AI is becoming an Assembly Line for the Mind

Monisha:

Welcome to Colorado Tech People, where we talk with the innovators shaping how technology is transforming learning and work. Today's episode explores how artificial intelligence is entering the classroom and changing the way students and educators engage with knowledge. I'm joined by France Hoang, founder of Boodle Box, a platform designed to help colleges and universities integrate AI responsibly into teaching, research and collaboration.We'll discuss how institutions can build AI literacy, maintain academic integrity, and prepare students for an AI-driven future. Let's get started. France, thanks so much for joining me on the podcast. It's really great to have you here.

France:

Monisha, it's great to be here talking about one of my favorite subjects, the intersection between AI and higher education.

Monisha:

Perfect. What inspired you to build Boodle Box specifically for higher education? And what gaps did you see and what problems were you trying to solve?

France:

Yeah, so I'm an immigrant. I was born in Vietnam. I was evacuated when I was two years old from Saigon by US military.I came to the United States, grew up in Washington state, and I've had amazing opportunities. I've gone to West Point. I got a master's degree from Washburn. I've worked in the White House. I went to law school at Georgetown. I've been able to start companies. And none of those things would have been possible without the power of education. And so on my entrepreneurial journey, I've had a couple of other companies and somewhat successful. When Chat GPT happened, I just felt strongly that there was going to be too much AI in AI. And I felt that because my love of education has led me to serving as a trustee of a university, teaching in the classroom as a visiting lecturer at West Point. My love of technology has led me to build AI products for a better part of a decade. So was doing AI before AI was cool. The intersection of all those things is Boodle Box.I became and remain concerned about getting the relationship between people and AI right. If you're concerned about that, the natural place to start is the classroom, because the classroom is at the leading edge of figuring that out. How are humans and AI going to interact? Is it going to be responsible? Is it going to be collaborative? And so I wanted to build a platform, the platform for human AI collaboration, for responsible human AI collaboration. As it turns out, that desire to get that relationship right also dovetails with the fact that education is itself undergoing a transformation.We have had in many cases a very transactional model of education. You do enough of the right kind of work, you produce the right kind of product, you get a grade. If you get enough grades, you get a degree and you can trade that degree for a job. Well, that is under tremendous pressure right now. I just saw an article that talked about how Gen Z men, they have the same unemployment rate whether you have a college degree or whether you don't.Well, that's remarkable, right? That's obviously going to cause people to question what is the value of education. Now, don't get me wrong. Obviously, I think there's tremendous value education. But I think it's AI has just revealed that we need to think about what education delivers and how it delivers that. Whereas before, we've always wanted students to engage in critical thinking, deep thinking, metacognition. And the kinds of assignments we gave to write the essay, write the project, the only way to produce those work products was to think, right? And to create and to comprehend. Well, now you can create those same products with AI. So students being students, right, have optimized for that. They are not engaging the kind of activities we want for learning, right? They're not engaging in the productive struggle. And so I think part of what we're doing at Boodle Box is giving the tools and the infrastructure so that teachers can teach and students can learn by returning that productive struggle to the classroom, but alongside AI. So that's what we're doing and that's what we're passionate about, Monisha. And yeah, look forward to exploring this further with you.

Monisha:

Yeah, well congratulations on the growth you're seeing. Over 100 universities have adopted Boodle Box in 17 months. What created that momentum?

France:

Yeah, we're meeting, I think, universities right where they're at. So they are suffering from a number of pressures and trying to solve a number of problems. First, for the students, there's a student in the classroom right now who's using AI, and the student next to them has the resources to pay for better AI. And they're going to get an unequal outcome in that classroom that allows AI simply based on the access they have to resources. And so one of the problems we solve for is equitable access to AI. We provide unlimited access to all the top AI platforms in one place. And so an institution that is concerned about equitable access, we're the solution. We can, you know, at a very affordable price, provide that universal access. For the faculty, they want their students to learn, obviously, and they need a structure for that teaching and learning in an AI era. And we call that the AI native classroom, a classroom where you can work alongside AI, you can work alongside multiple AIs, you can work alongside other students, and the work you do isn't just evaluated on what's produced, but the process by which it's produced. And so there's, and the professor can introduce as much as literal guardrails around the students use of AI to create that productive struggle that leads to learning. And so for professors, it's giving them control of that AI classroom while also providing them tools to learn about AI itself, right? AI literacy. So let's not forget educators are on as much of a journey as the students are on. And then for the institutions, they have to deal with the fact that there's a sprawl of AI tools, their IP is going into free tools. So we provide CIOs an ability to enable all of their educators and students to succeed in a way that's safe and secure and affordable. And so it turns out that trifecta of student choice, of educator control, and the needs of institutions for compliance and safety and security, by solving all three at the same time, we're really answering an urgent need. And that's why over 100, as you mentioned, over 105 colleges and universities are now using Boodlebox's AI infrastructure.

Monisha:

Fantastic. And when you're building these tools for the classrooms, how do you decide which features truly improve learning versus adding unnecessary complexity?

France:

Yeah, great question, Monisha. The short answer is, I'm not sure. So we go to the folks who do know. We have AI Leadership Council of Educators over 100. We spend a lot of time listening and learning from those at the cutting edge, right? The professors and students in the classroom right now.You know, I'm based here in Colorado. Our company is headquartered in Colorado Springs. So, you know, just a month ago, I was at Pikes Peak State College, you know, talking to students, talking to professors, meeting with the administration, getting their feedback. And so we spent a lot of time talking, listening, and then visiting. I will visit, I think, four colleges this, you know, later this month, spending time in the classroom, spending time with students.It's really important. This is really changing fast. And so we don't want to guess, we want to know. And the best way to know is to talk to the folks that are in the know.

Monisha:

And was it hard? I mean, you say you're offering access to the top AI tools at a discounted price. So what were those conversations with ChatGPT and so forth? Was that a difficult conversation to have with them, to get them to offer you a discount?

France:

Yeah, so we're using their commercial APIs. And by the way, there's multiple places you can get access to those APIs, right? They offer them directly, they offer them through third party services. Our ability to offer unlimited access is actually based on a proprietary piece of technology we built inside Bootlebox. So we have a token reduction technology that allows us to reduce the number of tokens required to produce a AI response, but up to 96%.And so that does a number of things. One is it makes it affordable to provide unlimited access to all these top AM models in one platform. Second, it reduces the energy consumption and the environmental impact, which is of great concern to a lot of students and educators. And third, it actually makes the platform more secure. We don't send all the data out that we have, we only send what's relevant. And so it's yet another way we secure user data in a way that is not just FERPA compliant, right, but further respects privacy. And by the way, it actually produces a better output.

Monisha:

Really interesting. And can you share one hard product decision that you took when building Boodle Box?

France:

Ooh, good question.So I think one of the really common mistakes that entrepreneurs make is they try to, they fall in love with their solution and they try to build it to meeting the needs of lots of people in lots of situations, right? Versus really trying to focus in on a particular customer, a particular pain point, a particular partner, a particular use case. And so I think every day is filled with hard decisions like that, Monisha, right? Especially in an era of AI, you can build anything at any time. You know, the...I think we're all familiar with what's happened with software development over the last year. And so there's such a rapid pace of change. We put out a release every week. So we're constantly in the mode of improving the platform. And so the decision, the hard decisions are we see all these opportunities to do these things that are more, but more isn't necessarily better. So...When do you add features? Who are you trying to serve to? I think the key is to have a North Star and the North Star is what's going to help your partners, right? What's going to help the educators? What's going to help the students? What's going to help the university? And so that in many ways makes the hard decisions easier because now you've got a focus and you've got a kind of a North Star to go by. And that runs through everything, right? What does the user interface look like? What models do we provide? When do we add support for certain features?And so those are all freaking hard decisions to be honest, like really freaking hard decisions. But they're made easier by having a North Star.

Monisha:

Good advice. Advice for other builders, choose your North Star wisely. How does Bootlebox help faculty integrate AI into courses while still maintaining academic integrity and transparency?

France:

Yes.Yeah, so there's a saying I've been, analogy I've been saying a lot. So the key right now for AI adoption and implementation isn't faster horses, it's better roads. So we've been very obsessed with like better AI, faster AI, more AI. But as it turns out, AI adoption isn't an AI problem, you know, it's a human problem.You know, am I trained? Do I understand the use cases? What's the infrastructure? Is my organization is designed to support this? Have I changed my workflows? And so in Boodle Box both provides the faster horses. We provide the better AI, but we also provide better roads. We provide the infrastructure for a professor to use that. And so what does that look like? It means that when I ask a student to, and I allow a student to use AI, I don't simply say, well, and also document what work you did,Like I can't tell anything from that. All the students have done is acknowledge it. Imagine instead that they could share a link, which they can in Boodle Box, to their actual conversation. Well, now I can see that conversation. I can see the process which they produce something. But, right, that's unwieldy. Now the student has to copy and paste that.That's a lot. Now I've got all these links everywhere. Well, we've also created a structure, the AI classroom, where you can assign work to the students and they can do the work in AI. All that automatically flows into a user interface where I can see all my students work. By the way, outside of the AI classroom, all the student use of AI is private. We are big proponents of privacy, but inside the classroom, everything is transparent.Well, that's great. Right now I've got all the student work, but that's a, that's a lot. Am I going to read like hundreds of pages of chat transcripts? No. Now we have tools that allow you to apply AI to assess that work, to even let the students self assess their work with AI. You can do analysis of that work. You can apply rubrics if you want, and then review the results. You can create simulations and tutors. And so maybe, maybe the model of you do the work, I grade the work and I'll give it back to you. Maybe we can.and flip that on its head and maybe we can think about other things. So this is what I mean by the AI native classroom. It opens up a world of possibilities, not just to do what we did yesterday better and faster, but maybe to do things tomorrow that we couldn't even do today.

Monisha:

It's really exciting, a bright new future. How do Boodlebox's features like custom AI assistance and collaborative AI chats change the way students engage with course material and with each other?

France:

Yeah.Yeah, I love to the story. So Christina Kahlberg from Point Lowell, she teaches marketing out in San Diego. And she does her typical marketing course, does a lecture, but then the students are required to take their notes and actually build a marketing assistant, AI assistant in Bootlebox.And that marketing assistant has all their notes and they're training it or quote unquote teaching it right. How to do marketing.And then her assessments aren't essays or quizzes or anything like that. They're real world case studies where the students have to collaborate with the marketing AI assistant they created to solve real world problems. And then as the semester goes along, they actually do this in groups where you have multiple students collaborating with each other and multiple AIs to solve real world problems. So all of a sudden the student isn't just learning marketing, they're learning how to build AI assistants and they're learning how to collaborate as part of a human AI.AI team. So this is what I'm talking about. This is an AI native classroom. We're teaching skills that go beyond just knowledge. They are developing expertise. They're developing how to responsibly use AI. And they're developing really durable skills of collaboration and critical thinking and communication all at the same time. And that's the direction education needs to move.

Monisha:

Wow, really fantastic. It is transformative in terms of how people are teaching in the classroom today. It sounds very different from the marketing class I took.

France:

It can be. Now I to say that may sound, you know, some professor, listen to this, maybe sound like that sounds like a lot of work. So we are trying to build the tools that make it easier, right? You know, agentic support and tools and tool kits that make it easy for a professor to look at where they're at now.decide on where they want to be in terms of their teaching and their pedagogy and make this an evolution, not a revolution. One thing we have found is everybody's at a different place in their AI journey, and that's perfectly fine. And it's also perfectly fine not to use AI. So I want to be clear that like, you know,AI is not the answer for everything. There are plenty of educational activities where AI should not be involved and where we really need to lean in on real world and communication, interaction and...Other things just because you can doesn't mean you should and that might sound funny coming from an AI founder. But I you know, I also believe in academic diversity and choice and AI is a wonderful tool, right? It should augment our potential not replace it. And so there's a lot of excitement on AI and I think there's a lot of potential use cases, but I think we should also be thoughtful about when and where we incorporate it.

Monisha:

Are you seeing in the classroom that there are some classes where AI is restricted?

France:

plenty. there's still and I think this is the grand, you know, to certain extent, this is the unintentional and unvolunteered experiment we're all in, right? There's AI everywhere. There's a study that 92 % of students are using AI for academic work in some way. I think they missed 8 % that weren't telling the truth in that survey properly. But yeah, think there should be, and that's another point, there should be a lot of room for experimentation. There should be, you know, there are folks who want to fully embrace it. There are folks who...want to embrace it at all there's everything in between and that's both on the faculty side and the student side and that's fine. I am not a fan of detection though, the idea of like trying to detect AI work and discipline students. I think it creates an unhealthy adversarial relationship between students and professors. I think there are ways to address that mainly through redesigning assignments and redesigning assessments.where we can stand side, you know, a student, a professor, and an AI can stand side by side kind of pointing in the same direction versus against one another.

Monisha:

And can you give an example of a feature that you decided not to build and explain why you decided not to build it?

France:

Yeah, we, there's a lot we haven't built yet, mainly because we just didn't feel like it met our North star. You know, one of the things that we're eager to build, right, is even more collaboration features that allow for, you know, notifications and tagging and, you know,kind of further human to human things, but realize that's more appropriate for a work teams, workforce application than an education application. there, you know, right now, if you go into the top AI platforms, right, there's all these connectors and ways to bring in outside data.In many ways, we will eventually add such features, but for now, it's not necessary in a teaching and learning environment.It doesn't support the core use case of teaching within about AI in responsible way. And so we've delayed implementing those. If this is a work team platform, we need those from day one. But again, I think this goes back to what we talked about earlier, the discipline of knowing what you're trying to be, and then ruthlessly focusing on that rather than trying to be all things to all people.

Monisha:

And how big is Boodlebox now? How many people work there?

France:

We've got 21 people inside the company right now.

Monisha:

Yeah, cool. And what's your fundraising strategy? Are you planning on raising more funds? Are you bootstrapping? Or how are you building the company?

France:

Yeah, we raised a seed round about six months ago, a five-month seed round led by Osage and Dogwood Adventures.You know, I suspect that not too long from now we'll be raising again. You know, we've had, you know, we hit a million in annual current revenue in less than a year. We're at 3 million in fully ramped contracted revenue here, you know, six months later. So we're growing at a pretty good clip. And we're going to, think.We're going to want further resources in order to accelerate that growth and to build an even better product that further meets that North Star.

Monisha:

So do you feel like you've hit product market fit?

France:

I don't think anybody ever feels like they did product market fit. There's always more you want to do. One of the best definitions I've ever heard of product market fit is also one of the simplest. It's just simply pull. Are the customers pulling the product out of your hands, even if it's not perfect, even if it's incomplete, even if it's broken? And we see that.You know, we have outreach every single day from faculty and from institutions that have an urgent need for AI infrastructure for teaching and learning.Yeah, and so we certainly feel the pull. And we're also seeing the pull from work teams. We have organizations that are not in higher education that clearly have expressed the need for a platform that allows for work with multiple AIs, that allows for collaboration between multiple people, is safe and secure, and provides that infrastructure for what we call the AI native work team. And so we're seeing that pull as well.

Monisha:

So do you think you're going to diversify and go into corporate subscriptions?

France:

Yeah, so to be clear, we already have over 100.companies, work teams from companies that are using the platform. So that diversification has already occurred. Our focus is higher education. But to a certain extent, work teams kind of comes with the territory. If you think about it, if we are a platform that is preparing students for an AI ready workplace, then the students need to be using the same tools and the same infrastructure that they'll be using when they graduate. And so we're kind of by definition to build a platform for AI readiness ineducation, the platform had to also be able to do that in the workplace. And interestingly enough, over 100 teams agree with us and have found Boodlebox and are using it from everything from nonprofit fundraising to military planning to litigation to consultancies.

Monisha:

Yeah. And are the main selling points, it's a discounted price and the security?

France:

I think those are table stakes, frankly. I think the main selling points is the fact that you have access to multiple AI models, so you're not locked into any one model. You can use them together. So it's not just having access. I can research a complexity draft with Claude, then ask OpenAI's GPT models to evaluate. And then the human collaboration. Work is a multiplayer sport.Yes, we do individual work, but we eventually have to bring that together. And right now it's really awkward. I do something in AI and then I've got to what? Cut and paste it? Put it in an email? Instead, what if you and I were working on something, what if we were in the same together with the AI tools that we're using and we could actually just collaborate directly? And that's what bootlebox is. And it turns out there's a lot of use cases for that.

Monisha:

Wow, so I mean, this could be really massive, right? I mean, if you think of all the universities and all of the companies out there all using AI, your TAM is pretty big.

France:

Tam is pretty big. Look, I think we're at this moment where, one of my favorite TV shows is the Men Who Built America. a history channel series. It was about the Gilded Age. It's about the Vanderbilts and Rockefellers and Fords reshaping American society and the world through the industries they created. And I think about the assembly line, right, and the way it changed the way we do manual work, the way we produce goods. Well, if you think about it, the AI is in many ways, right, an assembly line for the mind, right? It is automated intellectual work the way the assembly line automated manual work.And so we're at this stage where we've, know, it's a bit of transition. What does that mean? You know, up until this point, until November 22, if you wanted to do something intellectually, largely, you had to do it yourself, right? Now, look, there's some automation and RPA, but nothing at the scale we're seeing now. And so what does it mean to be a knowledge professional? You know, I think there was a time where,Knowledge equal expertise if I know something I'm valuable for knowing that thing Well an age of AI I would argue maybe knowing things isn't By itself isn't that valuable now having knowledge and then knowing how to apply it? Knowing how to contextualize it knowing what questions to ask knowing having the judgment of knowing When to rely on something and when not knowing what the jagged edge of it is and knowing how to collaborate with people that what I would call domain expertise as opposed to just domain knowledge. I think that's the real value today. And so we've got to, I think we are in an era where we have to create domain experts. We have to be facile with AI, be AI enabled. And we have to double down on the things that make us uniquely human, right? That critical thinking, that collaboration, that communication. That's what the worker of tomorrow. That's what the worker of today needs to become. And then companies need to think about how they do business and perhaps even reorganize around that kind of employee. And that's what I mean by better roads, not faster horses.

Monisha:

Thank you for that. As you've built Boodle Box, how has being part of the Colorado tech ecosystem influenced your growth, hiring, or partnering with universities?

France:

Yeah, so we're based in Colorado, we are active members of the ecosystem here. Our company is based out of exponential impact. When we raised our last round, had participation from service provider, Capital, which is a capital provider here in Colorado.It's been great and we have partnerships with multiple schools in the Colorado Community College system. also running pilots in a couple of the CU schools. And so, I get the distinct privilege and pleasure of being able to work with educators and students from around the country. visited dozens of campus. Obviously I have a soft spot in my heart for the hometown heroes of our own educators and educational system. And so I'm always delighted to work and be a resource with them.

Monisha:

and what advantages or challenges come with building an education technology company outside traditional tech hubs.

France:

Yeah, there is this thing, right? If you're in San Francisco or New York or Boston, maybe we throw Austin to mix, right? There's more capital, there's more talent, there's more of a focus. It's easier to fundraise. And I wouldn't deny, at least on that last point, that those are true.But I obviously believe it's possible to build a valuable company outside of those tech hubs. The reality is we're a remote company, so we have people all over. We do have a nucleus of employees here in Colorado Springs. I think if you're outside of Silicon Valley, I think...You just need to recognize you're not playing by Silicon Valley rules, right? Like you can raise money a certain way, you can find people a certain way out there. And, you know, I think it's undeniable that it's easier in many ways. That being said, there's plenty and plenty of examples of companies, valuable companies that have answered a real need, have an impact, raised money, and been very successful even outside. But I think to answer your question in a more short, condensed manner, you just need to know who you are.Don't try to be something you're not. You're not a Silicon Valley-based company that's trying to grow at a certain rate and raise money at certain rate. You're something else, and that's fine.

Monisha:

know yourself. What lessons have you learned about scaling a platform that must serve many institutions with different policies, cultures, and technical needs?

France:

Know yourself.Yeah, the schools that are, you the institutions are getting right. They're recognizing that AI actually, the adoption of AI isn't a technology problem at all, actually. It's a people problem. It's an organizational problem. It's about providing training. It's about evolving pedagogy. It's about creating structures and incentives that enable, or at least don't hamper the adoption of AI.Access doesn't equal adoption. There's a number of schools that bought large licenses, oftentimes without the involvement of faculty and students thinking they were quote unquote solving the AI issue and have been disappointed by the results. And we're seeing that time and time again. The most successful schools don't just invest in the platform, they invest in their people. And they invest in the organizational change required.to go from AI independent to AI enhanced to what I would call AI native, where you're kind of rethinking your organizational structure and the way you do work. it's, look, I think we're all learning and I think we should also give ourselves a lot of grace on that. I also recognize the...the challenges of a larger organization, the harder it is to transformation, let alone radical transformation.

Monisha:

And what measurable changes have universities reported after adopting Bootlebox?

France:

Yeah, we had a wonderful pilot at Pikes Peak State College. They introduced Boodle Box in an English writing class, right? Like that's probably like ground zero for difficulty with AI. And the students reported that 90 % of them felt that.Boodlebox was a more ethical way to use AI, probably because of our token reduction technology that reduced environmental impact. There was no cases of academic integrity issues because using AI was the point. The professor reported that the student output was among the best, if not the best, she had seen over the last two years of teaching. 83 % of the students felt more comfortable using AI after even one session with Boodlebox.because we provide this AI coach that actually teaches you how to use AI better inside the platform. And 87 % of students prefer to do it over free AI tools. And so pretty solid results from a pilot. And Pikes Peak has now adopted Bootlebox across its campus. And so we're continuing to grow on those early results and see what else additional impact we can have onon student teaching or student learning and educator teaching.

Monisha:

Wow, and speaking of that, like looking ahead, how do you see AI reshaping higher education over the next decade? And what role do you hope Bootlebox will play in that transformation?

France:

Yeah, I mean, our goal is to be the infrastructure and the partner of choice for institutions that want to create this AI native classroom, that want to have teaching and learning where.professors and where educators and students can collaborate with one another and collaborate with AI in a responsible way. I think education is going to evolve. It has to evolve in a number of ways. Learning is going to be personalized and continuous. We can do that at scale now and and.It doesn't have to happen just inside the classroom. It can happen in between, right? And it can happen after. I think there'll be a realization, and there already is, right? AI is best not as a tool, but as a thinking partner. And how do we teach students to work with that partner responsibly? And how do we as educators use it responsibly? I mentioned earlier about the difference between domain expertise and domain knowledge. I think schools...One of my favorite quotes is from Plutarch about education. He said that the mind isn't a vessel to be filled, but a fire to be lit. I think there'll be a realization, a further realization, right, that we don't want domain knowledge, we want domain expertise. We don't want to just fill minds, we want to light fires. How do we, and how do we create students' experiences that value judgment and creativity and reasoning? And that's gonna almost certainly involve AI in some way.It doesn't have to, but from a resource perspective, it's easier if we involve AI. And then ultimately, think colleges, the workforce is going to value the ability to collaborate and lead human AI teams. And I think colleges will have to lean into that, And that, because that'll, if that's what the workplace demands, our higher education institutions will respond to that demand by introducing that in the classroom.And many already are.

Monisha:

Can you give us an example of a mistake you made early in building Boodle Box that taught you an important lesson and how that changes how you make decisions or lead today?

France:

Yeah, I mean, I think in the...So most of what you do as an entrepreneur is not gonna work. That's kind of the hard truth, right? Like you try a lot of things, hopefully you iterate fast, hopefully you fail just as fast and learn even faster if at all possible. So in the early days of Bluedobox, we...we were experimenting. So, when you say mistake, I'm hesitating a little bit because somebody once told me, in fact, I was just talking to someone earlier today and they said, look, you either win or you learn. Like there is no losing, right? And so I feel that the way about Boodle Box and our journey, right? We either got it right or we learned something from it. And so is that a mistake or is that just the path to learning and getting better? And so we constantly make mistakes. introduce,We introduce a feature that we think will make things better and there's an unintended consequence on it. I'm trying to think of a more recent example. we had users that felt like the platform wasn't snappy enough in terms of providing responses. And so we changed the way we stream the responses from.word to word to letter by letter. It turned out it had the unintended consequence of not streaming if the user wasn't actually on the tab, right? And so it caused users to think that there was nothing going on when they came back. Well, that's not true. It was just happening in the background. Now that's a technical quote unquote mistake, everything you do has intended and unintended consequences. Maybe more big picture. Early on, we were trying to figure out the right way to package this human AI cloud.early on we actually experimented more with like a message board style of interaction versus less of a one-to-one style. It turned out that was the wrong model for human-AI interaction. The social media model wasn't appropriate for the AI era.develop that further and we focused more on kind of a know a message style one to many or many to many type of interaction.

Monisha:

And a final big question. Looking back, what do you wish you'd known before starting the company and what would you do differently if you were building again from day one?

France:

Yeah.It's a bit of an unfair question because I think to the point what I just said, you're the winner, learn. If you don't have those mistakes and those failures, you also don't get the learnings from them. We wouldn't have the product we have and we wouldn't be the company we are if we hadn't made those mistakes and had those failures along the way.Now if you're asking me if I could go back in time and undo those mistakes but still keep the learnings, obviously that'd be great. We would be five times further than we are. But I think that's an unrealistic kind of thought process. In fact, I don't really, my brain doesn't work that way. One of my favorite mantras is ignore sunk costs.Like I don't dwell on the past. I don't even dwell on the present that much. I'm just thinking about the future and how we can do the things today to make that future state we want to have happen. And so I guess the short answer is like, look, there's a lot of things that I wish we'd done faster and done better, but the reality is all those things that we did quote unquote wrong taught us the things that helped us get it right. And that's okay as a founder. Just do it fast, do itright and do it honestly.

Monisha:

And last question, what is a book that every builder should read?

France:

Ooh.So there's this great book called Freedom's Forge. It is about the industrialization of the US at the start of World War II, how we went from having a standing army smaller than Belgium and focused on making cars and nylons. And then we switched over to having an army that could fight and win on the beaches of Normandy. And we were making parachutes and tanks.And that is a fascinating story about innovation, about disruption, about entrepreneurism. Highly recommend it. I think any entrepreneur would enjoy that book.

Monisha:

Fantastic. Well, friends, it's been a real pleasure having you on the show. Really enjoyed learning from you and learning more about Boodle Box and all the lessons that other builders can take from you. Thanks to our listeners for listening to this episode of Colorado Tech People. If you enjoyed this conversation about how AI is shaping the future of learning, be sure to share it with an educator, student or innovator in your network. Don't forget to subscribe.so you can hear more stories from the founders and builders transforming industries in Colorado and beyond. Until next time, keep exploring how technology can create real impact in people's lives. Thank you again, France.

France:

Thanks Monisha, it's great to be on.