Chris Mailander (00:02)

Today I'm joined by a guest who comes from the blue chip world of Goldman Sachs, Bank of America, EY, and Google. All the big entities that help to define the shape of the future. And the reason that I have asked her to come join us is because of her expertise in helping these entities respond to situational change. That all the changes that are going on in the world and being able to capitalize on those opportunities. And she's doing it now. As a founder, she's founded one company and successfully exited and she's on her second right now. And we'll talk a little bit about that. But I first want to welcome Monica Marquez.

Monica Marquez (00:41)

Thank you so much. I appreciate being here. How are you?

Chris Mailander (00:44)

I'm well, I'm well, thanks. So, as I mentioned, this dynamic of situational context and being able to respond to the changes that we see, which are so dramatic in terms of the technological change, the cultural changes that we see underway, geopolitically, economically, et cetera, you have gone through, it strikes me in your career, being able to help organizations and individuals really respond to those conditions well. There is a dimension of my work that I do with corporate clients where we assess how they're doing and how they're performing relative to their competitors. And we decode who's winning and who's losing based on three variables. And those variables are their decision processes that they're using, the way that their financial engine is constructed, and then the third variable is how they respond to situational context. How do they respond to change? And when we use this methodology, we get very good at predicting winners and losers because it's such a fundamental characteristic associated with it. And I know that you have deep experience in managing through that. Set it up for us. Tell us a little bit about your background.

Monica Marquez (01:55)

Certainly. So, as you shared earlier, I started my career in kind of leadership and inclusion at firms like Goldman Sachs, EY, Google, Bank of America. But across every role, my focus has really been on people, how they grow, how they adapt, how do you stay human inside complex systems? And today, as co-founder of Flipwork, I help organizations and leaders reimagine and reinvent how people work with AI and how do you actually do those two things together? And so we focus on helping people flip outdated beliefs about work and helping teams build more adaptive human-centered cultures in the AI era. Because the reality is, is that you can't have one without the other, especially in this day and age of change, and AI is changing work faster than people can change.

And the one thing that we've learned and here at Flipwork we love to say is that, you know, it's no longer survival of the fittest, it's survival of the fastest. And being human and the natural resistance to change is actually going to be something that's going to hold us back.

Chris Mailander (03:07)

Yeah, you talk about that natural resistance to change. I find that people will always fall back into the comfortable grooves that they've worn in whatever that they've done, whether they've been out in the workforce for five years or 30 years. They want to build on those patterns. There's things that have made them successful. And it strikes me at this point in time, what has made you successful in the past 5, 10, 20, 30 years of your career are not the same things that are gonna make you successful going forward.

Monica Marquez (03:10)

Yes. No, you're exactly right. I I usually like to point out, Chris, that what got you here is not going to get you there, especially in this world of AI and the way that things are changing. I mean, the kind of table stakes or the new currency for success has definitely changed. And we have to get people to unlearn this idea that… You know, it used to be that hard work which hard work is would define how we want to, but really the effort, the time and the kind of like blood, sweat and tears equaled success. 

And what we see is people fearing this thing where then when they partner with AI, it's not as hard and that the amount of time is not as much. And so they start to question their value in that. And so how do you help people unlearn those? Because it's becoming a limiting belief and really getting people to say, well, we really have to focus on your zone of genius. Where are the high quality areas? What are the things that you bring that you can augment with AI and get AI to get rid of the pain points of, you know, OK, if you have a zone of genius where you are really amazing at identifying trends or analyzing data,  half your time or more than half your time is gathering that data. And you don't really get as much time to spend on really deciphering the data. What if you were  able to use AI to gather all that data for you in a matter of minutes and you have hours now to do what is uniquely you. And so that's what we're trying to get people to understand is that, you how do you augment your genius with AI opposed to feeling like AI is going to replace you?

Chris Mailander (05:14)

Yeah, it strikes me that it's not just what we understand, the cognitive exercise, but you're describing also that feeling of how I worked before, which is that, you know, it's an endurance race. You've got to have diligent effort. It's going to take this amount of time. It's got to be hard. And now that it might be a little bit easier and we have the tools and workflow, that that is uncomfortable and unsettling, quite frankly.

Monica Marquez (05:20)

Mm-hmm. Yes. Yeah. I mean, we hear all the time where people like, feel like if I use AI, I'm cheating.  And so we've got to get past that because there's this level of like, "Oh, I'm not, you I'm using AI." But we've seen recently in the last couple of weeks, there was an article in Harvard Business Review where, you know, people now are starting to deal with work slop where they're leveraging AI, but just taking that output for what it is and turning it in.

And that's where we tell people like, no, you can't do that. What you really have to think about is… I like to play on words, artificial intelligence, AI. You have to teach, you have to treat AI like your artificial intern. You would never give work to an intern and then take that work and just give it to the leaders, you know, or give it to the client. You always check that work. You really kind of bring the intern along so that the intern can start doing better output. Same thing with AI.

And so really being able to say, how do you really bring in your authentic intelligence and partner with the artificial intelligence so that you come with a better output? And so those are the things where it's a new way of working and it's hard. And so it's those things that we've got to get people used to - disrupting the way they did work and doing it differently.

Chris Mailander (06:51)

Yeah, part of the fear of AI strikes me, when I see it and think about it, in my own work is that it strikes me that the nature of intelligence is changing, that the pyramid of intelligence is getting much higher, steeper. And for those who are able to use the tools in a really fantastic way, it...

that's where they're getting ahead. Part of the fear is that the capacity, the need for 100 hours of labor now can be done with 30 hours of labor. So does that mean that I don't have a slot? Because what happened to the 70 hours of labor that historically I needed, right? So am I in the 70 group that's gonna get slough off or am I part of the 30 hour group that becomes more intelligent?

Monica Marquez (07:18)

Yeah. And I think you're right. And I think what sometimes people, you know, we have to think about is like, listen, if you put in a 10 hour day, an 8 hour day, doesn't mean that now that you're using AI, you're going to put in a four hour day. What you really need to think about is like, it's the compounding effect of the, of the output and impact. You can have much higher impact where if it, if you were someone who was usually spitting out some sort of like analytical marketing analysis reports.

And on a good day, if nobody was disturbing you, you could like churn out three of them. Well, with AI, maybe now you can churn out nine. And, so it's one of those things where don't stop at three, because then it's just going to be equivalent to the output, and you're going to have somebody else churning out nine in the same amount of time. And, so that's the idea of like, how can AI actually… you know, what's the compounding effect on the impact?

It used to be, like we said, that effort and that blood, sweat and tears, the elbow grease equals success. Now it's going to be impact equals success. How much more impact can you have in your day to day to where the output is better and consistently more than you would in any given day? And so it's really... I really see AI as removing some of the pain points and getting you to really focus on the zone of genius, the things that you love to do.

But it does take a moment to step back and really understand what is that area of expertise? What is that zone of genius? You know, what is your unique value proposition that you've always brought to the workplace that, you know, now you can really focus on and no longer have to focus on the $10 problem of, you know, getting all the data. Now you can really focus on the $10,000 problem where you can actually do, do your best work.

Chris Mailander (09:22)

Yeah, I like this idea also about measuring the impact of your work as opposed to just the volume of the work or the diligence or the pain or the hours and the labor that went into it, but what is truly the impact and if you can achieve that faster than wonderful. Tell me a little bit in the people that you're working with, who makes the turn and who doesn't? So you are helping them work on... things that are, know, substantively what they're doing, but it's also the fear, it's the mindset, it's feeling and working into rhythms and workflows that are new and different and maybe have to be defined, all of which can be unsettling. Some people are going to gravitate to that and adapt to that more readily than others. Tell me more about what you see in terms of who makes it and who doesn't around that turn.

Monica Marquez (09:49)

Yeah, I think, like you said, it's definitely the individuals who are waiting around to be told how to use the AI.  What I really am trying to, like I try to get across to people is that no one is going, if you wait around for someone to tell you, you know, how to use the AI, you're already going to be left behind. Because it does take a little bit of trial and error and testing it out and understanding its idiosyncrasies. It's almost kind of like learning a new language, right? Because you have to communicate with the AI in a different way. You have to learn how to prompt.

And really prompting now is table stakes, right? Once you learned a prompt, how do you actually move over into this more agentic AI of getting it to make sure that the output is consistent, right? And reinventing those workflows to really understand, OK, on any given day, how do I actually get work done? How do I leverage AI to ask AI, how might I do this work differently? And how might I make sure that the output is at a bare minimum x, right?

And so part of it is creating that safe space for people. So it's not just, you know, it's not just the individual themselves, but it's also the organization, the people leaders, the manager to create this psychological safety that you can test and learn. You can take this tool and maybe try to do your work differently. And it's okay if the initial output is a little clunky or you're learning, but really giving people permission to try to do it differently. Because they've been rewarded, like you said, for 10, 20 years of this is the way they used to do work. They had solid work. Why do they want to mess it up? But like you said, if they don't really change the way that they're doing, that solid work is still going to be good work. But the impact of it or the volume of output is going to be, they're going to get dwarfed by people who are actually leveraging AI. And so again, it's this idea that the tool itself, the technology itself is not going to replace people, but people who leverage AI are going to outpace or replace people who don't. And so really, it's the idea of jumping on the bandwagon sooner rather than later.

Chris Mailander (12:12)

Right. And it seems like you have to have a mindset of wanting to disrupt yourself. You have to come into it to say, I want to change my patterning to be able to have higher impact, more intelligence, brainstorm with a tool that allows me to do more.

Monica Marquez (12:20)

Yes. I mean, you kind of like took that thought out of my head. I mean, one of my mantras is always you have to disrupt yourself before you get disrupted. And in this world of work that is changing so dramatically every day with AI, you have to disrupt yourself because even the way you do work today, the way you complete a task today may be different next month because the AI has changed or there's a new tool or something. So you've really.. agility is kind of that new currency of being able to adapt and pivot and change and reinvent yourself. And I think that's been the through line of my career, my success. I've always been able to reinvent myself. And I think that's why I've always kind of been ahead of the curve because I'm someone like you said, who embraces that change. And I think it's even more impactful to embrace that mindset.

Chris Mailander (13:24)

So let's talk about that just a little bit as well, which is that there are these portals that you pass through in your career. And I know that you have done the reinvention. I've done the reinvention as well.

You also come from an environment of these large blue chip global organizations, which are extremely insightful, but it also attracts people that are, you know, a cog in a very large machine. And you have gone through a portal, which is something I think is fairly unique and challenging. And you don't see that often of going from really large organizations like that into the founder type role where you have to, you're not a cog in the machine. You are the machine. You've got to figure out how to make every cylinder run as it were. Tell me about your personal journey through that.

Monica Marquez (14:05)

Mm-hmm. Yeah. Yeah, I think, you kind of nailed it on the head. think there was a piece of me that always felt like I was, you know, having to stay in like third gear in some of these organizations, or I just really wanted to shift into, you know, fifth or sixth or something. And so there was, there's, you know, sometimes the organizations can get so big that, you know, it's like trying to make elephants run, right? It's just like, they're just so big that it's hard to get them to change really quickly and really agile.

And where I found myself being really successful was coming in and partnering with some of these smaller teams and helping them innovate or transform really, really fast. But again, it was kind of like this micro environment in this big macro environment. And every organization that I went to, I realized that it's not necessarily the company itself or the technologies, because the companies are usually pretty progressive in adopting the new technologies.

But what they're forgetting to do is teach the tool or teach the technology to the people. And so where I found the linchpin is that sometimes it's people resisting the change because like we said, we're very complex and we're resistant to change. And so part of it was like, how do I pull myself out? And again, this mindset of focusing on the impact, how could I have more impact beyond the four walls of the organization that I was working in? And so that was part of my journey of saying,

If I leave an organization and I start something on my own, I can have much, I could scale that impact much more broadly, by leaving one particular organization because I found that in every organization I was recruited to, it was basically because it was like same song, different DJ. Can you do this here? Did there? And so it was like, how do I kind of maybe do more for more, if I go out and branch out on my own?

Chris Mailander (15:53)

I think that there's this dimension going on right now that some get and some don't, which is that you're going to have significant fragmentation in the marketplace. I mean, if you look at, I think it's Accenture laid off 11,000 people a week or two ago. You know, I'm sure many of the entities that you historically worked for have downsized. I know that Goldman Sachs has let a lot go and slow down the pace of hiring, et cetera. So these large intellectual organizations that where you do a tremendous amount of research and analytics and processing and it all comes down to the decisions that you either make or that you're recommending in management consulting or you know, EY being CPAs and investment banking, things of that nature, lawyers, et cetera.

When it strikes me that you have the opportunity for these large organizations, that there are new opportunities with smaller organizations that use the workflows better, use the tools better, move faster, as you said, are more agile, perhaps they solve the problems in different ways. And that's where the edge is, it strikes me, that in three to five years, it could look very different when it comes to how some of these industries are organized.

Monica Marquez (16:53)

Yeah. You're absolutely right. And I think, you know, when we think about talent management and talent in and of itself, like, you know, how do you help that talent up skill so that they move, you know, like you said, there are going to be some roles like those entry level analysts who are just gathering the data. Well, AI can gather that data really, really fast and very cheaply. Right? And so how do you upskill those individuals to say, okay, if we looked at it like an assembly line, they're no longer at the front of the line. How do we kind of repot them somewhere else where they can really leverage some of these more high value tasks whether it's discernment or judgment or bringing in some unique curated kind of perspective in there. And so that's what I tell individuals is you've got to really start to look at this macro idea of really thinking about how is AI impacting my industry? How is it impacting my company? How is it impacting my team? How is it impacting me?

How might I, what are the things that only I can do that AI can't do and how might I make sure that I am leveraging AI to augment that even more, but more importantly, letting the powers that be the leaders and others to know how I'm evolving and how I'm the kind of reinventing the way I do work so that I'm not, can be repotted?

I think that's the, that's part of it is, is, you know, it's not just on the company itself, but it's also for the individuals to start kind of widening the aperture and understanding that they're going to get impacted. How do you ride the wave opposed to getting crushed by it?

Chris Mailander (18:45)

Right, right. It strikes me, yeah, I love that. You've got to craft a new playbook, as it were. And I've got one kid that just came out of college and another one is just starting college. You know, I was just with him over the weekend, over parents' weekend, and I'm like, the world that you're entering in three years when you finish up school is vastly different than the world it was a year ago or five years ago. You've got to create a new playbook and figure out, and I like your concept there of looking at how that supply chain works and typically for an entry level person that's coming in doing a research type role or some of that heavy labor that we talk about, the entry point into their career is going to look different.

And it strikes me that what's unsettling right now is that we all know that AI has a huge impact and that we're all ingesting it and figuring it out, but the waters are still choppy right now. The evolution every week of what we see in terms of AI developments is dramatic in the impact. And so it hasn't settled. I don't know what the supply chain looks like. I don't even know where to guide them in terms of the entry point yet, only to say it's going to be different. Keep your eyes wide open and think about it and get ready for it.

Monica Marquez (19:34)

Yeah, and I think you're exactly right, is this idea of like, know, everyday things are changing and you have companies who very quickly adopted AI, they invested millions on AI and now they're scratching their head because they're not seeing the ROI on AI. And the research is showing it's because the adoption of those tools is really relatively low. I was talking to a colleague of mine from Microsoft and you would think Microsoft and Copilot,

Everybody has access to it, but only 47 % of their talent has leveraged the tool. And so, it's like, it's those things that you realize it's a people thing, but those people who are adopting it are the ones who are going to be helping create the change, right? Of letting you know this is how the workflow can be changed and augmented, and you have to be part of it. But like you said, we don't know what's happening right now.

We've seen a big trend on people complaining, saying that they're getting a lot of work slop from people who are leveraging AI because those people are taking AI and just putting out the output and handing it off, which is the other dangerous thing, right? You're crossing the line. It's like AI is resourceful until you cross a line. There's a line in the sand that you can cross it and it becomes un-resourceful when you're just taking it for face value and putting it out there.

I think where people are going to differentiate themselves is really kind of adding their authentic intelligence to the artificial intelligence so that it comes out with a very unique output. And that's what I tell people is like, have to treat artificial intelligence, AI, like your artificial intern AI. You would never give your intern a piece of work or a task and then take their output and give it to the leadership or give it to your client. You always kind of take it, you work with that intern, you kind of like... you know, take that intern through a journey and really kind of transfer your knowledge to this intern so that you come out with the output you want, you have to do the same thing with AI. And so getting people to see it in that way is really where they're going to start differentiating themselves.

Chris Mailander (21:57)

Yeah, interesting. So in this transition from to a new playbook, one of the things that impressed me about your background is it struck me that you were able to go into situations in which there was an old playbook, know, here's kind of how we think about various types of issues and then transform that within that organization. So for example, you would come in through a diversity or inclusiveness type mandate associated with it, but...

Tell me a little bit about how you were able to take that diversity and not just as a focus of inclusion and doing what's right, but instead making the target a financial target, a return on investment, how that could be used, the diversity of voices and ideas was used to create products, to improve products, to improve geographic expansion, things of that nature. So I'm curious in your experiences and if there's lessons that are applicable from that transformational process.

Monica Marquez (22:44)

Absolutely. mean, I think, you know, in this, in this world of, DEI, even though right now it's kind of like this word that you don't want to say, it's kind of like Voldemort, right? You don't want to, you don't want to say the name. But the reality is, that diversity, ethnic inclusion, like it's, it's genesis really came from how do you, how do you actually impact the bottom line?

I mean, when they really started thinking about diversity, equity, inclusion, at least in my experience where they were bringing me in was because companies were trying to do work in other countries or emerging markets. And like, how do you do business with other cultures, with people from other cultures? How do you increase your cultural competency in order to do more work and really get more market share? Well, know, some of where along the line, it became a check the box. And then people kind of forgot this idea that DEI is really tied to ROI.

And how do you actually leverage the diversity of thought to build better products, better solutions so that you can gain more market share or that your product is actually more attractive to the broader market? And so in a lot of my companies, really the teams that were doing diversity correctly were really looking at how do you impact the bottom line? It wasn't just about checking the box on representation and those types of things. It was really how do you take that knowledge from different people, that diversity of thought and really leverage it to make better products.

And I mean, one really great example, there are several examples, right? But I remember way back when there was a study done out there where gift cards were kind of starting to lose their edge. And Amex was like trying to think of all kinds of ideas about how can we increase gift cards.

And they...ended up partnering with all of the employee resource groups. Now we call them business resource groups, but they started saying, hey, you know, what are some creative ideas that we can do for gift cards? And the Asian network was like, hey, well, know, Chinese New Year's right around the corner and it's a tradition to give money in red envelopes. What if you were to create a gift card that was like had a red envelope on it or came in a red envelope? Maybe you'll see something.

They have hard data now where they rolled that out. And over the course of January to February, there was a 20 % increase in the sale of gift cards that were in red envelopes. So you can kind of see this idea of like, there are different ways that you can pull in and really start to leverage, you know, just various different cultures, various different people to say, how might we make the product better and appeal to  various different cultures, right? And so.

That's the idea of how do you extract that knowledge, that diversity of thought, and use it to make better solutions.

Chris Mailander (25:47)

Mm-hmm, yeah, and to come full circle, you're correlating, in that instance, diversity to financial return, to ROI. You'll remember at the beginning, part of the analysis that we use when we decode who's winning and who's losing is a cross correlation between how your financial engine is built, how well you respond to situational change, and the decisions you're making about it. If you are winning on all three fronts, you'll win the race. And right now, I feel like we're in the middle or even the early stages on AI because right now, corporations aren't seeing the return on investment. They're doing lots of experimentation, but they're not getting the adoption. And I also wonder, and I'm curious as your perspective on this, since you have that large company experience, which is, do they...

if you apply AI to old, methods and old ideas and old workflows, you end up with a lot of co-pilots that maybe aren't as transformative. And there might be different applications of ways to weave in AI into the workflow, into the intelligence, into the decision-making process that is more transformative. But if you use the old playbook, you're not going to figure that out.

Monica Marquez (26:49)

Yes. Right. No, that's very, very true. mean, it's, it's, you don't want to limit yourself, right? Like it's like taking your recipe and saying, I'm just going to digitize my recipe, but my recipe isn't going to change at all. And so it's, it's one of those things of really learning and even asking the AI, you know, how might I do this differently? I mean, here at Flipwork we've created, when we work with companies, first, we focus on the mindset of getting people to see themselves working, you know, with AI of like what is their identity? What is their zone of genius? How do they augment their genius with AI? After they do that, then we start to ask them, how might you reinvent the way you do work every day? Or how might you, you know, start habitually, start your day differently by partnering with AI to say, here are the three tasks I have to complete this week. Or, you know, how might I do them? What order should I do them? And maybe what even, what tools do I use, right?

And so really getting this idea of being open to reinvention, right? Of reinventing the way that you do work. Then once you find, once you've prompted it and you find a prompt that works, then how do you actually turn that into an agent that can be repeated over and over? Because the one dangerous thing is people are learning how to prompt, but if you aren't learning to capture that process and having to tweak the output because the output wasn't as good as you wanted it to be,

Once you get the output to where you want it to be, how do you reverse engineer that to say, how do I create this AI agent that can do exactly what we did, all of the iterations to make sure I get the same output every week?

And so that's where you start to really see traction in people differentiating themselves of learning to reinvent that workflow, get the output that you're looking for, and then being able to do more of it better.

Chris Mailander (28:49)

And tell me how you're working with larger enterprises, large organizations as part of Flipwork?

Monica Marquez (28:53)

Yes, we're working with  large enterprises, even some kind of like, know, middle market companies and things like that, are really having to, you know, they've embraced this idea of AI, yes, but how do they get their people to leverage the AI? And it's exactly what you're saying. The challenge is how do we get people to step back and say, okay, let go of what was working, the old playbook, and how do you kind of reinvent that playbook?

And some cases it does have to be baby steps like Playbook 2.0, but at some point they realize like that playbook is just gotta be rewritten. And so it's a little bit of working with those organizations to find out how do you start to automate and really free up your people from the pain points of, if you were to do...

kind of a controlled experiment and have one team do an analysis. Maybe it's some sort of like market analysis report ⁓ and say you do it the old way and then get a team to saying, hey, you guys leverage AI and do it the same way. The output needs to be exactly the same. It's due at five o'clock. And then you find out which report is better. You're going to find that this group spent probably three hours gathering the data. And this group had you know, got the data in 15 minutes and had almost three more hours to actually pull out the trends and do deeper work with the output than the other team. And so we've seen a lot of the research, a lot of the research that has come out that the people who are leveraging AI are having better outputs. And so sometimes it takes that kind of experiment where you have a controlled group and an AI augmented team for them to kind of see it for themselves and connect the dots of like,  the output was better. So, and then they kind of start believing it and trusting in it and then starting to use it.

Chris Mailander (30:48)

Yeah, I love the approach. Red teaming, as it were, which is creating two teams to compete, criticize each other, plus up each other. It's a fascinating approach. Tell me about the genesis of Flipwork. I know that you had another startup beyond barriers that you exited. Why create Flipwork and what do you see going on and what are you trying to capitalize on?

Monica Marquez (30:53)

Yeah, mean, I think, you know, similar to it just kind of goes along with the theme of reinventing. I mean, we saw the, you know, that, you know, the AI and the writing on the wall that, you know, the world was going to get, you know, flipped in terms of the way people do work. And, you know, my area of expertise has always been, you know, learning and, you know, change management, people management. And I saw that really going to be impacted as well. And so the idea was how do we make sure that the old way of learning and teaching and helping upskill people, how is that going to get impacted? And so we really started to focus on how do you help people reinvent and flip the way that they do work? Because otherwise, they're going to be resistant to the change. And because the change is happening so quickly, we're going to see a really messy middle, right? And so it's just like it's basically adopting the technology and really upscaling the people have to kind of coexist in order for those things to happen. And so with that, we kind of saw, we pivoted really quickly and said, we really need to kind of focus on how do we help companies close the gap on the human aspect of the adoption of AI.

Chris Mailander (32:26)

Yeah, and then tell me also about how you think about creating an organization that can grow fast, that can have a huge impact, that enables authentic intelligence as you call it. It strikes me that you can build organizations now that have significant revenue and valuation potential with better tools, technology, and a much smaller, even skeletal crew than you had historically. At least that's the promise.

Monica Marquez (32:50)

Absolutely, I mean five years ago when I created my first company, I mean, you know, we were like, oh, we need all of these people to do all of these jobs. And with, you know, the initial, I mean, you know, we're coming up on, you know, the official launch of Flipwork, but I can tell you right now, you could call it a skeleton group where it's just like we were able to do all of these other things with AI tools, then, you know, bringing in a person and... and, you know, it costing us so much more money or, you know, us thinking, oh, we're going to have to go get funding to be able to afford all of this talent. Now it was like, well, we don't necessarily need funding right now. We can actually start to build all of these things and then get funding to help us just scale really fast. And it's amazing. I mean, some of the research we've read, I mean, there are companies that like predicting that, you know, we're going to see the first billion dollar company with, you know, no more than two or three people, you know, managing it because, you know, they if you leverage AI correctly, you could, you know, you could really do a lot of that. I think for us, you know, we see a little bit of the human has to be involved. So we definitely are going to probably see more humans just engaging because of some of that, those unique skill sets. But definitely, I would say a quarter of the size of a normal kind of human focused company.

Chris Mailander (34:17)

Yeah, fascinating. One of the things I wanted to explore is a bit about your personal background. You have an interesting trajectory and maybe not even what most people would anticipate or think about, which is that you're an Air Force kid with a heritage in West Texas in the oil fields and then end up in New York and in San Francisco in the Bay Area. Tell me about that because that doesn't always conform to the norms.

Monica Marquez (34:36)

Yeah, you know, and it's funny because sometimes I go back and I think like maybe it was the exposure of growing up as an Air Force brat, moving around and learning to be someone who reinvented themselves all the time, right? Because my dad would move around and I'd go into new schools and, you know, getting comfortable with this idea of reinvention. Probably at the time my parents would say I wasn't really embracing it, but it's one of those things that I think really helped kind of wire myself into not being afraid of change.

And so, you know, but my dad retired and we settled in my family's hometown of Odessa, Texas, Odessa, Midland oil country. So I went to high school there, graduated, went to Texas tech university and really, you know, growing up as a first generation, the oldest and only daughter, very traditional Mexican American family. I realized early on that, you know, it was in hindsight, but I realized early on that there was a limited frame of restaurants. I wanted to become a doctor because to be successful that that same playbook like being a doctor, lawyer, engineer equaled success. It wasn't until I got to college that I'm like, what are all of these other majors? Like, wait a minute, like there's something else here. But I still stayed the course because it was what my family knew what we all wanted. And it wasn't until, you know, my senior year in college when I was getting ready to go off to med school, I had a mentor who knew me and he was like, you know, why do you want to be a doctor?

And I was like, well, because my family, it's, you know, it's all I know. And he kind of challenged me to say like, well, but over the course of the four years, I've seen you do all of these amazing things on campus and none of them, you know, and you would light up. He's like, but when you talk about your medical school or your biology classes or whatever, you don't light up in that way. He was just like, and he was the first person who got me to think about like, what is my zone of genius? And so that made me pivot. And before I knew it, I was pursuing a different master's degree, graduating, moving to New York City. And it was really kind of that... the widening of the aperture of like what I could become was kind of one of those things that just was like an a-ha moment. So yeah, it was very unique in that way, and really always chasing that like zone of genius. What am I good at?

And you know, so my nickname for, you know, my family is like your ‘MacGyver’. Like you figure all of these things out. Like what is the next thing that you can kind of get a hold of and figure out how to do. But yeah, and I realized that the through line has been embracing change and reinventing and pivoting and not saying no to an opportunity that like, how might I, you know, do career differently?

You know, it doesn't necessarily have to be this linear line which for me was breaking a lot of the cultural norms of, my mom was a lifelong teacher. My dad was in the military, but even when he got out of the military, he was still doing the same work that he did like his entire life. And so I think I was one of those that kind of broke that generational curse of like, you can do lots of different things if you're following your, like your passion and your, your zone of genius. So, yeah, it's something that I think was, is, was a byproduct of, of just having to experience change early on and being comfortable with it.

Chris Mailander (38:08)

I love it, Monica. And we are certainly in a period of change right now. I mean, it just feels like the pace is, I've been doing this for 35 years. The pace just keeps increasing and it's almost at an exponential scale now. So, having that ability to change and adapt and find, reinvent and create that new opportunity and also recognize that it's sometimes the feeling is going to be uncomfortable and the mindset has to change. It's awesome.

I want to thank you for spending some time with us today.

Monica Marquez (38:39)

Yeah, thank you so much, Chris. I appreciated it and loved the conversation.

Chris Mailander (38:43)

Absolutely.