's actually gonna be more jobs. And there's gonna be more opportunities for authors, you know, and as you move forward and you think of everything that's happening, same thing with like the advent of Microsoft Excel. People were freaking out, accountants are going to lose their job, but it turns out, like you just need a different type of accountant now. The accountants that had really good handwriting and could do math very quickly in their head, maybe it wasn't as important, but it allowed them to upscale, take on more accounts, and

be more of a strategic accountant. And now we're in an accounting shortage, you know, 40 years later. So I look at history to guide the future, and I think it's just going to be more of the same. AI is an incredibly powerful tool. And even when AGI becomes real, I think it's going to be a lot more narrow than what we think it's going to be. And it's than what we think it's going to be. And it's still going to be a human powered tool.

And it's going to give more opportunities for more people all over the world. And I think it's going to be a great leveler. And I'm really excited to see what comes from that. So through my journey of discovery of what this could be, I've come out the other side an optimist. I would say that I'm AI neutral for a few reasons. There are elements of AI where I am optimistic and the capabilities that it unlocks, right?

But the reality also is that I do think from a macro perspective, it is going to create a very hard job market. Going from paper accounting to accounting and Excel is not a huge gap than going from in Excel to something much more powerful technologically speaking. The other thing too is that, you know, CS used to be and has historically been such a great field of study. I come from a family of engineers. My dad was a computer engineer. And now there's this emerging view of,

we don't need CS to know how to code. We have AI to code for us. And so my concern from a macro perspective is, what is it going to do to our talent, right? If they don't necessarily understand or value understanding the fundamentals of the engineering problems that we're solving. And yes, it is human powered, but it's human powered by a handful of individuals. And that to me is a little bit different. However, you know, with SQUAD, one of the things that we're doing, I'm an MIT grad, we have an AI data partnership

with a professor at MIT that actually allows us to help sports teams and leagues unlock revenue at the fan level, revenue opportunities at the fan level based on the different things they're talking about, their sentiments, et cetera. And I think that's just one minor application of what AI can do, how it can help businesses make more money, how it can drive much more valuable data insights. But I think net and net, I'm neutral because I think that there are some benefits, but I think that there are some drawbacks. And right now what we're doing is we're moving much faster than we are processing things on a human level. It's why, you know, the average 16 year old is scrolling on TikTok nonstop all day without any

intentionality of thinking, is this good for me? Is this what I want my mind to consume? Because it's just a habit we develop so fast. Have coders on your team used AI to write code that's gone into your stack? Not that I know of, but I'll ask my CTO when I get back. So you work on talent and resourcing. Have you gotten, I assume, more AI inquiries? Can you even remember the first AI-centric requests for a prompt engineer or prompt engineer team, that kind of thing? Ninety-five percent of our team that we build for

other teams is technical talent, so software engineering. I wouldn't say that it's been a night and day difference. that we build for other teams is technical talent, so software engineering. I wouldn't say that it's been a night and day difference. Before it was AI, it was ML. You know, before. So it's not necessarily, in our world, a huge graduation. It's just a slight shift of what they're requesting. I would say like the big aha moment will be

when they ask for a prompt engineer without any kind of coding experience. And to your point about if coding becomes obsolete and all of these jobs are potentially going to disappear. I believe it's similar though in the sense of like math is still foundational. English is still foundational. If we have AI write stories, you can read it and tell it came from a computer. If we have AI do, you still need to know the math behind it.

You still need to know the computer science behind it. So I think it's gonna be more important than ever to continue to develop those foundational skills and understanding. But then everybody can be more like a mini CTO, organizing and understanding. And so if we live in this world where coding becomes obsolete because, of course, the computers can do it, well, we still need to validate that it's accurate. And you can only validate that it's accurate by knowing the foundation.

So I don't think it's going to be as night and day in that sense either. But we'll see. We'll see what happens. Do you see within your engineering teams, what kind of skills are they asking for? What kind of training are they looking for? Within the teams, like when people are making requests for the teams? No, no, like with your employees.

Like what are they like curious about? Where do they see their own skills gaps if they have them? You know, I think there's, we have two camps right now. There are the people that wanna know how to use AI tooling. I think for us, software engineers in general tend to have more of a curious beginner's mindset anyways. They're always hacking, they're always, so like the tooling, they're self-learning. A lot of folks are self-learning.

So we don't see as much request for that. But on the other side, it's like, okay, well actually, how do we build an inference pipeline? How do we build the things, how do we build our own large language model? How do we build our own large language model? How do we build our own real AI tool? And so we're getting more requests for that than the prompting, the tooling. Because I think naturally,

that segment of the business tends to be more curious. They tend to be more early adopters of these types of tools anyways, and they're more self-taught. I agree. For us, there's a huge data infrastructure that we had to build in order to layer on the AI applications. And there was a lot of, hey, is this the right approach? Do I have the right information to make the right decision here?

And quite frankly, being in New York is very great because there's a myriad of conferences and meets with so many different experts coming in. So I think the question is at the high level, do I have all the information I need or maybe I don't have all the information that I need to actually make the best decision here and how do I get it? But then it's, what is the approach here? Let's try this approach,

but then let's compare it to this approach. What are the pros and cons? Okay, we've decided to implement this approach. And so it's a level of curiosity really anchored in the fact that we're trying to build something new and something that feels more future oriented than it does reliant on the past. I imagine that there's like a attracting talent play to that too,

of like come here and help us build the future. When it comes to recruiting talent, where are those conversations like right now? It's interesting because we are a sports technology and we work with professional sports teams a lot and professional sports leagues, and it's not very uncommon for the team to interface with their favorite GM and things like that. So I think that I have a team that's really excited about

innovation in sports. And sports is a great product, it's an entertainment product, right? And data-rich. And data-rich product. But where sports has a big opportunity to level up is in the technology, right? And so I think that just the nature of our business extends itself to get people really excited about what we're doing. And then when you peel back the layer of the onion and they're like, wow, and we can do this and build this and come up with these innovative ideas. I'm not a computer engineering technical founder. I am a chemist by training and then I was trained as a product manager.

But I had been building my computer since I was seven, so technically fluent. As founders, there's a lot of curiosity among founders about AI and how to use it within your company to optimize processes, non-technical processes, how to use it personally. So what are some ways that you use AI personally, whether it's to make decks or whether it's to send collection letters to clients or all the above, what are some ways that you've been using it? Oh man, so we've done some really fun things with AI. We have one guy who tends to have all the information

about all of the various components of the company. And so we actually built an AI bot that just duplicated his information. So instead of like just bugging him with questions all the time, now everybody has the ability to use this AI bot with all the information, which has been really fun. And we're all-

And how accurate is it? It's totally accurate, because it was built with all the information that he injected. And then if it seems a little outdated, we'll get clarification. But for the most part, it's actually working really well. And we also are implementing ways to think, how do we create something

within our organization that creates more objectivity than subjectivity? When you think of annual reviews, it actually tends to be really hyper-focused on the last three months. So if you're looking at a full year, we don't have the best ability to like zoom out and have equal footage from January all the way to December. And so we're thinking, okay, how can we draw on all this information over the course of the year to have an objective review of a person so we can give real feedback that's not time sensitive to, you know, the recency bias.

And so that's one of the things that we're working on in building this little AI program to help have more objective reviews so people feel better and they feel like they have like a really clean picture of where they're at within the organization. And then of course we have a couple of AI processes. We match people with companies. We work with tech companies all over the United States and we're showing them profiles.

So how do we create profiles and opportunities and bring them together in a way that is automated and more of a delightful experience on both sides? I love that tip about performance management because it shows people that you care about like what they've done throughout the year, right? Yeah, at the end of the day, we work with technology companies and AI companies,

but we consider ourselves a people company. What about you? How are you using AI? It's been really impactful in helping us manage and implement processes. I think that it can be very easy for things to get out of control or to feel a bit chaotic, especially when you're growing very rapidly. But from note-taking, AI note-taking to make sure that everyone has

central repository to all the information, the engineers can see what the customers are saying, what they're requesting, why, okay, now we know that this request is coming up across multiple customers now, and we thought it was a weird request, but then we're like, oh, wow, five people sent that. And so that's actually allowed for information to be used in a really strong contextual way across the company. There's also, you know, you talked about recency bias in reviews. There's also a tool that we use around calendaring reminders about certain things. And if there's a process that we agree as a leadership team

that we need to implement across certain areas or all areas of the company, we can actually apply that and make sure that people are achieving those processes. And then with our customers who are, you know, NBA teams, WNBA teams, you know, and growing into other major leagues as well. When it comes to what's going on with the teams and what's going on with the leagues, there's AI tools that we use to actually kind of understand what do we think is going to

happen toward the end of the season and how is that going to impact how we're building or engaging with set customers, right? There's a lot of AI tools on the predictive analytics around how a season might end, who may win the playoffs, who may win the championship, and that, or who may actually be out super early, right? It's not just, you know, this is a team that I go for. We actually really want to be objective

without our own personal biases, of which we have a lot on our team, with how the season is going to unravel because that impacts our strategies and engagement with the teams. Who within your organization is sort of the in charge of AI or in charge of the thinking about AI strategy? I mean, I feel like we're all thinking about it. We don't necessarily have one person who's head of AI at our company, but it is at the forefront of all of our conversations. Knowing we're in this new era, how do we become an intelligence company?

So that's the question we always ask ourselves when we're meeting. We organize our company for the year, then we break it down into quarters, and then we review our metrics weekly. And on that weekly call, we're constantly asking, are we getting closer to our goal or getting farther away from our goal? And one of our goals is to turn ourselves from a tech company to an AI company. And so it does get discussed weekly with the leadership team. I agree that it's not just on one person. But as a trained chemist, I have the view that I don't have the right answer. This person doesn't have the full right answer.

Neither does that person. But it's usually the right answer is usually a combination of perspectives that get to the most exceptional answer. And so while we discuss it at the leadership team, we've created this culture where people can raise ideas anytime they want, right? And those ideas are received

because I'm not going to necessarily come across all of the valuable AI tools and applications in my purview, but there could be something really interesting that this person sees. And so, we discuss it here and we're constantly talking and iterating on the ideas. But, you know, we've created this culture

where people feel free and are excited to recommend things that they think will be helpful, understanding given the direction of the company. Can we talk about money for a second? Yeah. Yeah, so I think money is one of those things that you both run tech companies. For people who run non-tech companies,

technology can sometimes be a cause for sticker shock. I'm surprised at how much it costs to hire up and staff up my tech team. I'm surprised at the amount of money that I have to spend on this software product or on this project. I'm curious, first of all, in terms of investments, what are some big bets you're making within your companies now in terms of where you're putting your money? So for us, a huge investment that we're making

is in AI education. And so we've developed a whole curriculum. And like I was talking about earlier, there's two paths, AI tooling and then actually learning how to build AI yourself. So we've built several modules around this that we're giving to our developers for free because 95% of our team, the software engineers, because we want to make sure that we're giving to our developers for free, because 95% of our team is software engineers,

because we want to make sure that we're filling in all the gaps with their knowledge so that they can be not only up-skilled, but be five times more effective, five times more productive than anyone else on the teams that they're working for, and to really feel like, hey, I'm making a monumental difference within this organization. And that's been really, really fun for us to see the level of people that are signing up and doing it and completing the courses.

We just finished the quarter and we did a raffle like for the person who completed the most courses would get a free trip to San Francisco. And it was like the last week of the quarter, everyone was like jamming through them. And how many courses did the person have who won? We haven't, I can't announce it yet. Okay, all right. Just kidding. Yeah, it's in stealth.

Yeah, it's in stealth. But it's been really fun to see the adoption and the excitement. It's like for our team, like they've been given a new candy, like our new treats. It's a huge investment we're making. We're thinking about how are we going to evolve this even further? How can we open this up to non-technical people and non-technical rules? Then how can we make this information available to everyone? We have a database of all the AI tools that exist,

and what they all do and what they all mean. We have hundreds and hundreds of companies that we have engineers working on. We get an incredible amount of data. Who becomes more effective? Who's more efficient? What tool works better? Why? And so we're compiling all this information and we're thinking, how can we just give this away so it can help others as well? We don't have the answer for that yet, but.

I love the AI education. I might steal that from you. But one of the things that we've been investing in heavily is on the AI and the predictive tools that unlock additional value for our customers. So our customers as professional sports teams in leagues, a few things that are big pain points for them, one is first party data. Mm, interesting. So when you think, on average, you take any NBA team,

99% of their fans will actually never see the inside of an arena during that season. And then when they are following the team, they're following them on third-party tools like Instagram and other places where they're not able to say, oh, this is Jaclyn, who's a fan of XYZ team, and this is what she's doing with the team, right? And so as sports moves more direct to consumer, they have to do a better job of owning and curating their own first party data. And so Squad actually helps them a lot with that.

And the other part is unlocking revenue opportunities digitally that aren't just in the arena and through some of those traditional models, including media, because the reality is that if 99% of your fans are never going to see the inside of an arena, you're actually skimping on monetizing a great deal of your fans, right? And so a lot of the investments that we've been making are in building the tools and the capabilities,

especially leveraging AI, that can deliver the value to them of dramatically increasing first-party data and dramatically increasing digital revenue, because it adds more value to them than it adds more value to us. And so there's that kind of positive feedback loop. And so that's where we've been making advancements. But I am going to get our AI education module because maybe it'll make us move faster. Of course, by all means.

Well, so then what's the converse? What are areas in technology that you're investing less in than you were maybe five years ago? What we've realized is because there's just so much noise out there now, and like you said, kids on TikTok six hours a day, it's just like zombie mode. How do we break through? How do we break through that noise and actually meet and

connect with people where they are? And so we're trying to move away from the traditional means of getting in front of people and actually going like old school, doing traditional things. How much more can we be in person? How can we meet people in reality and make them see us for who we are so that they're not in that like zombie mode because now you don't really understand or ingest anything in that way. So I would say that that was a huge expenditure that we're not spending,

but we're taking those funds and we're moving it more into in-person events. We have a big investment in an arena. There is a big venue in Austin that plays the UT basketball games. And so we're bringing people there a lot and just reconnecting on a real human level. I would say that we're probably investing less in the people component of service, right? So we are dealing with not just US-based teams, but keep in mind,

we are also scaling with teams and leagues in Europe and South America. These contracts have SLAs, and then where there's, hey, what's the response time if something goes down at 4 a.m. your time, right? But the reality is that there's so much of that, that we can actually service through AI. I mean, it started with kind of smart FAQs. It was like, hey, you know, these are the top 10 questions. If they're not in the top 10, you know, what's the next, you know, then you can call us,

right? And that was everyone's model. But, you know, there's this element of leveraging, you know, AI and tooling to be able to be effective and efficient in servicing customers without it reducing the quality of the service. And so when you're able to do that, I think that that shifts the cost a bit. It's more technology and making sure that technology is functioning well. And there are people still there, right? But you don't need as many people.

And so I think that with us being a business that is licensing a technology to entities around the world, there's an element of, how do we be more efficient and effective in servicing our customers and implementing technology in some of these tools is a big part of that. Are your companies remote or hybrid or how are they structured? We have a hybrid model. We have eight offices across the United States and South America, and it's mostly built in so that we can have a community.

We do lunches once a week, we do hackathons, we did actually an AI competition. I was talking a little bit earlier about how everybody on the team might have a great, brilliant AI idea. We had got something similar last year. I was like, let's do an AI competition. I was talking a little bit earlier about how everybody on the team might have a great brilliant AI idea. We had thought something similar last year. We were like, let's do an AI competition. Whoever has the best idea will win $10,000. So we like to do like a lot of fun things like that. And what I've found too, is people actually are like choosing to come in when it's not forced upon them. They're coming in more and more and more. And I think COVID was great because it showed the world, hey, we don't all have to be, you

know, butt in seat nine, 10 hours a day to still be effective at our job. And it swung the pendulum to this place where it was fully remote. But then we lost a sense of ourselves and we lost a sense of like what provided happiness. And it's starting to slowly come back and it's nice to see people naturally wanting to be together without having to be forced to be together. So that's how we work. I would say that we are actually more in office. You know, we have offices in New York City and North Carolina. And there is four days on and one day you can come in or not come in.

But I would say that the team actually really enjoys it. And things like sometimes things move so fast. It's like, oh my God, Mike, did you see that thing that happened? Da da da da da. And it's been, I would say that, and I know this is an unconventional view, one that get canceled on social media, but I would say that being in office has been really effective for us. And the team has just really appreciated it. And so we are in our offices four days a week

in New York and North Carolina. I will say, I said to your point, a lot of conversations I have with other CEOs, because we work with a lot of companies, is they want to be back in office and they don't feel like they have permission. Yeah. And so for me, a lot of times I'm like, actually a lot of CEOs are making that decision and people are happier. And the people that don't want to do it, they go find another opportunity. And so sometimes it's just like giving yourself permission to make that kind of policy and not feel like, oh my gosh, I'm going to be canceled because we have this way of working.

I agree with that. I had a dinner with several CEOs when a lot of this conversation was happening in the media and on social media, et cetera. And it was like, hey, we really want to be back in the office, but oh my God, are we going to get canceled online? And there's this view of like, is being in the office anti-family? Most people have been in the office for the entirety of the existence of America, with the exception of 2020 to probably 2022.

And so, yeah, it was a decision that we made, but we didn't have backlash. People really enjoyed it. Yeah. I would think, you know, I have a family, and I've actually thought it makes me more intentional when I'm home, because when you're working and the kids are there, you're always distracted.

So when they learn that you're always distracted and you learn it's okay to be distracted, it's not a good environment. So when you're gone and when you're back, it's like, no, I'm not working. I'm home. I have intention. I actually think it can be pro-family in a lot of ways. I'm curious. A lot has been read, a lot has been written, and a lot has been said about the experiences

of women in tech and as female founders in tech. Can you talk about your experiences? Have you found it to be difficult, or what are the areas in which it's been difficult? There's pros and cons of everything, right? I would say that it's unfortunate that people don't take you that seriously in the beginning. And my company was the same company it's always been from the beginning.

We didn't have any major pivots. We've always had the same purpose, mission, vision. And in 2021, we got into Y Combinator. And there was no difference between December of 2020 and January of 2021. But the fact that I got into Y Combinator, now all of a sudden everyone was like, oh, what is it that your company does? Oh, that's amazing.

Oh, let's have a conversation. Let's meet up for coffee. And it's like, why did I need that to like actually have you pay attention to what it is that we're doing? So there's been a lot of that. And even now, like we're getting a lot of traction. We're growing pretty quickly.

And we were always, in my mind, I think, like a big deal, but people are now starting to take it serious. And I think just my general experience is that we just have to be that much better, that much more successful before people even start to shine a light on you, which I actually think is a pro though, in hindsight, because it allowed me to just stay super tunnel visioned on what it is that we were doing, what we were building, how to be successful without

the flashing lights or without the distractions and without the magazine articles being published about you. You see your peers that are men that are doing less than you or less successful, or in all these different ways, get all of these accolades, get these like spotlights. But now, you know, six years later, they're, the company, you know, went under and they're working on something else. And so I think it's been a benefit in the end. It's the interesting thing about technology, right?

That it's like supposed to be independent minded, but of course credentials matter too. Yeah, totally. So I'm here. Well, I've worn the underdog shirt with pride the majority of my life. When Squad started, we have had a big pivot. It was horizontal social. So the idea was actually a platform that actually helped you talk to your actual friends every day off social media, since 90% of social media is actually just lurking, consuming other people's content and perfected highlight rules. But you know, the interesting question I got when I talked about Squad

in that era, it was, oh, you must be building a social tool for women or you must be building a social tool for black people. And it was never that we were just building a tool. And you know, the reason why we got into sports is because so many people were using our platform to talk about live sports games. And the reason why we got into sports is because so many people were using our platform to talk about live sports games. And it became such a natural engagement tool that then the leagues were like, hey, is there a way that we can work together and use this? And then we anchored our business in sports.

People sometimes I think too often focus on where they may be disadvantaged or where they may be handicapped. I like to joke sometimes that, you know, on certain days and in certain meetings, I'm going to identify as a white man and I will walk into that meeting just as confident, just as much with my chin up, just as much with my chest out as any other white man would do. And I am not handicapped. You know, I did go to MIT.

I have accomplished quite a bit. I was, you know, Inc. Top 100 female founders, right? I mean, all of these things. But to Jacqueline's point, we have to come into the room with way more than a lot of these guys and a lot of our counterparts have to come into the room with. And so it's my internal joke.

If I feel like a little bit of an imposter or I feel like, you know, people aren't taking me, you know, fine, it's okay. I identify as a white man today. And I am going to march as such. And nobody can tell me otherwise. And everything works out just fine. What have your experiences been with funding and how do you fund your companies? March as such and nobody can tell me otherwise. And everything works out just fine.

What have your experiences been with funding and how do you fund your companies? Yeah. So we were bootstrapped for the first few years. I was leading sales and operations teams at startups for a majority of my career. And when I started my company, it's like I'm going to get off that like hamster wheel. I don't want to be on the VC treadmill. I'm going to build a good, and you know, at that time too, there was this like dystopian world of like money didn't matter.

I was like, did we lose like the business principles of what a business is? It's to make money, right? And at the time it was like, oh, we have this many users. It will eventually convert to something, you know, raise more capital, raise more capital. And so I was like, I'm not going to do it. I'm going to build a good business, a solid business that makes money from day one or as much as possible. And so we did that.

And we grew to a point and we were at this place where it was very capital intensive. And the question was, should we take in outside capital? And my co-founder and I at the time were like, well, why don't we do this? Let's apply to Y Combinator and we'll let fate decide. If we get in, then we'll do that journey. And if we don't, we'll continue down this path. And because we were personally risked at the time. And so we got in and so we went down that path. But to the same point, no VC was talking to me prior to that. After I did Demo Day, I had 93 meetings booked. So it's, it's amazing what a little social proof can do.

Yeah, fundraising is actually one of the most painful things for me as a founder, because it takes you out of the business. And I love just the building and engaging with other customers and adding value. But the thing that adds a little bit more to it is that it's a very, Silicon Valley is a very insular environment. And I had probably 200 doors slammed in my face where anyone took me seriously. And then once we got the social proof of a few VCs

that people knew, then it was, wow, my round is 10x oversubscribed. I'm like, where were you guys before? You know? And that social proof is actually super important. And I think that one of the things about women and how we're taught is we're taught, do the work and you'll get the rewards.

But Silicon Valley teaches you a little bit different, right? You have to do the work, that's the baseline. But you also have to navigate and build the right sponsorships in the right corners of Silicon Valley. And then you can get all the money that you want and need. And so we fundraise, thankfully, we are in the position to achieve profitability this year. Not a word. Congratulations.

Thank you. And I think that going through the kind of 2023 downturn really forced people to think strategically about, OK, yes, users, users, users. But what is our money strategy? When are we going to achieve profitability? And how do we do that faster? Because no one wants to see a year like 2023 was.

I think everybody collectively hurt that year. And so it's definitely one of those things that's for if you're building a technology company where you're building a product where you need engineering talent to build the product and then you need the sales talent to help sell the product. You're going to generally use investment dollars, but I think that moving forward, a lot more people will think very intentionally about, okay, how quickly can I achieve profitability and sustain that while not compromising on growth?

So whether it was talking to venture capitalists or being part of Y Combinator, I'm sort of curious, what feedback did you get from all the different investors that you talked to? And did that change the way you look at your business or the way even you manage your business? I think some of the initial feedback that I got was, oh, this market's not big enough. And it wasn't that the market wasn't big enough. I just wasn't telling the story big enough. Right. So I think I learned a lot from that. And then another piece of feedback that I got was, oh, sports, they're finicky. Now they're coming and they're saying that they're not finicky. So I think I learned a lot from that. And then another piece of feedback that I got was,

oh, sports, they're finicky. Now they're coming and they're saying that they're not finicky, right? And so, you know, some people, they didn't like our customers. And then other people, they're like, oh, but is this a $500 billion market? Those were the two kind of areas of feedback that I got. One thing I would pivot a little bit is, I want to tell founders that you're interviewing them as much as they're interviewing you. They're gonna be hugely invested in your business.

And when I had that mind frame going into the conversation, it became a much more casual, like, hey, are we gonna work together or not? And I knew right away, like, if they understood what we were doing just based on the questions that they were asking me. So not so much what piece of feedback did we give, but just feedback I want to give to founders is, make sure that you're interviewing them.

Don't just take the money, because with that comes things. Yep. And you want to make sure you have the people on your side that sees the vision the way you see it too. Agreed. If we had had this conversation a year ago, we'd probably be having a different conversation then than the one that we're having today because there is so much change right now in the world of technology.

I'm curious, with that caveat, what do you think is the next move for your company? Jacqueline, we'll start with you. Just more of what we're doing, more of what we're doing, and being more intentional about measuring results. Like you said, 2023, very, very tough year across the board. We had success last year, and now we have that momentum. So how do we just keep going without taking our eye off the price? I think for us, our next move is global expansion.

So beyond, you know, the sports leagues that we've deployed in the US and that we are on par to expand to. There's an element of Europe, South America, Africa, etc. That there are cultural nuances that are different. There's a lot of language nuances that are different. And so making sure that we are able to effectively scale when we go overseas is going to be a huge undertaking for us. Great. Well, I saw lots of them of Squad, Jacqueline, Samneera of howdy.com. This has been a great conversation and we'll come back to you in just a minute.

Thanks for having us. Thank you. All right. Now, let's welcome to your next move, Emmanuel Ofion, Vice President, CTO Business Bank Engineering at Capital One. Thanks for joining us today, Emmanuel. Thanks Mike. It's great to be here. Inside the systems of every business is a host of data.

Let's talk about how companies can use that data to drive revenue growth. From digital interfaces to customer relationship management systems, technology has given businesses more data than ever. When you look closely, that data offers clues into your customers' behaviors and needs, which can define opportunities for growth. For example, the customer data you already have can help your business personalize communications, online interactions, and offerings for your customers. So what are some other data points that can help businesses find new opportunities for revenue? Your point of sale data or CRM may show purchasing trends that lead to more sales or savings.

For instance, if you notice that particular products or services spike seasonally, those insights may help identify opportunities for new promotions or plan for better inventory management, which can improve your cashflow. And so sifting through all of that data and finding ways to make it manageable seems daunting. How can businesses overcome the challenges of managing so much information? Yeah, it's true that managing data can feel overwhelming, particularly for smaller companies

or those that are less experienced in analyzing data. There are a few key steps that businesses can take to set themselves up for success with data management. First, businesses should ensure that their data ecosystem is well governed. This means implementing clear, regulated policies for how data is organized, accessed, and used across the company. This will ensure that you're meeting any compliance requirements for how you use and store data. Businesses should also regularly evaluate the quality of their data. In order for data to be valuable, it needs to be trustworthy.

In other words, it should be error-free, well-defined, and appropriately stored. This not only makes your data easier to govern, but also makes it easier to interpret and apply. Emmanuel, thank you for being with us and sharing your insights today. Thanks for having me, Mike. I really appreciate it. Here at Inc. we report every day on how AI is changing the way we do business. Next, our own Sarah Lynch explains the benefits of embracing the AI revolution. Thanks, Mike.

You've seen the headlines. AI is everywhere, and its presence continues to grow. In 2024, AI investments surged to $110 billion, up 62% from the year before. The promise is that AI will make growing a business easier, turning labor-intensive processes, like sending collections letters, making sales presentations, or even writing routine code into simple tasks that anyone can complete. So how exactly are companies using AI to level up? And what can you use for your own business?

Businesses of all sizes are already using AI to streamline the boring stuff, automate risk assessments, research, meeting notes, and fraud detection, and make sharper business moves. It can predict demand and help you tweak pricing to stay ahead. The technology can even deliver experiences that feel personal with AI driven recommendations, smart chat bots, and tailored marketing. But let's get specific. Here are a couple of use cases for how AI actively makes businesses

stronger, leaner, and more efficient. Take Neptune Flood Insurance. They developed Triton, an AI platform that's shaking up insurance underwriting by making flood risk assessments faster and more personalized. Their system processes thousands of data points, climate models, past floods, property details to assess flood risk instantly. Neptune Flood reduced customer service costs by 78%, cut resolution time by 92%, and saved $100,000 in one year. Then there's Era MedSpas,

which deploys AI-powered personalization to redefine skincare. The company uses Perfect Core's AI-driven skin analysis to scan for 14 skin health factors. What used to require pricey, bulky dermatology equipment now takes an iPad and a 10-minute scan. Plus, the software lets customers see their before-and-after comparisons, which helps them track their progress and see the results. The impact? A 31% increase in repeat visits,

and a 47% boost in spending per visit. If you're in sales or customer service, AI-powered tools like Salesforce Einstein can automate follow-ups, while chatbots like Intercom handle customer questions 24-7. AI assistants like ReadAI have changed meetings forever with the ability to generate real-time transcriptions, summaries, and actionable insights. If you're focused on operations, analytics platforms like Tableau AI can predict demand,

and finance tools like QuickBooks AI can automate invoicing. The trick is to find the AI tools that actually make your life easier. And while AI is powerful, you may not want to throw all your company secrets into it. Not all tools are secure, so be careful with your personal data. AI-generated policies and contracts should always be reviewed by humans.

AI isn't done evolving. What's possible today might look basic six months from now. So keep experimenting. Find new ways to use AI tools and give new ones a try as they launch. And remember, no matter how much AI evolves, human decision-making matters. The businesses that win will be the ones that blend AI's efficiency with human creativity and strategy. Mike, back to you. Thanks, Sarah. So this season we want to give our audience access to founders like our guests today.

Here are some of our readers' most popular questions about technology and AI. Okay, our first audience question is, what are your favorite tech tools? There are three that come to mind. I just started this tool called Fixer AI, and it is incredible. It's like having a personal executive assistant with you at all times, because it's writing your emails, it's looking at your appointment slots available.

That has given me several hours a day back, which has been great. We also, the team loves ClickUp, where we have so many people distributed across so many different places, and it organizes everyone's task and to do and how it all clicks up cleverly to the main objective that they're trying to achieve.

And then finally, our sales team and our operations team love Gong, because all the sales calls are transcribed, all the action items are taken care of, and then it's all integrated into Salesforce. So all of the information and all the data you can imagine is at everyone's fingertips. So all of the information and all of the data you can imagine is at everyone's fingertips. So those are the three ones for us.

I also have three. The first is Fireflies, which is an AI note-taking tool. You have the ability to record it just from your phone. So I can actually have an in-person meeting that I just press record, and then it also generates all the notes. The second is functional, but with AI layer, and that's Notion.

Our team, especially our product team, loves Notion. All of our task management is managed on Notion. And then the third tool, myself and business development team would be remiss if I did not say superhuman. I call it kind of the COO of your email, like that's not important, don't worry about that. Or okay, hey, by the way, these customers are emailing you now, right? It gives you that prioritization layer across your email that just allows you to be so much more effective.

Our team also says it just gives them hours back of being able to do their jobs. Our second audience question is about tech stack. So how can you assess the effectiveness of your tech stack? One is what are the error rates that are coming up? There was a pretty significant tool that we actually had to move off of because there wasn't enough flexibility here. So we were creating all these creative solutions and-

Workarounds. Workarounds, right? But reality is that we just actually needed to build a much more custom database. And so I think that constraints, when they're popping up with frequency, that's something after you visit. I look at it from a little bit of a different vantage point. My background, I'm econ major, got my degree in economics.

So every quarter, we're looking actually at the cost of everything. And I'm saying, okay, well, what tool is this? And what is it doing? And what's the ROI of that? And I'm constantly, okay, well, what tool is this? And what is it doing? And what's the ROI of that? And I'm constantly challenging the team because, you know, you give people credit cards and everyone runs away. Well, I'm going to add this little tool and I'm going to add this little thing. And it's all of a sudden like a death by a thousand SaaS fees.

And you're like, what is going on here? And so we keep it really in check for the tools that we're investing in. Collectively, we're going to get more ROI from having everything together. So that's how we review it and decide, are we going to make it, invest in it, expand it. If you look across companies that you're familiar with, how do you sort of assess where those companies have the most room for improvement typically? There's two types of CEOs.

There's the founder CEO, and then there's the business management CEO. A lot of times where I feel like companies fall down is when a founder CEO is trying to be a management CEO. They're taking all of these courses on, oh, well, this is what the Harvard Business Review told me to do, and this is what this person told me to do. The same thing too from the management side of things. How much buy-in do they have with their company?

Well, maybe they weren't a day one CEO. So where can they have leverage? So I think we need to be very intentional because everybody has a different version of why they're in that seat. And you just got to use the tools and the information out there that's most effective for you. I would actually say that places where companies can grow and need to grow, and sometimes I've realized it in our own company company is really on the people

side and upskilling people I think is very important to be intentional. We give each employee a certain budget to attend conferences, get certain training each year. Sometimes without the right upskilling of you know management, expertise and growth, it can actually stifle the team. And you have to really be intentional in investing in the people. But it's something that can actually hurt us the most if we don't intentionally invest in it. Great, great.

So our fourth audience question is, what do most companies get wrong when it comes to their tech budget? One of the things that we have to budget for, and it's completely predictive, is there are some usage components of our technology based on how much our customers are using it, their fans, and how with the frequency.

And they're not always easy to get right, but with more information over time, you could become smarter about it. It also impacts the way you code, because I can build something, and I can have a query once, or I can build it without looking back and making it more efficient and realize that it's actually querying five times for that one thing.

Right? And I didn't update it, right? And so we have to go back and say, hey, by the way, our cloud class shot up significantly. Like, what's going on? OK, let's fix that and reconcile. And so I would say kind of usage driven. I would also add that a lot of companies

are penny wise and pound foolish. And so when they're thinking of building something, what we see a lot is like, oh, well I'll just like hire this freelancer or I'll just do this or I'll just do that. And then they hire a freelancer or they hire this person here and they hire this person. I've got this contractor here, I've got this guy here.

And then all of a sudden it's like 10 hodgepodge of very affordable resources that ends up being very, very expensive for you, rather than just sitting down, planning, being realistic about what it is that you're trying to achieve, and then making the investment. Because maybe it's more expensive upfront, but in the long term, it ends up being way better for the company. You're gonna have much better ROI, and you're gonna be able to have more say in influence when you're building an actual team that's bought in, that's a core member.

All right, last audience question, you ready? So what's the best way that I can keep on top of emerging AI trends? So I have a daily prompt from ChatGBT about the five major pieces of AI news that it just shows up in my inbox every single day. And it's been really effective of keeping me, at least personally, on top of what's happening and what's going on.

I actually subscribe to a handful of Digest in New York and San Francisco, Silicon Valley in particular. Our investors are there, our team is here. And it'll tell me, okay, these are the next 20 events going on. And when I start to see interesting things that I'm like, I haven't learned as much about that, but I keep seeing that this is a meetup or this is an event, then I also go and I say, okay,

tell me more about this, right? So the news is helpful, but also, what are the conversations and the events that are happening? And you can kind of glean in and then even participate in them. Great. Aysah Watson, founder and CEO of Squad, and Jacqueline Samira, founder and CEO of Howdy.com.

Thank you so much for being here on your next move. Thanks for having us. Thanks, Mike. And we hope you enjoyed today's conversation, and it encourages you to use the latest tech to your advantage. Tune in next time for more industry leaders, breakthrough businesses, and the strategies you need to make your next move.

Join us next time when we'll dig into more hot topics for business owners. I'm Mike Hoffman and we'll see you next time.