MacKenzie Price, founder of Alpha School & 2 Hour Learning, discusses her revolutionary educational model that uses AI to enable students to master traditional academics in just 2 hours per day while achieving 2.3x faster learning rates than statistical models predict.

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MacKenzie Price, founder of Alpha School & 2 Hour Learning, discusses her revolutionary educational model that uses AI to enable students to master traditional academics in just 2 hours per day while achieving 2.3x faster learning rates than statistical models predict. The conversation explores how Alpha School combines adaptive learning apps with personalized curriculum systems rather than giving students direct chatbot access, and how this frees up afternoons for field trips, independent projects, and interest exploration. They discuss the transformation of teachers into "Guides" who focus entirely on motivation, mentorship, and emotional support rather than content delivery, creating transformative relationships with every student as the rule rather than the exception. The episode reveals how this AI-powered approach maintains rigorous academic standards while potentially revolutionizing education without disrupting the teaching profession.

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CHAPTERS:
(00:00) About the Episode
(04:01) Introduction and Welcome
(04:26) AI Revolution in Education
(06:45) Two Sigma Effect Explained
(10:49) Understanding Two Sigma Results (Part 1)
(16:28) Sponsors: Oracle Cloud Infrastructure | The AGNTCY (Cisco)
(18:28) Understanding Two Sigma Results (Part 2)
(18:28) AI Scalability and Efficiency
(22:39) AI Tutor Experience Design
(30:48) Technology Evolution at Alpha
(38:29) Early AI Implementation (Part 1)
(38:36) Sponsor: NetSuite by Oracle
(39:59) Early AI Implementation (Part 2)
(45:43) Fifth Grade Math Investigation
(49:51) Future of Personalized Learning
(54:48) Multimodal Learning Experiences
(58:52) Role of Guides
(01:05:25) Hiring and Teacher Transformation
(01:10:27) Economics and Scalability
(01:18:03) DIY Education Advice
(01:22:10) Outro

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Transcript

Introduction

Hello, and welcome back to the Cognitive Revolution!

Today, I'm speaking with MacKenzie Price, founder of Alpha School & 2 Hour Learning, and pioneer of a new educational model that's using AI to scale 1:1, mastery-based tutoring to help students learn 2-10X faster, such that they can finish traditional academic subjects in the morning and then spend their afternoons taking field trips, working on independent projects, and otherwise exploring their interests.  

Importantly, just because the Alpha School model is futuristic and gives kids lots of free time does NOT mean they've gone soft on academic standards. On the contrary, MacKenzie frames learning time as "productive struggle" and Alpha Schools demand focused effort and expect students to master all the usual common core subjects.

The results speak for themselves: despite spending just 2 hrs per day on academics, which means spending some 20-30 hours per subject per year, or just 10-15% of the 200 hrs per subject per year that's standard today, Alpha School students learn 2.3 times more per school year than statistical models predict they would in a normal school, and their school-level results on standardized test are nearly always in the 99th percentile.  

In this conversation, we explore both the AI product implementation and the way in which the rest of the school experience is changing, starting with:

Why MacKenzie does not recommend that schools give students access to chatbots, and what they do instead – which is to combine an ever-evolving mix of adaptive learning apps, which they both build & buy, with systems that analyze learning rates & patterns and make personalized curriculum recommendations, plus more and more lesson-level personalization & multimodal support all the time.  

We also discuss

- What kids are doing in the afternoon once their academics are complete,

- how Alpha School is beginning to teach them to use AI as a superpower, 

- and How the Alpha School model can be adapted to different price points, including the possibility of Public Charter Schools and the new Home School option they're starting to rolling out.

Perhaps most importantly, we explore the evolution of the role of the teacher, which Alpha Schools call Guides or Coaches, and what it means both for kids and the future of work more generally.

As MacKenzie explains, because Alpha's Guides don't have to worry about delivering academic content, they can focus entirely on motivation, mentorship, and emotional support, and the school can both hire for those skills, and hold them accountable to making sure that each and every kid truly loves school.  

I find this vision super exciting because, both because this does seem like one major area of the economy that AI can positively transform without also disrupting the labor market, and because when I think back on my own education, it was clearly the teachers who made an extra effort to engage me with special projects, one-on-one conversations, and possibilities for my future I'd never considered who made the biggest impact.  

I was privileged to have quite a few who made their mark: Mr. Francis and Mr. Rogers in 6th grade, Mrs. McBain for Biology, Mr. Vance and Ms. Kohut for high-school English, Mrs. Voss for AP History, Mr. Andriaschko for Chemistry & Physics, and Mr Madorski for Government.  The idea that every kid could have his kind of transformative relationship with teachers, not just as the exception but as the rule, could easily be more impactful then the AI-powered instruction itself.

The bottom line for me, as a parent of a six-year-old who just finished Montessori kindergarten and a four-year-old that starts in the fall, is simply that I'm thrilled that the AI revolution is coming to education before my kids have had to endure much time in the one-size-fits-all, lecture-based classroom model that's dominated education since the Industrial Revolution, and I look forward to seeing how the combination of AI instruction and human mentorship helps them learn and develop at a rate, and in ways, that our generation could only have dreamed of.  This, it seems to me, is one of the most exciting upsides of the Cognitive Revolution.

With that, I hope you enjoy this fascinating exploration of the AI revolution in education, with MacKenzie Price, founder of Alpha School and 2 Hour Learning.

Main Episode

Nathan Labenz: Mackenzie Price, co-founder of AlphaSchool and 2 Hour Learning, welcome to The Cognitive Revolution.

MacKenzie Price: Thank you, Nathan, I'm so excited to be here. I love anything cognitive, and revolutions are great, especially when it comes to education, so I'm in.

Nathan Labenz: Yeah. The AI revolution is coming to everything and education, as you're demonstrating, is no exception.

MacKenzie Price: And so needed, right? So needed. It's time for education to change. So yeah, this is great.

Nathan Labenz: Yeah, no doubt. I'm excited for multiple reasons. I am always interested in the intersection of AI and anything, and regular listeners will know I'm also a parent. It's the first day of summer vacation here. My six-year-old just finished his Montessori kindergarten, my four-year-old is excited because the next time his big brother goes to school, he gets to go too.

MacKenzie Price: He's going to school. Very fun.

Nathan Labenz: And now I'm going to be worried about the two-year-old who's going to be home by himself, and that's going to be quite an adjustment come fall, but we all have these seasons in life.

MacKenzie Price: One of the things I've been saying, Nathan, there has never been a more exciting time to be a five-year-old, especially with what's happening in education and how much we're going to see it change in the next 10 years. Your kids are so lucky. My daughters are 17 and 19, and I so wish that I could shrink them back and start their education journey over, because there's just so much exciting things that are going to happen. I think we're going to really see that change that we've needed to see in education for the last couple of hundred years is finally going to be a realization.

Nathan Labenz: Yeah. I share that sentiment. It seems like a tough time to be somebody who's in college or graduating from college or just entering the job market. But the world, assuming everything goes reasonably well, not something I take for granted, but putting the positive hat on for this conversation at least, I think education will likely go very well. It's other things I'm more concerned about.

MacKenzie Price: It totally is. Well, and you think about higher ed and the state of higher ed, I've had a lot of university presidents that I've been in conversation with in the last couple of months who are just realizing, "What do we do now that the half-life of knowledge is, what, six months?" In the age of AI, what is it that we're doing to equip these people? I talked to, I've got a daughter who's in college herself, and we had the conversation this last weekend around if she's interested in law or consulting or whatever she's doing, she has to be AI first. That is the key to making sure that our job skills are successful and translate. You have to figure out how to use AI to give superpowers, and that's what we actually teach our students. Literally starting in kindergarten, we teach our kids how they can use AI tools to give them superpowers and be able to focus on what I always consider the gray frontier, right? AI is really good at knowing the black and white of existing knowledge, and where humans are going to need to be successful is they need to be out on the frontier pioneering new knowledge and new ways of thinking. That's what we're trying to equip our young people to go do.

Nathan Labenz: Perfect. Well, let's take it from the top. I've often quipped, but I don't know a lot about this, that AI could enable the Two Sigma For All era in education. Can you unpack that Two Sigma effect and just give us a state of current understanding of what really matters, what really drives outcomes in education, and just set the stage for then what you're building toward that goal?

MacKenzie Price: Absolutely. Well, I'm going to start by answering that question by going way back. I'm going to go back 1,000 years to think about Socrates, who was tutoring Plato, who was tutoring Aristotle, who tutored Alexander the Great, who took over most of the known world by the time he was 22 years old. Back then, we had a one-to-one mastery-based tutoring system, and of course, it was only saved for the very, very elite, right? For royalty and the intellectual elite of that time. But that was a rich environment. We think about the Socratic method of discussion and how people could go deep into a topic and become experts. Then a couple of hundred years ago, with the start of the Industrial Revolution, we had to figure out how to educate the masses and how to do it inexpensively, right? That was really the birth of the teacher in front of the classroom model, and that's what we've been doing for the last couple of hundred years. Now, for the last 40 years, since I was an elementary school student, there have been learning science research papers that talk about how kids can learn two, five, 10 times faster. And every single one of those papers refers to that being able to be done in a one-to-one mastery-based model. So when you think about the Two Sigma, Bloom had his Two Sigma taxonomy, which is basically showing you could get Two Sigma improvement in learning when you had this one-to-one mastery-based level. Now, every single one of those research papers starts or ends with, "Unfortunately, these types of results are not possible in the teacher in front of the classroom, time-based model where every kid goes at the same pace." A teacher takes a group of fifth graders who are wildly different levels of knowledge, and starting in August and ending in May has to figure out how to teach fifth grade curriculum to kids, some of whom already know the material and sit there bored and disengaged, others who don't even know their fourth or third or second grade material and are lost. So that's fundamentally what we're looking at is how do you incorporate these learning science principles into a classroom? It's not been possible, but that's what's incredible about artificial intelligence. When AI has come out, it is finally the tool that is going to allow us to provide precise and specific, not only measurement of what a student knows and what a student doesn't know, but it's also going to be able to create those personalized lesson plans that allow us to meet every single kid in that one-to-one tutoring experience where they have truly an expert that's able to go with them at the pace and level of education that they need. And we're also able to do it to mastery so that a kid doesn't move forward until they have full mastery knowledge of that. So when you think about when the microscope was invented and what that did for biology, or the telescope and what that did for physics, we have such an awesome opportunity now that artificial intelligence is going to be that tool that allows us to take learning science and turn it from this sort of fuzzy, unclear, depends on the teacher, depends on the kid, depends on the environment, depends on what's going on at home, all these things. It's finally going to allow us to create learning science as a precise science with clear inputs and clear outputs, and give us those results. And that's what is so exciting. Add to that the fact that it's scalable and that it can be accessible for any and all kids, no matter where they come to it. So that's what gets me up out of bed every day. This is finally the chance that we have to truly bring education and great outcomes for all students.

Nathan Labenz: I love that you brought up the Alexander the Great thing. I was going to bring it up if you didn't. I wonder if you could unpack a little bit what exactly Two Sigma means. I understand that it's two standard deviations, right, the measure. So, in a sense, we're saying that we could take the average student and bring their performance up to, if my recollection is right, basically the top 5% of students?

MacKenzie Price: Yes. You can get really phenomenal results. It's funny. I'll just give you a little bit of my history. I was pretty good in school, but I actually hated school growing up. I was always that kid who would raise my hand and say, "Why do I need to know this? I promise you, I'm not going to be doing anything that requires me to understand major details of chemistry, physics, calculus, or anything like that." It's funny because even my math is a little shaky when we look at this. But fundamentally, what we're looking at is this: when we put kids in a one-to-one environment where we're going at the pace that they need and we're providing the level of material that they need, that's where you can see these phenomenal results. Now, Bloom's Two Sigma problem is one that many people who get into learning research will pick apart and say, "That depends on the audience, where they took them, and how they measure this." Let me tell you practically what we do and how we're getting the results that we're getting, where our kids are learning. We just got our results from the '24-'25 academic school year; we're at 2.3 times learning. The way we measure that is we use something called the NWEA MAP assessment. MAP is a test given to about 10 million students in the United States. It includes public school, private school, and homeschool kids. It's an adaptive test that moves along with the child, constantly figuring out their knowledge, as opposed to some state tests where they just test you on a certain level of curriculum and you get a percentage. So, there's something called a RIT score, which is basically the score for performance in math, reading, language, and science. As part of that, depending on a child's percentile, score, and age, they're able to say, "We anticipate that this child will grow at this trajectory." So they might say, "For a student who is in the 85th percentile in math, we expect the student to go up four points in a given year." The results that we hold at our schools is that that student will go up twice the amount that's projected on MAPs. For example, if that student is supposed to go up four points in a traditional setting, we're going to deliver an eight-point increase. What we've found works is that we can take a child, no matter where they are when they come to us—whether in the 10th percentile or the 98th percentile—and deliver a personalized learning experience that meets their needs and fills in any gaps they have. When you see those results, we can see children going up multiple grades in a year. This is another example of practical knowledge. Take a math curriculum, for example, fifth-grade math. Generally, in a traditional school, you spend about 180 days a year in school. You may have a little homework. So children are spending probably 200 hours minimum doing something like fifth-grade math. What we found is that you can complete fifth-grade math in about 20 to 30 hours. Isn't that incredible? This really highlights the benefit of one-to-one learning, where children are going at their own pace. You eliminate so much of the inefficiency of a typical classroom experience. First of all, those 180 hours are not all spent learning new material. The other thing is the quality of engagement we're able to deliver when a child receives that one-to-one mastery tutoring experience is so much higher than sitting in a classroom, watching a teacher deliver a certain amount of information over time. Sometimes, one of the responses we get to our results—and we like to be very open with the results we're getting—is that people are incredulous. They say, "That can't be possible. And you're only doing it in two hours a day. How is that possible?" But the bigger question is, when we look back at how inefficient the time-based classroom is, it's a joke. That's why only a third of our students in the United States are reading or doing math at grade level. The problem gets more compounded as students become more varied in their knowledge. I look at teachers who are doing this most impossible job. How is a teacher supposed to take a group of 20, 25, or 30 children who are all at such different levels and be expected to get them all through the curriculum, plus possibly fill gaps or challenge those who need more advanced information? It's a very sad state of affairs when you look at how the current education system is structured. One of the things I focus a lot of my energy on is helping people understand that when artificial intelligence comes on the scene, the answer isn't going to be through a chatbot on every child's computer, or having the teacher use the chatbot for some extra lesson planning. It really allows us to finally disrupt that teacher-in-front-of-the-classroom model and move teachers into a role where they can have a much larger impact, which for us, we believe is motivational and emotional support and mentorship.

Nathan Labenz: There's a lot there. There are a number of huge themes. In terms of guiding people to understand what's possible with AI, I always come back to a couple things you highlighted. One is making things scalable that weren't previously scalable. In business, we would always like to be doing more prospecting. We can almost never do enough of that. We would always like to be doing more recruiting, but can never do enough of that. How many business leaders are doing as much as they ideally aspire to? Almost none. So, making things scalable that aren't previously scalable. I usually frame this in terms of cost savings more than time savings, but that 90% savings is another thing I steer people toward expecting. If you implement a good AI process for whatever process you're trying to get AI to take over, 90% savings is usually what I would coach people to expect. It's interesting that this also translates to how much faster people can learn. That doesn't come as a huge surprise to me, but it is still a striking result.

MacKenzie Price: Homeschool parents have known this for a long time: it doesn't take six hours of sitting in class a day for a student to not just do academics, but actually excel in them. That's the other fundamental thing with our model: we're giving kids back their most valuable resource, which is time, to go do other things. When you walk into one of our schools, we tell the kids, "Here's what we're going to do. We're going to spend two hours of what we call productive struggle, two hours of focused time, focusing on core subjects. Then, starting at noon, you're free to go work on really interesting projects, activities, and group things." What we talk about is learning life skills. That's a whole other section. What we're doing is providing the motivation for a student to say, "I will put my 25 minutes into each subject of focused energy, and then that frees up my afternoons to go work on these interesting projects." There's a whole other component to motivation, which our teachers focus on. Frankly, Nathan, that is the challenge with the majority of students in our world: if you don't have a motivated student, then there isn't going to be a lot of learning. Unfortunately, in the traditional system, there's absolutely no focus put into that aspect, which is motivation.

Nathan Labenz: Talk about things that are hard to scale. Another one of my quips is, there's never been a better time to be a motivated learner. I feel that when I'm motivated to learn something, it's very obvious that AI can teach me extremely well in many cases. I've been using it mostly for biology lately. Let's come back to the motivation and the afternoon in a minute. I'd love to go a bit deeper, quite a bit deeper actually, on the AI-assisted learning experience. Everybody in our audience has used ChatGPT, of course, and Claude, and probably Gemini, especially now that they've got competitive models and lots of other products. They probably haven't used anything like what you're describing. I personally have used Khan Academy and a couple other more educationally framed experiences, but what is the experience like? You said it's not just putting a chatbot on there. That works for me because I'm motivated. What is the experience? How would you describe it for the kids? By the way, your comment earlier on the difficulty of measuring is another classic theme in AI. My company Waymark does creative work for small businesses. Good luck measuring that, right? It's all about taste and what somebody likes versus another; there's no ground truth. There isn't even necessarily agreement. But we can all agree that it's far better to have the AI spit out a decent first draft for you, and in many cases, better than what our users used to do on their own. So I'm definitely sold that sometimes these things can be hard to measure, and the qualitative experience often matters most in the end. So, tell us about the qualitative experience. What's the UI like? What's the experience like? Are there personas? Is this still structured in terms of courses with lessons?

MacKenzie Price: Let me explain that, because people always want to know about this AI tutor. We get a lot of news headlines saying, "This is the school with no teachers. They have an AI tutor running the show." Let me give you the experience of what this is like for a student going through this. First of all, when you think about the components of AI, the one most people think of is the chat interface, right? When I go to ChatGPT and ask for help, for example, I was just filming a script this morning and asked ChatGPT, "Look at this script and give me a better ending." That's the kind of thing. That's actually the component we do not use. If you go to one of our students at one of our schools and say, "Tell me about your AI tutor," they're not going to say, "Oh yeah, this little cartoon figure pops up and it starts teaching me about math." We don't use that, and here's the reason. If you give a kid a chatbot interface, generally it's going to be used to cheat, right? We would love the idea that they engage in Socratic discussion with this chat feature, and maybe that's what you're doing when you said you're doing this with biology. But unfortunately, most of the time kids are like, "Copy, paste, what's the answer? And I'm putting it in," or, "Write this essay for me." So that's one feature we do not use. We're using common core curriculum, K through eight common core, and at the high school level, advanced placement curriculum. Our students are learning the same curriculum that kids in a traditional school environment use. We're not having an LLM generate lesson plans. We're taking the existing curriculum. We're using adaptive apps, things like Alex, IXL, Grammarly, Egged On, and many apps we've built ourselves: Alpha Math, AlphaRead, AlphaWrite. We have another reading program called Teach Tales, which we can discuss. Our kids are using these adaptive apps. However, when they log into what we call Dash, which is our AI tutor learning platform, they log in and say, "Okay, it's time to do math." We take that child to exactly the lesson they need to learn within whichever adaptive app the AI tutor has determined is appropriate for them. When you think about adaptive apps, not all apps are equal at all grade levels or all subjects. Part of what we've done over the last 11 years is curate which curriculums and apps are best for teaching different subjects, whether that's math, reading, science, or language. This includes reading comprehension. Unlike in a traditional app world, take IXL as an example. If you hand a kid IXL on a tablet, they might say, "I want to go play on this lesson. I'm going to do a little bit of this lesson, then I'm going to back out of it when it starts getting hard and jump to this lesson." Our experience curates what a kid is able to work on, ensuring they're always working at their appropriate level. Then, our AI tutor, in the background, analyzes how accurately and quickly a child moves through any specific lesson. It can then provide coaching to a student, saying, "We notice that your level of accuracy is a little low here, and we see that it's because you're not taking time to read the explanation when you get an answer wrong. You're skipping to the next question, so we're going to slow down." Or, "We're noticing that your accuracy level is a little low here. You're taking time to read it, but you're still challenged. We realize we need to go back and revisit a previous lesson to make sure you have the required knowledge to be successful in this subject." So what it's really doing is providing a very curated experience to ensure a child learns the curriculum level they need at the pace that works for them, then putting them in what we call the zone of proximal development. This is the idea of a learner's sweet spot, where they're challenged at the right level, not overworked, not unsupported, and able to progress. The other thing we look at is cognitive load theory. These are many learning science principles that we can now finally incorporate into a student's learning experience. Cognitive load theory basically talks about the amount of information we can put in someone's working memory for them to process at any given time. Basically, working memory is what I can put into my head and still manage. If my working memory gets overloaded, I will start short-circuiting. I won't understand. One of the great things about this personalized learning experience is we can say, "These are the number of concepts a child can learn," and if they start to get overwhelmed, they'll go out of their zone of proximal development where it's too hard, and we take it down. On the other hand, a kid who can learn material quickly needs to progress quickly. I'll give you another example. Let's say it takes you, Nathan, five repetitions of a concept to understand it. You shouldn't have to sit through 10 repetitions if you understood it after five. For me, maybe it takes 15 repetitions to understand something. I shouldn't only get 10. That's the other aspect of this personalized AI tutor. If you ask a kid, "Tell me about your AI tutor," they're going to say, "I go into my dashboard. I go to my subject that I'm going to be working on," which is 25 minutes of whatever core subject. It takes me to the adaptive app that is right for what I'm doing, and then I go through the questions. They're doing everything from video, reading, audio support; they're engaged in different things, writing notes on paper. Our AI tutor continues building out personalized lessons for where that kid is. It also gives the student, teacher, and parent the ability to see daily how much material a student has worked through and how long it's taking them to get through certain lessons. If it's taking longer than it should, what do we need to do to coach them, or what challenge is the kid having? What we're doing is teaching the kid the skill of learning. How do they gather resources to learn something? Another question people often ask is, "If a kid gets stuck on something they're not understanding, what do they do?" Let's say they're trying to learn a concept. The AI tutor will give a couple of different examples or explanations, maybe suggesting they watch a video or read an explanation. If you're still struggling, go into this resource library and see other explanations that have helped students who struggled with this problem. It will also say, "Let's go back and revisit something." For example, if a kid is struggling with fractions, the AI tutor will say, "We need to go back and revisit the multiplication table." That's another concept called spaced repetition, where we're constantly quizzing kids on material they've learned in the past. In a traditional classroom, you learn material and may never see it again, hoping you remember it. So that's what that experience looks like. The other aspect of AI that we're using is the vision model. We analyze how a student is working through the material. For example, when we provide coaching, the AI tutor will say, "You're not spending enough time reading an explanation, and here are examples of that." We can literally go back and show them the recording of when they were looking at a question, got it wrong, an explanation popped up, and they moved right to the next question. What can you do? What we find is that this really helps kids take ownership of their learning experience. Instead of being reactive passengers who show up in a classroom, sit, and listen to a teacher talk, these kids are learning, "If I take time to understand this now, it actually helps me go faster and more efficiently through remaining lessons."

Nathan Labenz: One high-level question is, you started this school a number of years ago. AI was nowhere near where it is today, so you've had a chance to ride this technology wave and obviously been aggressive early adopters of the technology. How has this changed? You could take that in any number of directions, but I pinged a friend who's in the education tech and education science space, and he said one huge challenge generally has been that any assessment begs the question of relative to what. We landed on the idea that longitudinal helps a lot, because if you can compare a kid to their past self, that's much better than to some abstract aggregate statistic. It strikes me as interesting. How would I build an AI product to do that? The easy thing to do now is with Gemini 2.5 Pro in particular, and a million tokens of context, I could just gather up a bunch of stuff that the student has done over the last two months perhaps and say, "Here's everything this kid has done over the last two months. Assess it on these dimensions." I honestly think that would work pretty well these days. But you didn't have that for a long time. Could you describe the evolution of how you were doing these things, or to the degree you were pre-AI, then what early AI unlocked, and how the latest advances are starting to change how you're doing these?

MacKenzie Price: Absolutely. There's a huge difference in how what we're doing has evolved, especially over the last three years. When I started the first school in 2014, I started it when my girls were going into third grade and first grade. The reason I started the school was because I was frustrated with the lack of ability for my kids to get time in a traditional environment to dig into things they were interested in and also receive that level of knowledge. As an example, both my girls went into kindergarten already being able to read chapter books, yet they would sit in their kindergarten class and the teacher would be talking about how A sounds like "ah" or "A" and B sounds like "Buh." And that was just difficult. This is not the teacher's fault; it's a model issue. You have a classroom of kids and you have to take the lowest common denominator and say, "We're going to start with assuming you've never seen the alphabet before." When I started in 2014, there were apps on the market. Khan Academy was already out there. Alex was out there. There were quite a few different apps used. We knew that we could use adaptive apps that would allow kids to jump in at the level they were at. So, when my third grade daughter started at the school, she didn't have to sit and do third grade content. She could work her way up and do fourth, fifth, sixth grade content. Here was the problem with those apps: kids could really bounce around a lot. You could be doing, "I'm going to work on some geometric patterns and shaping," and then as soon as the questions got hard, a kid could hop out of that and go work on something else. We call them anti-patterns, which are things like topic shopping or not even engaging in the app. A kid could certainly just sit on a computer and do one question every 15 minutes. That would be inefficient. The other thing we found is that when we first started the school, we were letting kids be in charge of where their learning took them. One of the moments when we realized, "We need to put some guard rails up," we had a first grade student. He loved math. He was obsessed with math, and he just wanted to do math all the time. But he got to the point where he was doing eighth grade level math, and he needed somebody to read the word problems to him because he couldn't read. That's when we realized, "This kid is not going to spend time reading on his own. We have to make sure we do something." So one of the things that came out pretty early was we incorporated the Pomodoro Technique of 25 minutes of focused attention in each of the core subjects each day. Many alternative education schools will say, "If a kid doesn't want to focus on reading for a few months, no problem. If they want to go deep in math or something else, that's fine." We took a different approach, which is making sure that students are spending time in each of the core subjects every day and moving along that level. But there was quite a bit of inefficiency, and kids could mess around. In 2022, that's when we really saw the power of AI coming out and realizing, "We can now use this as a measurement tool. We can use this as an analysis tool to build lesson plans that ensure a student is learning in a linear fashion the material they need to learn, and to go back and fill holes for material they don't know." This is where assessments come in. We can take assessments, standardized assessments, which in a traditional environment are pointless and have gotten a bad rap. The reason is because nothing really changes for a child based on how they do on a standardized assessment. Maybe the school gets a grade on how they're doing, but nothing changes for the student. In our world, we can take an assessment for a student and feed that back into our AI tutor. We build an updated lesson plan that says, "Let's go back and revisit these concepts in each of these different subjects and grow from there." One of the things we saw a big difference in was from the school year of 2021-2022 to 2022-2023. When we incorporated this AI tutor and personalized learning system and made a couple of other changes, that's when we saw our learning rates go from 1.5 to 2 plus. That has been a huge difference. If you look at our graphs of learning rates over the last several years, there was a major step change when we incorporated AI to ensure we were providing the right level and pace of material, and that we were making sure kids weren't wasting time or that their focus was right. The other big part of that, which didn't have to do with AI, is that there was a time when we were thinking, "Maybe there's a world where we're still having teachers do some academic teaching." The big change we made in the fall of 2022 was that we said, "We're going to do no academic teaching. We are going to allow the AI tutors to do all of the academic teaching." What we found was when we got out of that hybrid environment, we had learning rates just go crazy. That's been the big change that happened in the last three years. The other key thing we'll get into in more detail is that for 15 years, ed tech has been touted as this great solution that's going to make all the difference, and it's never really worked. There are two reasons it hasn't worked. One is, I don't think if you take a kid who's in a time-based classroom, going through seventh grade math in a school year, and then three times a week you have them spend 15 minutes doing Khan Academy or some other app, that doesn't really help. It just puts the kid back in that same time-based system, and often that 15 minutes on an app isn't time well used. So I do not advocate for the idea of handing a kid an iPad and a random app and saying, "Let me know when you've graduated high school." It doesn't work. The other key component to that is the motivation aspect, which is another part of what's made our model work.

Nathan Labenz: In the 2022 timeframe, in language model terms, that would have been like GPT-3. Were you using language models at that time to process assessments and design curriculum?

MacKenzie Price: Yes, we started early and haven't partnered with any particular LLM. We've been using Alpha as our testing ground to see what the latest and greatest is when it comes to LLMs. I believe when we get into scaling and making this more affordable, there will likely be solutions where you can use LLMs that have become less expensive. We spend a lot of money on the data and analysis we use, and the vision model. Understanding how a child works through a problem gives us the data we need to understand how children generally approach this, how much time it should take to complete a lesson, and then troubleshoot if it's taking a child longer. Is it because they weren't engaging with the computer, or because they weren't reading the question, or watching the video, or whatever that part was? We haven't partnered with anyone up to this point and are constantly testing that out. That's part of the reason it's expensive right now; we're using a lot of AI. I think over time, and I truly believe in the next five years, we'll reach a point where every child can have a tablet for $1000 a year that will allow them to learn all their information. I'm excited for where that leads. I think it's sooner than we think in terms of bringing costs down and what AI is doing for that, allowing us to collect so much information on how students learn, which we'll continue building into our system.

Nathan Labenz: Yes, there's no doubt the cost curve is extremely favorable. Sam Altman just said in the last 24 hours or so that the typical ChatGPT query consumes about a third of a watt-hour of energy, which, at least in my jurisdiction with the electricity rates I pay, is a few hundredths of a cent. So, the fundamental costs when operating at scale are already quite low, and there are forecasts that they will continue to get lower, at least given a fixed level of intelligence in the models you need for most of this stuff.

Nathan Labenz: We have those levels of models today. So the cost will definitely...

MacKenzie Price: The other thing that's going to happen, yes, the cost will go down. The other thing that's going to happen, and we're still in the early phases of this, is for example, we have an app called Teach Tales. It's something anyone can use. It allows us to create reading comprehension at a child's proper reading level, incorporating their interests. That's one of the exciting things about generative AI: being able to take a student's knowledge graph and overlay it with their interest graph. We already do that with some reading comprehension, but that will get even better as we're able to say, "Let's learn math and relate it to baseball statistics or fashion design," incorporating those things. We're just at the beginning of the ability we'll have as AI gets better at generating curriculum that doesn't have hallucinations. We haven't really been focusing on that part because there have been issues with accuracy. If you ask for a fifth-grade math curriculum, you'll get some mistakes. But that's getting better, allowing us to do a lot more with student engagement and learning. We can already do that from a reading comprehension perspective. Kids can give their opinions, like, "I thought that was interesting and I want more articles like this," or more reading examples like this, which is really helpful. That part of engagement and connecting with a child is another learning science principle: the more knowledge you have, the better you can draw on analogies. That's what allows us to create even more exponential learning experiences where kids can quickly grasp something they already know and relate it to a new concept they're learning. That's only going to get better with AI over the next months and years. It's also one of the things, Nathan, that when parents consider putting their child in our schools, we tell them, "The only constant is change." We are constantly rolling out updates to our apps and our learning system. Then we look at the data we have, the measurement data. For example, in January 2025, our MAP report came out because our students take MAP assessments three times a year. In January, we saw our classes were 99th percentile across the board in every grade, every subject, except fifth-grade math, where we were 93rd percentile. Our academic team was able to jump in and say, "Okay, what's going on in fifth-grade math? We obviously have some sort of curriculum issue or something is causing us not to perform as well there." We can go in and troubleshoot. That's where I think AI is giving us precise measurement and assessment, doing it in a more pure environment than a traditional classroom where you might wonder, "Was it a bad teacher? Was it bad curriculum? Were the kids not doing anything during school?" Here, we can truly see all the different inputs and more accurately analyze the output measure and how we can improve it.

Nathan Labenz: Can you share the big reveal? What did you ultimately find when you got into that fifth grade math?

MacKenzie Price: That's a good question. We realized a couple of things. There are a few different apps out there. For example, there's an app called Math Academy. Math Academy is a great math app for advanced kids and those who really like math. It doesn't work as well for the average student who is just getting through math, or who doesn't really love math. That's an example of something we found. While not specific to fifth grade, we've realized that about 25% of our students really like learning with Math Academy. The majority of our students use Alpha Math or IXL for lessons. Sometimes it's realizing an app isn't right. Another thing we've seen is that you can measure something called DOK, Depth of Knowledge. How deeply does an app teach a student in a subject, and are they getting the right level? We had an SAT blitz for our high school students this fall. One of the apps we were using was good for Depth of Knowledge levels one and two, but didn't go deep enough into three and four. We gave feedback to that app company, and they rolled out a new version. That's what's really exciting about innovation in ed tech. I think it's why many app companies like Alpha, because they're getting so much data on how students use their products. This data isn't skewed by unknown classroom activities or curriculum. It truly shows how kids are learning the material and how they are performing. That's where I now have an academic team of psychometricians who are literally figuring out the best ways to help kids learn, applying both learning science principles and actual curriculum design. LLMs and AI in general will get much better at delivering customized content that meets a student where they are and provides things that help with engagement. To be clear, we're already seeing this in certain areas. Our high school students are taking their AP courses, and our students created catchy songs, even a soundtrack, to help them study for AP US History. It was like an updated Hamilton soundtrack, fed by AI. I remember my daughter, when she was taking AP art history, singing a song with the melody of a Taylor Swift song to memorize her canons. That's another example of how we're teaching our kids academics by leveraging the power of AI in the morning, but not to cheat. In the afternoons, our kids learn how to use AI tools to give them superpowers. This includes our high school students creating songs to help them memorize material for their AP tests. It's a lot of fun. It's fun to hear,

Nathan Labenz: Somewhere at my parents' house, I believe there's still a VHS tape from my AP History course with my rendition of Stonewall Jackson's Way, which hopefully won't ever appear on the internet. As you envision the future of this personalization, it seems like I'm not clear whether you are sticking to Common Core and doing these standard assessments because you need them, because you think they're a good true north, or because you need them for legitimacy. But it strikes me that in the not-too-distant future, it's plausible to think that all this might dissolve, and at the end of a day, week, month, or year, you might not even need a test. Or you might not even need a highly structured segmentation between subjects. Is there a more organic future form factor to all this that you can envision, or does that seem too fanciful?

MacKenzie Price: I don't know if I'll fully answer your question, but one thing that has happened in alternative education is a movement away from traditional academics and academic knowledge. Often, you'll hear,

Nathan Labenz: What about modalities? Another big trend in AI has been toward multimodal. AIs can now see, hear, talk, and generate images. How multimodal is the experience today, and where do you think that is going? It's one thing to sit through forced corporate training. That's been my most recent ed tech experience, and you're just clicking. I can relate to the kids. We're just trying to click through and get to the end as fast as possible. There are schools of thought that it is important to write by hand and something is lost if you're on a keyboard. I'm not sure if I fully buy that. You might have a stronger point of view. Are the kids talking to the AI? Is the AI talking back? Are you reading their handwriting off the pages? What does the multimodal component look like today?

MacKenzie Price: That's one of the things that I think is really cool about this model of learning. There are so many different ways that kids can engage in this learning. Yes, they are able to use voice, and one of the places we think about that is reading, for example. It is so important when you are reading and learning to read that you read out loud, so we use voice reading techniques where kids read back, and then the AI can analyze how they are doing on this reading. How quickly are they reading? Where are they? Are they at the right level in what they are doing? That's everything from an app we built called Fluency Coach that we use. There's another app called Literably that's available. It's a third-party app that's used. We use these regularly for reading intervention, especially for our pre-K, kindergarten, first, and second grade students. And again, when you think about how important those fundamentals are. In third grade, you go from learning to read to reading to learn. If you are not a good reader by third grade, your academic success for the rest of your career will not be as high. So we are making sure we get those fundamentals. That's one of the things that's so cool about being able to take something like reading and have kids not only practice writing their letters, typing their letters, recognizing them, going on the screen, and matching things, but also speaking out and listening for pronunciation. We do phonics-based reading as learning. That's one of the things that's cool. We have video and auditory support. It's where we are seeing success with kids who have learning differences, like dyslexia or dysgraphia. To be clear, we are not changing the neural pathways of a child with dyslexia. There are schools that specialize in helping kids build tools and rewire their brains to work with that. We generally see that kids who are in the bottom 50th percentile of severity for that learning difference can do very well in our model. That is because they are going at the pace they need, and they are getting auditory and visual support where they need it. But that's what we do. Handwriting is another example of something that parents, especially young ones, want. I do believe tactile function is important. You have to have kids doing that. If you walk into one of our kindergarten or first grade classrooms, you will see the manipulatives they are able to use as they do math. They get these little pegs and can count and lay those out, seeing that visual representation, feeling it, and doing it. The same applies to practicing their handwriting. In our second grade classroom, I was in one of the classrooms earlier this fall, and the kids were talking about some of the independent checks they have to work on in addition to their academics. When someone asked, "What's the hardest check?" in unison, they all said cursive is so hard. Yes, we are still doing that. Will they need cursive that much in this new world? Who knows? Maybe not. But there are certain things that I think we hold onto and add. Things like writing, our students are doing writing through apps that we have online. We also use independent time for kids to practice real handwriting. I think it's important to combine a lot of those different efforts, and I think one of the things that's great about these apps and AI tools is we are able to use many different modalities to really meet kids where they are. Again, sometimes some things don't work for certain kids, and others work really well. That's the other thing: it's truly personalized learning. What works for this kid, and how can we build our lesson plan around it?

Nathan Labenz: Cool. Thank you for spending so much time and going so deep on the technology. Let's talk about the afternoon and the role of the teachers. I think you call them guides in general, right?

MacKenzie Price: We do. We call them guides, coaches, teachers. We use those words interchangeably. One of the reasons we focused on the name 'guide,' and our guides prefer that term, is because they are not teaching academic subjects. They are not subject matter experts in terms of saying, "I'm a science teacher," or "I'm the language teacher." Instead of being the sage on the stage, they are the guide on the side. Their job and function is to provide motivational and emotional support and mentorship to these students. We are a very high-standard environment. We believe kids are limitless. We believe they can be very successful academically. We believe they can do impossible things, but we also provide the high support and mentorship needed to help kids do that. Our teachers are focused on helping kids develop growth mindsets and understand their connection to putting in work and effort and getting results. That is the function. I believe we have transformed the role of the adult in the classroom to focus on what only humans are truly great at: personal connection. One of the things we often say, and we ask our students this as they get into older grades, is, "Every adult would say they have one or two teachers who changed their lives. Do you believe that your guide is that person for you?" I'd ask you that question, Nathan. Do you have a teacher or two that changed your life?

Nathan Labenz: I can certainly think of a couple, yes.

MacKenzie Price: That's generally the answer. Most people will say, 'Two teachers I had in my junior and senior year of high school, my business teacher, Mr. Blood, greatest teacher in the world, and my sixth-grade teacher, Mr. L. They were fantastic.' But then I think about how many teachers I had in my career, and some of them were not good. Some of them were not. What we're doing is we literally hold our teachers accountable to delivering our three commitments that we have for our students, which is that they'll love school, they'll learn twice as fast in two hours, and that they will develop life skills. For example, when we think about learning 2X in two hours, we are handling the part of giving them the correct lesson plans that they go at their pace. The other key aspect is motivation. If a kid isn't motivated to learn, we're going to really struggle. What our teachers do is they spend their time getting to know every single kid and having the time to understand, 'This is the thing that motivates this child.' That can be everything from external rewards. For example, we pay our kids. They earn school currency for getting their work done, to privileges, being able to sit where they want when they hit their goals. They're able to have more autonomy over their space, to getting to bring in Chick-fil-A lunch, to being able to earn a trip to the zoo or whatever it is. We do all kinds of different things to motivate our kids. An example that I love: we had a student who would often find himself distracted. He was quite often staring out the window when he should have been working on his different apps. His teacher had enough experience and knowledge to know that often when he was looking out the window, it was because he loves birds. He's super obsessed with ornithology. So she and the student spent some time coming up with a big poster board of all the different birds that are in our Austin area Green Belt, and then when he would hit his goals on a weekly basis, that would earn him 15 minutes of time with his guide to go out into our Green Belt and do bird watching and go find all these birds. That was the connection that child needed to say, 'I want to focus on getting my goals done because I get to go earn time to bird watch.' We do a lot of different things, but if you were telling me, 'MacKenzie, you're in charge of K through 12 public education starting tomorrow,' what would you do for motivation? I think one thing you could do is have kids say, 'You can focus on your academics in the morning, and then you get your afternoons back to go do the things you love to do.' Often, the things kids like to do are what they usually start doing at about 3:00, such as football, basketball, theater, robotics class, speech and debate club, or dance. Whatever it is, you can figure out what a kid enjoys spending their time on and give them that time back. What we generally find is that many kids say, 'I'll take that focused time in the two hours to get time to go do these really fun, interesting things.' Unfortunately, in the traditional model, kids who do well usually base it on two things: intelligence (IQ) and their willingness to be conscientious and do the work. Are they willing to turn in their homework? Are they willing to study for the tests? So if a kid is not doing well in a traditional school experience, it is usually considered the kid's fault. It's like, 'He's not the smartest kid in the world,' or 'he's lazy,' or 'he's disengaged,' or 'he just doesn't want to do it.' In our school, if a kid is not thriving, then it's our fault. In fact, we just finished our staff days at the end of the school year on Monday and Tuesday, where we went through every single student and asked, 'Are we delivering these three commitments? If not, what are we doing to fix it? What do we need to change in the input to connect that motivation?' I think it turns the model on its head. Then, for our teachers, it's a much more fulfilling job because they have the time and ability to get to know each kid and understand what makes them tick, as opposed to trying to figure out how to teach curriculum to 20-plus kids.

Nathan Labenz: Speaking of jobs, how do you hire differently? Do you care about education degrees? What advice would you give to people if they want to be a guide at one of your schools? More broadly, there's a notion that we've gone from physical labor to intellectual labor, and perhaps the next big thing could be caring or the caring economy. Is that the vibe you're going for? What do people need to know?

MacKenzie Price: When we think about the people working in our classrooms, our guides, our teachers, I would say probably 15% of them come from a traditional teaching background, especially at the younger grade levels. I really believe teachers working in classrooms today are absolute heroes. So people who have said, 'I want to go and spend my time with five-, six-, seven-, and eight-year-olds. That's who I want in class.' We find we get many traditional teachers coming to those lower levels, but a much greater majority of people we've attracted love the idea of education and helping people, but they perhaps were not willing to go into a traditional school experience because they think, 'That doesn't work,' or it's just not where they want to spend their time. They don't see it as being fruitful. So they are drawn to this idea of providing expertise and motivation, connecting with students, and helping students figure out what they are interested in, saying, 'Let's go learn about that together. Let's figure out how to do that.' What we're looking for is really smart adults who are sharp and quick. Kids are so underrated in our society today. We want adults who understand that kids are so capable and truly amazing. Given that support and resources, they can do incredible things. So we're looking for people who buy into that and who have shown excellence in some form of motivation. We get people who come from entrepreneurial backgrounds. We get people who were ex-professional and college-level athletes and coaches. That's where we've found a lot of success, with people who come in and know how to create the motivation that sports often provides. We get people who have come from executive jobs, doing different work in the real world, and we find that creates something. We are hiring extensively. That's on our guide side. We're also hiring people on our tech side. We need people who are continuing to build these apps, continuing to learn how we can incorporate learning science principles to develop even better learning results. We do all of that through Crossover.com. The other thing is, we are big fans of paying people well. I believe that people who choose to dedicate their lives to helping young people in education deserve to be well-compensated. Our guides start at 100 grand a year and go from there. As a result, we attract people who are excited about coming in and making a big difference. One thing that is different for us is we judge our teachers on how they are delivering these commitments to our students. If they are not motivating students well, then they are not going to be long for this job. Someone was telling me the other day, 'I don't think there's a guide union in your schools.' You're never going to have that old battle-axe teacher that nobody likes but is still around. If the teacher is not doing a good job connecting with students, then they are not going to be long for this world. So we are looking for people who are willing to get in it with kids and truly engage. It's very common that you'll hear our kids talk about how during breaks and recess, they love that their guides are out playing football with them, playing basketball, and running around on the playground. They very much roll up their sleeves and get in it with the kids, and that's what makes them so fun. Again, to be clear, it is all attributed to our teachers, our guides, that we are seeing this success and this model. I think we've finally equipped them to be extremely impactful by providing the learning platform that allows them to deliver academics in a shorter period of time and much better. But we are by no means the school with no adults in the classroom. Our adults are able to spend their time in a truly impactful way.

Nathan Labenz: That's cool. Running around on the playground is what I like to do most with my kids. Let's talk about economics, ratios, and scalability, and your theory of change. Obviously, you can only start so many schools. I did notice there's a default price point of $40,000 a year tuition, but there's also a $10,000 a year price point in Brownsville, Texas. I don't know if that reflects a cross-subsidy or whatever, but can you give us a sense for the economics, how you see this? What is the vision? Maybe you want to start a million schools, but more likely, there has to be some mechanism for transfer from the learning you're doing, the evolution of education you're pioneering, to the public schools that most kids will presumably continue to attend.

MacKenzie Price: Absolutely. Most people have heard of our flagship school, Alpha School. At Alpha, we are redefining what parents expect from a child's private school experience. We are a high-end private school. Our tuition generally ranges between $40,000 and $65,000 a year depending on the city. Brownsville is an interesting example. We wanted to come to that community. Brownsville has one of the poorest school districts in the country. It has challenging educational options. They needed a lot of help, and we wanted to be a resource for the community. It was also an interesting place for us to cut our teeth, because about half of the students in our Brownsville school are children of SpaceX employees, and about half are from the local community. We had a lot of diversity: socioeconomically, racially, and English as a second language. What we've shown is that those students—in fact, our campus in Brownsville consistently outperforms our other campuses—when it comes to their learning rates. So I think it's been a great example of showing why a personalized learning platform can deliver phenomenal results no matter where a child comes to us or what their socioeconomic demographics are. It really is the great equalizer when we talk about meeting every student where they need to be. In general, Alpha spends a lot of its resources and money on life skills experiences in the afternoons, so children do incredibly cool things as part of their life skills workshops. We have other schools at lower price points. For example, we have a gifted and talented school, a sports academy, and a middle school that focuses on esports and gaming as a motivation model. Those schools are about $25,000 a year, and we're rolling out schools at a $15,000 a year price point. Again, they're all getting the same academic experience in that two-hour personalized learning platform. But what we're doing around the life skills component is a little different. We've also recently been trying to make a foray into the public world through charter schools. It's been interesting because we've had more mixed reactions. Many states have said, "No, we're not interested in letting you take your model of education into the public sphere." But we were fortunate to be approved for a virtual charter school in Arizona, and we're in the process of applying for a physical charter school in Texas. That will be exciting to give that education option to as many students as possible. I believe, especially as our cost of AI comes down, we can make this a financially reasonable option from an academic perspective. I also believe we're still committed to paying teachers well in this new model. It's really in the afternoons how we're putting things into the life skills workshops. That means in our charter schools, children may not be traveling to Poland to train Ukrainian refugee students on two-hour learning, but they can be doing sports workshops, entrepreneurial workshops, and vocational workshops as well. That's the big difference. And I'd also like to serve as an inspiration. I've had conversations with the Department of Education and the White House about how to make this style of learning more available in the public sphere. Again, Nathan, it just takes the public getting clear and understanding that this adds to education and isn't scary. Everybody thinks, "Oh my gosh," when you talk about AI in education, they imagine a robot standing in front of a classroom or kids cheating, and neither of those things are true. Actually, that's been my advice to people in the public sphere: don't put a chatbot on a computer and call it a day. Help teachers and parents understand that the role of the teacher is not to be replaced. That role will be transformed to focus on the social and emotional motivation side as opposed to the academic part. I believe we're going to get to a point where a billion children around the world will be able to take this type of education. As far as what I'm trying to do, I'm building out private schools starting in the US and eventually internationally, allowing other people to adopt our learning platform in their schools or start schools where they can have the academics. We're doing some intervention services in the public setting for children who need out-of-class support, whether remedial or advanced help. And I think there will be an influx of other innovators who come in and build things like what we're doing that will help. I spend a lot of my time and energy trying to raise awareness and be a platform for understanding what's possible if you understand that your child doesn't need to spend six hours sitting in class to do core academics, that they can crush their academics in a couple of hours a day. The other thing that I think is spreading like wildfire is how much value parents are seeing in spending a significant portion of the school day working on life skills. Financial literacy, entrepreneurship, storytelling, public speaking, leadership, teamwork, socialization, grit, and learning how to deal with failure. Those skills, I think, are what many parents say, "That's what I really want." The traditional education environment doesn't lend itself to spending time developing those skills. Hopefully, we can get more of that out. I do a lot on the future of education on social media, showing people what's possible, and again, helping them understand this isn't scary. Of course, the other component we haven't gotten into is teaching our students how to use AI tools to be successful. So, we can have our kindergarten and first-grade students who are able to create books, graphic art, movies, and things like that. They're able to code drones, robots, and self-driving cars, build video games. There are so many different things children can do when they have AI and are learning how to use it as a tool. It gets us back to the beginning of this podcast when we said the half-life of knowledge is going to be much shorter. So what children need to be successful at is knowing how to use AI tools to further their abilities. It's no longer about the three Rs of reading, writing, and arithmetic. Now it's about critical thinking, collaboration, communication, and creativity. If we can give children the knowledge they need to use these AI tools, that's going to be a huge thing. It's helping people understand that AI doesn't just mean cheating; it means growing capabilities.

Nathan Labenz: I'd love to see you come to Detroit where I live at some point. For those who are not in a spot where they can go to one of your schools and enroll today, what advice would you give me if I just want to DIY it to the best of my ability until you or somebody else has such a program?

MacKenzie Price: First of all, we have a homeschool program called Alpha Anywhere. We've spent a lot of time working on that to ensure the motivation model is built into the program, since we don't have kids in a physical building with our guides working with them. We've started seeing the results we want to roll out on a grander scale. Another thing is taking time with your kids to try out these tools. A great example for your kids at their age is inspiring a love of reading and getting better at reading by being able to do something like use our Teach Tales app. You can literally go on a website and try it, where suddenly your little boy is the main character in a choose-your-own-adventure that talks about his favorite movie with his best friends from his Little League team, delivered at the proper reading level. Suddenly your son will be like, "Let's read more. Let me do more reading." Using those AI tools helps with this. I also think there are many great tools on the internet. For example, I've always been a fan of public speaking. It's something I wanted my kids to be great at. There are many great AI tools that help kids get better at public speaking in a really unintimidating way, where they can get feedback on a talk they give. For your six-year-old, you can say, "Let's create a story and present this at dinner tonight. Then we'll use AI tools to give feedback on your intonation, how to make it more engaging, your pacing, and if you used filler words." There are many things to do. One of our students, a graduate of Alpha, just finished her freshman year at Stanford. Her name is Austin Scholar, and she writes a Substack newsletter for parents that gives them information on how to do education in this new world, what some great AI apps are, and what projects your kids can do during the summer with AI. One thing I will say, Nathan, and you're a perfect example of this because of your kids' age, is that this is where I was when they were about the same age. I was trying to build all this scaffolding alongside their traditional school experience, saying, "After school we'll do a science club, and we'll have you work on that, and we'll work on writing a book and doing all these things." Eventually, kids get busy, and parents are busy. It's like, "How much time do we have to go do an after-school science club, throw in piano lessons, and do all that?" So I really want the resource of time during the day to be something that's more accessible. I'm launching futureofeducation.net. It will be live in June, where parents can go and get free resources for using AI tools and different apps they can try. I think the biggest thing, as a parent, and I'm sure you're doing this, is to get familiar with those AI tools. One of the conversations I've been having with people in the public domain, in the administration, who are trying to figure out how to become AI-driven in education, is that many teachers aren't familiar with AI, so they don't know how to use it themselves and therefore are wary of it. As a parent, start using AI in your daily life to help you with your job, help you with everything from figuring out what you're going to cook for dinner. There are so many different ways, and there are many creative outlets that can get kids really excited about building. That's something we really want our students to do: be creators and contributors, not just consumers. AI tools allow us to be great super builders of things. There are plenty of projects that parents and kids can do together to get them excited about that.

Nathan Labenz: Cool. There are multiple pointers there that I will definitely be sure to follow, and I'll look out for the soon-to-be-launched website as well. Outstanding work. I love the vision, and yes, it is time for the future of education. I'm glad to learn that the future is now at Alpha School and with 2 Hour Learning. MacKenzie Price, thank you for being part of The Cognitive Revolution.

MacKenzie Price: Thank you for having me.