Magic School uses AI to help kids learn, not cheat | E2196

Are AI tools in the classroom just time-savers, or can they have genuine educational value? In a must-watch TWiST 500 interview, Alex chats with Magic School founder (and former principal) Adeel Khan about how AI tools can make teachers more effective, and keep students inspired, without just doing all the work for them. He talks about turning an AI chatbot into a true assistant teacher, that keeps the lessons balanced yet challenging, and particularly empowers classroom novices and non-professionals. THEN… is 6 years too long for employees to wait to vest? Is this just another founder trying to reinvent EVERYTHING, just because they can't resist? Ramp CEO Eric Glyman joins Jason and Alex to answer pressing founder questions from viewersPLUS there's a new entrant in our Gamma Pitch Deck competition, and it's so compelling, Jason can't wait to invest! Kris Canete of On the Fly Energy tells us about America's fragile power grid and his elegant solution: flywheel energy storage! Timestamps:0:00 - Welcome to TWiST!02:59 - Former principal Adeel Khan of TWiST 500's Magic School AI tells us why "teachers are magic"09:41 - Goldbelly ships America's most delicious, iconic foods nationwide! Get 20% off your first order by going to Goldbelly.com and using the promo code TWiST at checkout.10:50 - How AI tools can particularly help out classroom novices and non-pros who are just getting started20:57 - Check out the online payroll and benefits experts with software built specifically for small business and startups. Try Gusto today and get three months FREE at Gusto.com/twist.26:58 - How Magic School stays ahead of shifting standards across different states and regions32:57 - Zite is the fastest way to build *business software* with AI. Build apps, forms, websites and portals that connect to the tools you already use. Go to *zite.com/twist* to get started.33:30 - Why the best feedback Adeel ever got came from a teenager36:30 - Making AI a true assistant teacher, that keeps lessons balanced yet challenging38:38 - Is a 6-year vesting schedule too aggressive? Eric Glyman responds.41:00 - When even ambitious founders should sometimes just accept a standard deal.57:33 - What IS flywheel energy storage?01:00:00 - Why Jason loves the Fly Energy Gamma pitch and wants to invest right now.01:34:13 - Gamma Outro*Subscribe to the TWiST500 newsletter: [https://ticker.thisweekinstartups.com](https://ticker.thisweekinstartups.com/)Check out the TWIST500: [https://www.twist500.com](https://twist500.com)Subscribe to This Week in Startups on Apple: https://rb.gy/v19fcp*Follow Lon:X: https://x.com/lons*Follow Alex:X: https://x.com/alexLinkedIn: [⁠ / alexwilhelm ]( / alexwilhelm )*Follow Jason:X: / jason LinkedIn: [ / jasoncalacanis ]( / jasoncalacanis )Great TWIST interviews: [Will Guidara,]( • Lessons in Unreasonable Hospitality with W... ) [Eoghan McCabe]( • Great Builders & Success First with Interc... ), [Steve Huffman](https://podcasts.apple.com/us/podcast..., [Brian Chesky](https://podcasts.apple.com/ca/podcast..., [Bob Moesta,]( • Decoding Customer Insights, Trust, and the... ) [Aaron Levie](https://podcasts.apple.com/ca/podcast..., [Sophia Amoruso](https://podcasts.apple.com/ca/podcast..., [Reid Hoffman](https://podcasts.apple.com/ca/podcast..., [Frank Slootman](https://podcasts.apple.com/ca/podcast..., [Billy McFarland](https://podcasts.apple.com/ca/podcast...)*Check out Jason's suite of newsletters: https://substack.com/@calacanis*Follow TWiST:Twitter: / twistartups YouTube: / thisweekin Instagram: [ / thisweekinstartups ]( / thisweekinstartups )TikTok: / thisweekinstartups Substack: [https://twistartups.substack.com](

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  Hey everybody. Welcome back to Twist. This is Alex and I know you're probably just coming back from the OpenAI Browser Stream. Don't worry, we're gonna get to that tomorrow. But today on This Week in Startups, we are talking to founders. First up, Adeel Khan. He's the founder and CEO at a startup called Magic School that wants to bring AI into the classroom responsibly. Think about things like helping teachers with their lesson plans, creating more individualized setups for children that might need it, and on the student's side, AI literacy, and perhaps even getting early feedback on papers. It's a really cool idea. It's growing like a weed. And of course, yes, we do talk about privacy a little bit, and the risks of increasingly digital classrooms and what that might do to our children's brains.

• 0:44Speaker 00

  But based on all the data I can see, AI is coming to school and Magic School wants to do it well. Then after that, we're gonna take a founder question. This is a chat back from when we had Eric Gliman on the show, the CEO over at Ramp. You may have heard of it. And we thought it was a really fun one. Someone wrote in asking about how long it should be for an employee to vest their shares. Four years? Six years? Should it be different than what a CEO sees in their own pay package? Well, we dig into that and more. And then to wrap up today, perhaps our favorite ever on-screen pitch as part of our Gamma Pitch Event. This is a company that I didn't see coming, that I hadn't even thought of as an idea, but I absolutely love. And I got to learn quite a lot about material science during the conversation. So sit back, enjoy.

• 1:28Speaker 00

  We have a three-part show for you today, and each part is absolute gold. Have fun. This Week in Startups is brought to you by Goldbelly. Goldbelly ships America's most delicious iconic foods nationwide. Get 20% off your first order by using the promo code TWIST at checkout. Gusto. Check out the online payroll and benefits experts with software built specifically for small business and startups. Try Gusto today and get three months free at gusto.com/twist. And Zeit. Zeit is the fastest way to build business software with AI. Build apps, forms, websites, and portals that connect to the tools you already use. Go to zeit.com/twist and get 50% off your first project.

• 2:19Speaker 00

  AI is absolutely everywhere. It's doing great in the realm of software engineering. It's taking a big chunk out of the legal market, is showing up everywhere in the world of fintech. And one other place where AI has found an enormous footprint is in the world of education. Now, when ChatGPT came out, everyone became worried, what will we do if the students just use AI to write their assignments? Well, the picture is a bit more nuanced than that, and some people, especially entrepreneurs, are taking AI tools and bringing them to the classroom in an official context, offering tools and services for educators and students and administrators alike. And one of those companies, Magic School, seems to be doing quite well. It raised a $45 million Series B earlier this year, so I had to learn more. So please join me in welcoming to the program, it's Adeel Khan, the co-founder and CEO of Magic School.

• 3:04Speaker 00

  Hey, Adil, how you doing?

• 3:05Speaker 01

  Alex, thanks so much for having me.

• 3:06Speaker 00

  My pleasure, man. I love talking about bringing AI to places where people might not expect it to go, and also to kind of flip the narrative, because I feel like AI in education has gotten a pretty bum rap so far. And so I like the idea of taking a tool that some people are worried about and turning it into good. So let's start there. What does Magic School offer to students and then teachers and then school districts? Let's kind of go up the chart here.

• 3:30Speaker 01

  So Magic School ends up being this teacher co-pilot, so is AI for educators, where they can use it for their daily tasks, like maybe building a road break for a project they're bringing to their students, differentiating materials for students who are ahead of the curve, and students who might need additional support, English language learners, students with special education plans who might be behind grade level in certain areas of academics. So it's their co-pilot for their daily work. And then they also can craft these AI experiences. These are all teacher-led, so they have to actually build the experience themselves and then launch them to their students. These range from things like a ChatGPT for kids with garden rails, and you know, doesn't give them the answers, but helps guide them through their supportive, to support them with their academics, to more targeted personalized learning tools,

• 4:15Speaker 01

  like a writing feedback tool where students can submit essays that they've written on their own, and then get AI-aligned feedback, feedback that's aligned to a road break that the teacher's going to grade them on eventually. Areas of strength, areas of growth instantly, instead of waiting two weeks for their teacher to grade it and give them feedback, they get formative feedback before they get their final grade. It's, it's incredible. As a former English teacher, this would have been a godsend for me in my classroom. And then for districts, they end up picking up magic school because they kind of want to make their own closed sandbox version of generative AI for their teachers in their district. So they can fuse their own district knowledge with RAG technology into the platform and make sure that it's aligned to their district's priorities and

• 4:58Speaker 01

  goals and not just a generic AI that their teachers might be picking up in different ways. So they get to kind of create their own ecosystem of gen AI tools for their educators.

• 5:06Speaker 00

  So let's talk about the AI tools for teachers and helping them create rubrics and do some bits of grading or assessment and so forth. My immediate concern is, oh, Lord, the AI is going to be designing lesson plans. And you and I are both AI bulls, I believe. But I would say that the teachers that I grew up with were so experienced and so kind of in tune with students that they could certainly do a better job. So a lay for me, my concerns that feel very Luddite-ish now that I say them out loud. And maybe give me an example of a rubric that a teacher could put together with magic school that would be better or more in-depth or more flexible for students than they could do on their own.

• 5:40Speaker 01

  Yeah. So that's a great question. So one of the ways that we think about this is that, you know, the teacher is still the center of the classroom. Our slogan is teachers are magic and it's a catchy slogan, but

• 5:50Speaker 00

  I know, it's good.

• 5:51Speaker 01

  It is also kind of the E-boss of the company. We think teachers need to be in control. AI should not be the one teaching students. For the example that you shared, a rubric, the tools are set up very similarly where the teacher is asked to give very specific input into the tool before the rubric is generated. They can do things like upload their standards that they're required to teach to their students from the state level. They can do things like, you know, give additional instructions or the text that the rubric would be associated toward, or, you know, multiple things that would be associated toward. And then they could also add whatever additional instructions they would like. And they also generate, they get the rubric, they can edit it in the platform. And then more importantly, where this becomes really powerful is when you can differentiate this rubric for several different audiences in your

• 6:37Speaker 00

  Second time you said differentiate, my read of that is it means essentially creating variations of the same rubric for students that are at different levels of learning or preparedness. Is that correct?

• 6:46Speaker 01

  That's exactly right. And that is, when I was a principal, our ninth grade classrooms, our English teachers would have students who were three grade levels behind in English. We had students in the classroom who were branded the country, who were just learning English for the first time in ninth grade. Then we had students who were well beyond their grade levels expectations. And the teacher as a single person is required to differentiate or meet all of their needs at once. This was kind of like a, an imagined thing that we asked our teachers to do, but really only the most veteran teachers who had versions of their materials that they had before, they could spend maybe the next year doing it. Now you can do this in like the snap of a finger. So you take that rubric and then you differentiate it in Spanish. You make a version of it that better serves students who are behind grade level.

• 7:30Speaker 01

  You make a version of it that serves students who are above grade level. And now you have this incredibly differentiated assignment for all of those groups. Reading, like meeting a very practical need of educators today. One of those things that causes burnout is these, you know, incredible expectations we hurl upon teachers and they'll give them support to, to actually execute on them.

• 7:50Speaker 00

  That makes a lot of sense to me, and I think it explains why we need this. Because on one hand, if you imagine like the kind of R classroom environment, there's like 12 kids in this fantasy land and teachers knowing them all throughout the, you know, I don't know, third to fifth grade or whatever. But in reality, classrooms are large, they're multilingual, they're spread out across the current capability curve. And so it makes a lot of sense to use tools to essentially take that one teacher and then accelerate them, expand their capabilities. I don't know what the correct word there is, but we do have a pretty large teacher shortage in this country. According to data that I found, this is from the Learning Policy Institute, there's at least 412,000 positions that are unfilled or filled by not fully certified teachers in the US. So it's enormous.

• 8:32Speaker 00

  When teachers get their hands on Magic School, how long does it take for them to go from, okay, we have a new tool to being able to use it at a sufficient level of proficiency in the classroom to actually reduce their workload and then reduce the risk of burnout?

• 8:46Speaker 01

  So, you know, I think that the the core of the product is that it's so easy to use and it's so familiar for teachers. One of the compliments I still take a lot of pride in that we get today is that uh this must have been created by somebody who worked in schools. Like, how is it possible that you really know my job this well? You know, there are AI tools for other professions you mentioned when you started, like there's a bridge for healthcare, there's Harvey for law. Yep, yep. We just assume that these professions are um, you know, worthy of like spec- specific AI tools or there's a level of knowledge needed. And we don't necessarily as a society think about how technical a teacher's job is. And it is extremely technical. There are so many facets of what a teacher needs to do every day outside of the classroom teaching,

• 9:29Speaker 01

  including in the classroom teaching, things that go invisible to parents, that go invisible to uh the general society. But those were very intimate to me when I was a teacher and a principal and assistant principal. And we tried to throw all those things into the platform.

• 9:41Jason Calacanis?

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• 10:24Jason Calacanis?

  Hmm. Red Farm has that Peking duck. Oh, they've got some of those great knishes from the Lower East Side that I'll send to people. Bagels from New York, you know, my hometown of Brooklyn. You can even get pizza too. We're gonna give you 20% off your first Goldbelly order. Oh, Magnolia Bakery, I forgot about that one. That's another one I love. Goldbelly ships America's most delicious iconic foods nationwide. Get 20% off your first order by using the promo code TWIST at checkout.

• 10:49Speaker 01

  One of the things that's really interesting is that it's also solving that problem of like novice teachers in the classroom or under certified teachers in the classroom. We hear From schools and districts that sometimes the non teachers who are in the building, the long term subs, the maybe the career in technical education teacher who's coming in to teach welding in a school to

• 11:07Speaker 00

  Yeah.

• 11:07Speaker 01

  Help students get living wage jobs if colleges in the path for them. Those folks didn't get trained as teachers and Gen AI can be an incredible way for them to learn how to build a lesson plan and build content associated with these subjects that don't necessarily get big dollars for curriculum. So Magic School ends up being this incredible solve for the practical challenges of schools and districts right now. And yeah, it's been incredible to see the impact and the spread of the product. I think that the ease of use speaks to how fast it's spread. There are over six and a half million users signed up for Magic School. There are three and a half million educators in the United States and about half those users in that number are in the United States. So it's like a staggering number for distribution.

• 11:46Speaker 00

  I'll show the chart here. This is from, uh, this is your chart that you shared on LinkedIn, but I pulled it up for everyone today. Uh, this is from a company called Burbio. This is a tracker of the percentage of school districts that have paid to an AI platform in the last 12 months. And what you can see here is that there's a company called School AI that has some market share. There's ChatGPT, OpenAI, which does quite well. And then in first place, there is Magic School. And I wanted to ask about this because when I think about AI tools that have reached the mainstream, I mean, clearly ChatGPT with 800 million weekly active users has, has really crossed over into the, you know, normal conversation. How did you grow so quickly selling to a famously difficult industry? Because, uh, selling to governments, selling to schools has always been, at least when I was learning about venture capital and startups,

• 12:30Speaker 00

  like a big like red flag, don't even try. And yet you've generated enormous market share. So talk to me about, uh, distribution and sales.

• 12:37Speaker 01

  Yeah. As like a non-technology person, I learned down the line that I made a lot of mistakes that turned out to be the right decisions. Uh, I always think about like, when I started the product, there was, I had no monetization plan. Uh, you know, we were more or less a team of volunteers who'd launched a product in the world. I wouldn't even necessarily call it a company at the time, but I, I figured, you know, I've been a consumer of technology my whole life. I figured if I can get people to use this thing, we'll figure out the business stuff later. So I started seeding it to my teacher friends, folks I'd met through my career, and it was almost purely organic. We didn't spend a marketing dollar until we got to, you know, nearly a million educators signed up for the platform.

• 13:12Speaker 00

  That's crazy, man.

• 13:13Speaker 01

  When you build something that people want, like they will share it with others.

• 13:16Speaker 00

  Is that, is that just teacher word of mouth? Like teachers saying, look, this is really helping me organize my lesson plans, handle, you know, having lots and lots of kids. And then it just kind of spreading across the nation?

• 13:26Speaker 01

  Yeah, that's exactly.

• 13:27Speaker 00

  Wow.

• 13:28Speaker 01

  I mean, it turns out that, um, you know, teachers who are, you know, wired to help, right? That's in their DNA. When they find something that's genuinely helpful, they will tell the teacher next door. Um, and we certainly caught a moment of generative AI kind of coming to the world and

• 13:41Speaker 00

  Yeah.

• 13:42Speaker 01

  finding utility. But I think there was the ease of use, it being really directed to their profession and knowing them really, really well. All of that in combination ended up in this extraordinary red trajectory.

• 13:52Speaker 00

  So, speaking about the business side of this, I, I was curious who you sell to? Because on one hand, I know it says, you know, free for teachers on the site. Um, you also have stuff, you know, aimed at the district level. So are you selling to individual schools? Can a teacher buy more Magic School capacity themselves? Or is it district only? Talk to me about the, uh, the revenue side of things.

• 14:08Speaker 01

  Yeah, so it's very, very generous free product for teachers. We have a plus version of the product that has a couple of extra features, but it's not very, uh, heavily gated intentionally. We want teachers to, to get a lot of value out of the product, even if their district hasn't purchased it yet. And then our primary customer is the district. We want to sell directly to the district. And again, the reason why a district wants to join is similar to, um, you know, the, the easiest comp is like a ChatGPT, then ChatGPT plus, then ChatGPT enterprises. You know, they want data security and protection. They want single sign on. They also want to be able to infuse their own knowledge into the platform. They want to create their own customized versions of our AI tools that are backed by their state standards, their district policies.

• 14:49Speaker 00

  So it's going to be different based on not only if you're in Louisiana, but if you're in, you know, the New Orleans, um, school district or a different part of that state, just to pick an example.

• 14:57Speaker 01

  That's exactly right. So, you know, education is incredibly regional.

• 15:01Speaker 00

  Um, yes.

• 15:02Speaker 01

  So like we have teams that are based in more or less every state and region, uh, that understand like, hey, in this state, the district's priority is typically this. Um, and they actually work directly with the customers to help customize their product to their needs. So, and usually they're heavily contextualized to that area. So right now in Florida, uh, we're working directly with districts to build customized tools for the Florida state standards. And there, there are employees are in the school districts, working with their district technology leaders and academic leaders to make sure this tool is customized to their needs. In, in broader tech, this is considered like, you know, Forward deployed engineers or you know, we call them solutions architects at Magic School. And they are doing this work to really deeply customize the platform for the district.

• 15:44Speaker 01

  And you know, one of the things I share with our team, especially on our customer experience side is the next greatest thing that Magic School builds as a feature is actually the application of the current technology. Like if we can apply it really deeply and thoughtfully to the district's needs, then we can, you know, we can change the world. It's not about waiting for like the next shiny feature. It's about taking this incredible tech that we have and making it incredibly contextualized to the enterprise or the district.

• 16:10Speaker 00

  And underneath Magic School, you guys actually use a variety of AI models. You mentioned a couple of different providers on the site. Is the underlying technology still improving at a material rate to help you guys do more? Or is there already maybe enough capability inside of, you know, I don't know, OpenAI's four O and Gemini two point five to accomplish everything you're currently working on?

• 16:32Speaker 01

  At the current moment, I would say that, yeah, the models are pretty extraordinary for the tasks that we have them do right now. They do most everything exceptionally well. We use mostly anthropics and OpenAI's models in the platform.

• 16:46Speaker 00

  Okay.

• 16:46Speaker 01

  Where I think they can still improve would be in, for us, like things like guardrails for students. Yeah, like evaluations around text complexity, audio models, we part with eleven labs for some of our audio tooling in the platform. One thing that ends up being pretty challenging is when younger students are using like text to or speech to text. They'll often, you know, pause or stutter or, you know, these things that normal language wouldn't adapt to.

• 17:12Speaker 00

  Wait, they're not, they're not typing? Students need to learn, students need to learn how to type. I, I have heard, I've heard from employers of recent graduates that they type like this. And we're roughly the same age ish and like, I don't, I don't know, growing up, like we had to go to typing class. Like I sound like the world's oldest man, but bring back typing class.

• 17:30Speaker 01

  But you know, typing class is kind of like, I mean, AI is the new typing class, right?

• 17:34Speaker 00

  I know.

• 17:36Speaker 00

  As I was saying that, I'm like, but you use voice mode on chat GPT when you're tired. I'm like, okay, fair enough. Yeah. I, what's your general philosophy about students using AI? Classroom. The college board says that the percentage of high school students who report using gin AI for schoolwork rose from seventy nine to eighty four percent between January and May of this year. So it's gone from nearly everybody to nearly, nearly everybody. And again, I haven't been in K through twelve for half my life because time passes, but I can't imagine like my school handling it well in terms of how they approached changing maybe curriculum or expectations or so forth. So what do you think is the right amount of AI for students to use and interact with in the classroom? Because I know we want literacy, but we also don't want a lack of creative thinking.

• 18:21Speaker 01

  Yeah, well, I can, you know, quell your fears. Like, schools have done an extraordinary job of really thinking deeply about how they want to implement AI. We have been so inspired by our partners and how successful they've been in their implementation. So I'll give you my own opinion, but I think that a lot of districts will exist on a spectrum of how students should or shouldn't use AI. But for me, I think that there's real risk in cognitive offload to students early in their lives. And it should probably be pretty limited as kids are really early and maybe vary for very specific use cases. And then as kids get older, I think it ends up being this, still needs to be really thoughtfully guardrails and like, you know, grade by grade,

• 19:01Speaker 01

  scaffolded in a way that ends up ensuring that the students aren't getting too much support along the way. But I think it can be really, really powerful. The writing feedback tool I shared earlier ends up being this really powerful tool to grow students in their writing abilities. And they're still writing completely on their own, but just getting feedback right in time to revise and improve. So, you know, I'll capture this in a story of a student that I talked to recently who was in 10th grade. It was a friend of mine's daughter and we're talking, she knows I used to be a principal and she's asking me what I'm up to and I say, you know, I work this company called Magic School. She's like, oh, it's not, oh, we use this in school. I was like, oh, amazing. Like, tell me about how you use it.

• 19:43Speaker 00

  How tall did you feel in that moment?

• 19:45Speaker 01

  Oh, I felt

• 19:45Speaker 00

  Ten, twelve?

• 19:46Speaker 01

  Yeah, ten feet. Nothing gets more exciting when students say it, like, and they're excited about it. And so she tells me about it. Her history teacher uses the writing feedback tool about. So she writes her essays in history, gets feedback on it. She very articulately explained to me why it was valuable and how useful it was to get the feedback, revise her essay, and why that was like a good use of AI. I wish I could like, you know, she could have been the best advertisement for Magic School.

• 20:11Speaker 00

  You should have recorded that moment and just blasted.

• 20:14Speaker 01

  Nobody gets better. So she ends up, then I ask her, you know, tell me about your friends. You're in 10th grade, like, you know, AI is kind of this big thing happening. Well, what else are they doing with it? Like, what's happening with AI? She's like, well, you know, some of my friends are using it to cheat. And I know that's like, you know, something I can do too. And it's like an easy shortcut sometimes. But, you know, I've chosen to use it like in a really limited way. Sometimes I use it like to, as a thought partner, I really like when magic school happens in my classroom, but.

• 20:43Jason Calacanis?

  Launch is a fast growing organization. We've got more than a dozen employees working with me here in Austin and another dozen spread out all over the world. But there's so many moving parts when it comes to hiring and managing employees. There's the onboarding, of course, payroll, you gotta pay them. And listen, I've got all these podcasts to do. I don't have time for payroll benefits, HR taxes, answering questions, nor do I want to hire a full-time person and then have them do five hours of work a week. No, I have the perfect partner, Gusto. They're the all-in-one payroll and benefit product that's built just for your small business. Easy to use, it's incredibly fast to get started, and it's designed specifically with remote offices in mind. And Gusto is not just giving you helpful tools.

• 21:25Jason Calacanis?

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• 21:57Speaker 01

  You know, I don't want to give away my thinking too much, like my brain's in this important development stage. And so I'm thinking about using it in a really limited way and trying to be creative. But again, like when I take my tests and I'm applying to college, like I know my voice is going to matter and it's going to be proctored anyways. So like, you know, I'm not going to have this AI tool with me when I'm doing those things.

• 22:17Speaker 00

  Proctored for folks who haven't been in the system for a long time is when you're essentially doing something by hand and people are watching you take the test. You can't, you can't cheat, you can't have Google or something up on your screen.

• 22:26Speaker 01

  That's right. So, and the first thought I had was like, what a thoughtful young lady. Like how incredible it is that you've been, you have this much agency to decide how you're going to use AI.

• 22:36Speaker 00

  It gives me hope for the future, frankly. I hope, I hope everyone's like her.

• 22:39Speaker 01

  That same thought, and then the second thought that I had was she must have an incredible teacher who like helped her understand, you know, the difference between good use and bad use. And again, shouldn't every child be able to have that articulate response, that thoughtful a way of experiencing technology in the world?

• 22:55Speaker 00

  Yeah.

• 22:56Speaker 01

  So, so that I think that captures the story of how I want the world to evolve and students to use AI is have tons of agency and use it for the right reasons and be careful around the risk as well.

• 23:08Speaker 00

  I bring it up. So I was reading your guys' post from August 5th, 2025, calling, called Magic School's Commitment to Responsible AI Use in Schools. And you have, I'll just point up so everyone can see it. You have a bit of a kind of like demo text. I think this is what a school district might say to children about how to use AI. And this 80/20 rule stood out to me. It says, let AI handle the initial 80% of your draft and then add your final touches, the last 20%. Is that a standard rubric that schools use? Or is this just an example that I'm over indexing on because I'm paranoid about people not being able to write in the future?

• 23:42Speaker 01

  Mind you, this is not the message for students. That is the message for teachers.

• 23:47Speaker 00

  Ah, lovely. Okay, good.

• 23:49Speaker 01

  So yes, yes, you should be paranoid. I would never say that to students. Like, they need to be doing 100% of the cognitive lifting. And so that message is when a teacher signs into the platform, we let them know that, hey, Magic School can be this incredible augmentation to your work and help you feel really efficient. But be, be careful about offloading too much of your work to Magic School. Make sure that you're looking at every piece of material produced by the platform before you write in front of children because of other things we know. Like, there can be bias, hallucinations. So still trust your expertise. But yeah, that, that rule would definitely not apply to students. Not something that we're encouraging.

• 24:22Speaker 00

  Makes perfect sense. Just wanted to bring it up while I had you. So just to summarize, what Magic School has built is a series of tools to help educators not only differentiate their lessons to better fit each student, but also just to do more and also provide better, faster feedback to students with tools like the writing assessment. On the district-wide side, you can ingest your own information standards and so forth to create essentially a centralized AI tool to offer to schools. And on the student's side, they get better education via more tailored And plans and so forth. Okay, this all sounds fantastic to me. I'm glad things are going so well for the business. But I am curious what's next because you've really touched on a lot of the places where I can see AI fitting into K through 12 education in a positive sense. So I'm, I'm kind of curious to deal like, what do you want to build the next couple of years?

• 25:05Speaker 00

  Cause one thing you said in your funding announcement was we're gonna go build stuff. So I'm really kind of curious what the next year or two of a product looks like for Magic School.

• 25:13Speaker 01

  So one, like I mentioned before, I think one of the most important things we're gonna do is forward deploy our solutions architects, engineers to districts and make this deeply, deeply integrated with their challenges that they're facing every day. So that's gonna be

• 25:26Speaker 00

  And that's not cheap.

• 25:27Speaker 01

  And that is not cheap.

• 25:28Speaker 00

  Yeah.

• 25:29Speaker 01

  And then what does that actually look like in practice is kind of where the product will be going in the next couple of years. So, uh, one, um, we think that there is a huge opportunity to contextualize the use of both educators and students with the product. So if you think about, uh, like a unified knowledge graph for a student's experience with the product, uh, that could include maybe their, um, grade level, their categorization as a student who has, who needs a certain level of text complexity because of maybe a special education designation or an ELL designation or a language learner. And then all of the tools Magic School can very much directly support the student in their zone of proximal, proximal development.

• 26:13Speaker 01

  So they're not, you know, the, the material isn't below their grade level or so far above their grade level that's inaccessible. But it hits that zone where it's stretching them and helping them grow.

• 26:25Speaker 00

  Yeah.

• 26:25Speaker 01

  In a way that is, uh, incredibly valuable to, uh, you know, to the student and then also ends up being really valuable to the teacher. Because no teacher can carry, when they're looking at a student and building that relationship and having that connection, they also can't carry the student's last literacy, uh, test score, their last SAT score there. All of the designations they have that can help them learn better. It's really hard to carry all that with you. So can AI be this partner for the educator that helps them understand the students in context of what they can learn, what they love?

• 26:56Speaker 00

  Okay.

• 26:57Speaker 01

  Deeply contextualized to their world. And then on the Cater side, you know, Magic School needs to connect with their world more deeply, too. If you had a real assistant teacher, you would first train them on your students, their needs, the systems that they worked with, like you've got all messes. And then you could be more effective as a teacher. So Magic School is going to kind of get even deeper into all those places to be this truly personalized education assistant for students as well as a teacher's assistant for teachers.

• 27:23Speaker 00

  If we're going to end up in a world in which there's an AI or an instance of an AI tool per student that knows them from, let's say, K through 12, we're going to need to have relatively robust memory and context tools. Because, I mean, I love my instance of GPT five, but it's dumber than rocks. And can't forget me telling you, I don't want emojis, please, roughly twice a day. And it just can't hold on to it. So I know we're not at a level yet when I can say, hi, I'm Alex. I'm in grade 11 and it knows that in grade eight, I had a remedial English class or whatever. But I can see us getting there. And then you would have essentially for each student, a buddy for, really an assistant teacher

• 28:06Speaker 00

  for the student at that point, because the AI would know.

• 28:09Speaker 01

  Yeah.

• 28:10Speaker 00

  Lots about them, it'd have the context.

• 28:11Speaker 01

  Yeah, it'd have incredible context and still be driven through the teacher, right? The teacher still have to ensure that that AI was accountable to the student. This knowledge also ends up being super powerful for the teacher. Like I told you, the way that the teacher is differentiating the platform or the materials they're creating through the platform currently. But how incredible would it be if it just auto differentiated for you with the knowledge of each of your class periods? And it did it in a way that was even more precise to your classroom. So it ends up being a really great assistant for the teacher as well, because it has knowledge of all of the students in your class when it makes materials.

• 28:47Speaker 00

  That's fantastic. Huh. How far, how far from that do you think we are in terms of Fedrock AI capabilities? And also Magic School's ability to take advantage of them and implement them and bring them to market?

• 28:59Speaker 01

  Uh, our technology team, um, uh, would tell you.

• 29:05Speaker 01

  I think that we're, I think we're pretty darned close.

• 29:08Speaker 00

  Okay.

• 29:09Speaker 01

  Really cool work. I expect that some of these bits of what you're we're talking about will be available as early as January. And I think that in the next year, it can feel like a wholly different world, especially for the districts that partner with us. They'll get kind of like the earliest like testing and access to these things. We have really incredible partnerships with the foundation models. Who are really excited to support us and ends up being

• 29:33Speaker 00

  Do they subsidize? You guys, do they offer a discounted access to their APIs? Because you're actually trying to help kids because if I was OpenAI and you guys were using my model, I would try to find some way to shave off a couple of basis points. Just because you're trying to help kids.

• 29:46Speaker 01

  You hear that, OpenAI? We could, we could use a discount.

• 29:49Speaker 00

  Sam, we've met a whole one time for seven seconds. That makes best friends. Come on.

• 29:53Speaker 01

  There you go. Yeah, no, we do not. But we have a very sustainable business model that allows us to to do this work and you know, great funding. So it's been, we don't feel like these things are outside of our capabilities. But and you know, while they don't give us, you know, free tokens, they do end up being incredible supporters of us. Like Anthropic has a beneficial deployments team that supports us. OpenAI has an education team that supports us. So we feel really close to the model providers and they've been incredible partners. So.

• 30:21Speaker 00

  All right. One last question to deal before I let you go. The US is one small slice of the world. And I think we're all kind of seeing, you know, peak college student and that's going to trickle backwards into K through 12. So we're not heading towards, you know, opening tons of new schools in the US, I don't think. Which makes me curious when you're going to take this abroad and which markets are going to be the most, most second for the product? I mean, I immediately think of similar ish schools in perhaps Europe, maybe, but what does the world look like to you?

• 30:48Speaker 01

  So we will absolutely take this up to the world. We have a massive amount of usage internationally without any marketing or or direct sales. We do get inbound customers and partners from international schools and places all over the world. One, I mean, it is also kind of the staggering number of US adoption. We'll find countries when we look at our data sometimes and like the UA, we have reason to believe like 80% of educators in the UA are using Magic School.

• 31:13Speaker 00

  No, the UA is not the largest nation in the world, but 80% of any nation is. That's insane.

• 31:19Speaker 01

  Direct marketing, no presence there whatsoever.

• 31:22Speaker 00

  And that's why the $45 million Series B was led by Valor Equity Partners and Bain, Adobe, and Tradies and Smash all kicked in cash because everyone loves low CAC.

• 31:32Speaker 01

  Yeah, it is one of those incredible things. People ask us sometimes, like, how do you acquire so many folks? Well, we have this incredible product and legion of educators who want to support each other and that ends up being a really big superpower.

• 31:42Speaker 00

  All right, ideal. Well, I'm not only now less concerned about the state of K through 12, I'm actually more bullish about it. So Godspeed to you and the team. And whatever you do put out in January, send me an email. We'll have you back on to talk about it because it sounds like you have quite a lot cooking. Thanks for coming on.

• 31:56Speaker 01

  Lots of good stuff coming. Thanks so much for having me, Alex.

• 31:58Jason Calacanis?

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• 32:41Jason Calacanis?

  to bulk create and update records. So it's easier and faster than ever to design data-heavy apps that are constantly syncing between systems. That's the kind of attention to detail that sets Zeit apart. Start using the number one AI-powered business software generator on the market. I'm going to give you 50% off your first project. Go to zeit.com/twist to get started. That's zeit.com/twist for 50% off your first project. We like to do founder questions here. We have two good founder questions.

• 33:09Speaker 03

  Let's do it. Thanks for having me, Jason. I really appreciate it.

• 33:11Jason Calacanis?

  Okay, so number six, we got a founder question I think is pretty interesting.

• 33:15Speaker 00

  Yeah, so one person was asking about how long employee shares should take to vest. They were looking at an offer from a company in the hardware realm, and they were offered 0.023% of the company over a six-year period. And so the question is, is that a Standard term that employees should be willing to accept? Or is that something you might want to have only for founders that are raising venture capital money? Your take?

• 33:36Speaker 03

  Six is definitely abnormal. I would say market standard is a four year vest is fairly typical. There are companies that diverge from it, like I think probably the most, you know, the extremes on one end, you'd see six or you could see like even, I think like the stripes of the world have every year, you get an extra tranche of RSUs that vest over a 12 month period, which is a one year kind of vest and every year they kind of re underwrite where you are.

• 34:01Speaker 00

  But they're kind of a public company. It's a little bit different. They're essentially offering the Google.

• 34:06Jason Calacanis?

  No, but it's a good point. If you were going to come to a brand name company, they can extract a longer vesting period because the shares are worth more, right? I mean, that makes logical sense. It's not as speculative as a earlier stage company, to your point, Alex.

• 34:20Speaker 03

  What I would say ultimately is in some sense, a six year can be good, right? If you believe the value of the shares are going to multiply, presumably if that stock is going up two, four, 10 times, what you're going to be vesting into in the six year is going to be worth a heck of a lot more. And so you may be willing to elongate it. But I think like any negotiation, you need to look and say like, do I believe in this? And is this enough, you know? If you look at the total value of the compensation over the next year, cash, stock and kind benefits, does it meet your bar or not? And so while I'd say it's unusual, sometimes it would make sense to take that kind of an offer. But if I were friends with this person, I would say like, it should meet this level for you. And hopefully you believe, you know, in this company enough that you're willing to wait for six years

• 35:04Speaker 03

  and want to be there for this period of time to see where this goes.

• 35:07Speaker 00

  Six years is a long time, Jason. Do you recommend the companies going through the launch accelerator offer employees four or six year vesting schedules?

• 35:13Jason Calacanis?

  This is one of these like quirky things where founders who are a unique species in the world, I certainly was when I was starting companies. You want to reinvent everything. So you look at a vesting schedule, you look at shares, you look at the convertible note. You're like, oh, I can innovate on this. So, and I would do stuff like that. And I would like over negotiate like totally meaningless things early in my career. And, you know, at some point, I think rule off. You know, my best advice over at Sequoia is the best advice, just keep everything standard. So then when people ask you to do weird things on the other side, you can say, I prefer standard and everything I do is standard. So if you're not Elon or Carlson Brothers or somebody like really unique in the world, maybe keep it simple and focus on the product innovation in your product,

• 35:58Jason Calacanis?

  not in the legal documents. A great example of this would be Bezos at Amazon. He went with this like five, 15, 40, 40, I think is what it was where you first year you get 5%. Next year you give 15% of your equity grant and it's backloaded. What this does is lets the company, if they really value their shares, say, you know what? We assume some number of people aren't going to make it to year three, when really the magic happens and you tip over from being a drag on the company where we're investing in you, to you're actually providing massive value for the company because you've learned how to be an executive here. You've got executive training, but you're Bezos, you can get away with that. And also it's a bit of a test because if somebody argues that on the other side, Eric, you would be like, okay, why does this person want it?

• 36:39Jason Calacanis?

  The biggest tell I ever did was like one time in my career, somebody told me it was standard to give people like six months severance or three months severance. And I did it and like I gave them three months severance and literally the person became a disaster six months in. And I was like, oh my God, they're working for their severance package. And so then I just told everybody, you know, in startups, you don't get like a, there's no such thing as severance in a startup. If you do a riff or a layoff, sure, you can give people severance, but I'm talking about like, if you leave and you're, or you're fired, you don't get severance. I mean, that's like for Tommy Mottola at Sony or like some, you know, I don't know, Barry Diller at Columbia Pictures or something like, that's something a major executive can extract. So anyway, it's a really interesting question. I would keep it standard just so that you can focus on other things.

• 37:19Jason Calacanis?

  What I do like, I don't know if you've done this, Eric, with like high performers, but somebody's a high performer, you just layer on a parallel grant. So like, you're like, this person's killer, like year two, you're like, I'm giving you another four year grant. So now you have them for six.

• 37:31Speaker 00

  Yeah.

• 37:32Jason Calacanis?

  You know, you have just overlapping ones and then it gets really costly to leave if you're that employee because you've got double grants.

• 37:36Speaker 00

  That happened to be my last, my last job, Jason, they layered on extra merit comp on top of my salary. And I was like, well, I guess I'm never leaving. But sometimes people do leave. And a question that I wanted to ask today, Jason, is what happens when a co-founder exits a company?

• 37:51Jason Calacanis?

  Well, before we get to that one, I wanted to ask Eric if he's done the layered grants.

• 37:54Speaker 03

  First of all, yes, and I agree with your advice. I think innovating on the business model, what makes you different, really good idea. In general, I think what you and Ruloff and everyone is saying is right. Keeping it easier just reduces friction to people getting to say yes. And frankly, too, there are some people in your business that like they are not twice as valuable or four times valuable, they will be 50 times as valuable.

• 38:17Jason Calacanis?

  Yes.

• 38:18Speaker 03

  And once you find it, like, hold on, invest and spend against it. Because frankly, one, you should do the right thing for people who are just care at the level and can have the impact. But second, it's just very clearly good business. And so that's where I think you should hold the equity to invest in those situations.

• 38:38Speaker 00

  We have a friend from the Gamma Pitch Competition. I'm really excited to bring up Chris Canetti. He's the founder and CEO of a company called On the Fly Energy. And Jason, I was initially skeptical until I realized what they're building. And then I became an enormous fan. Please, everyone, welcome to the show. It's Chris. Chris, hey, how you doing?

• 38:56Speaker 04

  Good. How are you?

• 38:57Jason Calacanis?

  Welcome to the show, Chris. Why don't you go ahead and put on your presentation here, Power by Gamma. Great way to do AI presentations that look really sharp and crisp. We'll have you pitch us here and we'll give you a little feedback.

• 39:10Speaker 04

  Hi, guys. I'm Chris Canetti, founder of On the Fly Energy. And I'm here to tackle one of today's toughest emerging challenges. We talk about, we take electricity for granted until the lights go out. Our grid is fragile and a split second fault can knock out critical infrastructure and AI data centers are making this worse. GPUs swing from zero to 100% in milliseconds, destabilizing the entire system. The day solutions all fall short. Batteries are expensive, degrade and can burn. Diesel generators are slow and maintenance heavy. Take for example, last summer in Virginia, a lightning arrestor failed, forcing 60 data centers offline in an instant, nearly triggering a cascading blackout. Industry and AI alike need resilient energy storage, and that's the gap that On The Fly Energy fills. Here's our solution. The rotor seed is a 10 kilowatt hour modular flywheel that installs like a backup battery, charging, storing and releasing energy.

• 39:53Speaker 04

  Rotor seeds stack into rotor pods and scale into the rotor farm, capable of delivering megawatt hours of distributed protection for everything from a single server to the local electric grid. On The Fly Energy is built for America's backbone, where uptime is non-negotiable. The rotor seed delivers instant, fire-safe backup and conditioning for sectors that matter most with over two decades of life, and it's built in America to strengthen energy independence. Now, we're targeting over $100 billion energy market, consisting of over 100,000 US facilities from AI data centers to manufacturing hubs. All where batteries fail, diesels lag and uptime is priceless, needing to capture just 1/10 of a percent to get to 100 million in market share. On The Fly Energy wins where it counts. There's no fire risk, no degradation, no 30-second lag or upkeep like diesels, and scalable beyond capacitors for real long-duration protection. It's simply a better spin on backup power.

• 40:37Speaker 04

  The rotor seed units are offered as a monthly subscription and collect revenue on demand, shifting and energy delivered. Additionally, we plan on offering utility support and active AI energy optimization, all with a straightforward upgrade path that grows with the customer's business. Now, what makes this model powerful isn't just lease storage, it's the network functioning as a virtual power plant to help regulate the grid. We don't compete with the utilities, we help power them. The path to market, so far we've built our proof of concept to validate the core physics, design and functionality. In early '26, we'll conduct MVP trials at beta sites. In '27, we plan a small commercial launch targeting telecom and small data centers. And in '28, we expand into large AI data centers and full grid-scale storage capacity. I'm Chris Canetti, the hands-on founder of On The Fly Energy, Inc., and for nearly a decade, I've built automated manufacturing solutions at companies like Tesla and other startups.

• 41:20Speaker 04

  I still run a small machine shop out of my garage, and my teammate, Justin Osborne, brings deep electrical controls expertise. Together, we're building On The Fly Energy with AS9100 level standards and automation from day one, because engineering, quality and manufacturing scale. On The Fly Energy, we're tackling $100 billion market with hardware that outlast batteries, outpaces diesel. delivers protection where America needs it most. The grid's future doesn't burn, it spins. Thank you.

• 41:43Jason Calacanis?

  All right. I'm a little confused as to what the physical product is. I understand the problem.

• 41:51Speaker 04

  Yep.

• 41:51Jason Calacanis?

  People need extra energy. I understand there's a flywheel involved and there's like a cutout of it. What is this physical product?

• 41:59Speaker 04

  So the physical product, yes, the physical product is essentially a battery energy storage system, but with a kinetic energy storage rather than chemical. So restoring rather than lithium batteries, we're storing in kinetic energy form.

• 42:11Jason Calacanis?

  Explain what that means to, yeah, somebody who's not an expert in this. Is it, you're basically putting batteries into data centers, but they're different? Types of batteries?

• 42:20Speaker 04

  Essentially. So rather than a lithium battery, which stores energy in chemical form, we're storing energy in kinetic form, which is a flywheel that spins. And so you take that excess energy and you put it into the form of inertia and you spin a disk around really fast. And then you can pull power from that or buffer power into it, whichever way you need to

• 42:42Speaker 04

  level out these spikes that the AI designers use.

• 42:44Speaker 00

  So Chris, a question about that, because there's always going to be some friction in stored momentum. So how much, if I had this wheel, which it appears to be spinning very quickly in my data center, just waiting for me, how much energy do I have to put into it to keep it at max kinetic energy potential?

• 43:00Speaker 04

  So depending on the size of the system that you're using, we see about a 95% return currently from the power that you put into the power that you get back out. And that's in our

• 43:10Speaker 00

  Sounds very good to me.

• 43:12Speaker 04

  That is pretty good.

• 43:12Speaker 00

  Okay. So 95% of the energy that I put in, I get to take out. And because it's a spinning, is it iron? What's the actual thing that's spinning?

• 43:21Speaker 04

  It's a carbon fiber composite.

• 43:22Speaker 00

  That sounds light. Wouldn't you want something to be heavy and kind of

• 43:24Speaker 04

  It is light, but so where you wind up storing, because the way that energy stores in kinetic energy is, it's a to the power math equation, so that every RPM that you can gain is actually a significantly larger amount of energy that you can store. So if you can spin faster and not have the material weakness that say steel or something heavy would have, you can actually store significantly more than you could in just a heavier mass.

• 43:47Speaker 00

  And how big is this rotor seed, the 10 kilowatt hour module that you're describing? If I wanted to hold it in my hands?

• 43:53Speaker 04

  Yeah. So the current version that you're, that we have is basically an 18 inch diameter by an 18 inch long length, and that makes the 10 kilowatt hour base unit.

• 44:03Speaker 00

  That's not, that's not very big. Does it vibrate?

• 44:06Speaker 04

  It does not vibrate. It is on magnetic bearings.

• 44:09Speaker 00

  So you can just, you can stack these.

• 44:10Speaker 04

  You can stack these into something, say like an ISO shipping container or another form factor like that, that's easy to distribute if needed.

• 44:18Speaker 00

  So as long as they're not moving, there's no pushback from the wheels motion itself. So, okay, that's, that's pretty awesome. What does it cost to build one of these?

• 44:24Speaker 04

  Right now, the prototype that we're at right now is sub 10K and I'd like to be significantly lower than that, looking at what the business model is going to wind up being for ROI potentially being in the one to two years.

• 44:37Speaker 00

  Okay. And then for a 10 kilowatt hour battery, what does that cost today?

• 44:40Speaker 04

  So a 10 kilowatt hour battery can cost you anywhere from $10,000. If you get it really cheap and you're doing, you know, getting a little scrappy and you're buying 18 650 cells off of eBay, you can do it for probably a couple thousand dollars. And if you do it the legitimate way and say you're buying like a Tesla Powerwall, that's pretty close to a similar energy density, you're probably in the 10 to 15,000.

• 45:04Speaker 00

  Okay.

• 45:05Jason Calacanis?

  So this is interesting. I asked producer Claude to explain it to me like a 10 year old because, you know, I just still not getting it. I mean, I was getting it, but it's like spinning a top. You have this thing that you start spinning like a top. So you put some energy into it, it spins. You don't need to keep adding energy to it. It keeps the spinning going through magnets, et cetera.

• 45:29Speaker 04

  Yep.

• 45:29Jason Calacanis?

  Then when you need it, it slows down and slowly lets that energy back out. So they use this in space and on roller coasters and buses? This is the other use case for this technology?

• 45:42Speaker 04

  Yeah, so the original, the original bit of this technology, it did exist in buses, I believe, before the trolleys and SF existed, is by understanding that there were large mass spinning flywheels that existed.

• 45:55Jason Calacanis?

  Wow. So this is like you're bringing back an old energy source with new.

• 46:02Speaker 04

  Modern materials.

• 46:04Jason Calacanis?

  Ah, so genius. So I think like as an idea, it's extraordinary because people need more energy and they need more backup energy. So data centers have a ton of money to spend, so that's the best place to go right now. And there's cheap energy available when you want to.

• 46:22Jason Calacanis?

  Fill these up, right, at certain times during the day?

• 46:24Speaker 04

  Yeah.

• 46:24Jason Calacanis?

  So you can do that arbitrage, you can fill them when energy's cheap, correct?

• 46:28Speaker 04

  Exactly, you can fill them when areas cheap. And then you can also do this little bit where you're getting to condition these AI power loads that like to spike and then drop loads every time someone wants to generate their, their image. The AI data center goes up, that usage on the grid goes up. And the grid was really built for a pretty continuous load system. So we can kind of do this as the energy arbitrage with the virtual power plants. And then you can also condition the power that's going into the building. So that say, the AI data center's load is actually all over the place. But you can basically make it so that this is the buffer zone between the AI data center and the grid. So the grid sees the constant.

• 47:05Speaker 00

  We saw this, Jason, with Base Power and Zach Dell.

• 47:07Jason Calacanis?

  I was about to.

• 47:08Speaker 00

  Oh, yeah, sorry.

• 47:09Jason Calacanis?

  No, no, go ahead, finish it, yeah, you can.

• 47:11Speaker 00

  Oh, I was gonna say, we just had Base Power on, Chris, a couple, a couple of shows ago. And he was discussing how they were putting batteries in front of houses in the grid and how that would also dampen the spikiness of the overall grid that we live with, yeah.

• 47:23Speaker 04

  And being that I'm in California, I can't do kind of the same model that they were doing. California's energy grid is a little different than ERCOT, so we're targeting.

• 47:31Jason Calacanis?

  ERCOT being Texas's.

• 47:32Speaker 04

  Yes, being Texas's.

• 47:33Jason Calacanis?

  Which is completely deregulated and you can add and take energy out in a much more fluid way.

• 47:41Speaker 04

  Yes, they're much more free.

• 47:43Jason Calacanis?

  Much more free. So I guess, would this also work for air conditioning in places where it's very hot? So you go Mexico City, you know, Dallas, Houston, Austin, Phoenix, you know, all those kind of places where you have really 100 days of 100 degrees or hotter. You have these things attached to buildings. At night, they fill up and then during the day, instead of hitting the grid, when I think it's a 5X price difference.

• 48:13Speaker 04

  Yep.

• 48:14Jason Calacanis?

  You could power all the air conditioning.

• 48:16Speaker 04

  You can do exactly that. And something that if you weren't, what, there's a model like that? Or you could do something that's following what's the DUC curve is. Basically, we get a lot of solar, cheap energy, right when solar is peak. And there's really not a whole lot of residential load at that point. And you get a really tail end. The tail end of the duck that curves up, that is a high demand speak peak, right when solar and well, generally solar starts to taper off. You can kind of play that arbitrage game where you're going, where do you, where's the, uh, what makes the most sense to charge up? Do you charge up at night when the base load is, uh, steady and the peak's really low? Do you charge up when solar is really cheap in the middle of the day and there's not a high demand and you store that for a few hours? And then you can dissipate that when everyone's coming home and turning on their A C.

• 48:58Speaker 04

  And then across the industry, there's uses for this all over the place. One of the, one of the other sectors that I'm looking at, but we're not focusing on that because we're focusing on the A I data centers. Just try, try to get ourselves into it. You look at, um, all these E V fast charge, uh, systems that are being installed places. It takes 12 to 24 months to get these, uh, utility and permits set up to be able to do these fast chargers. And some of them don't have the support to be able to do 250, 350 or 500 kilowatt chargers. So you can do kind of this portion where even a kinetic energy storage system or just a battery energy storage system sits between the grid and this fast charger.

• 49:39Speaker 04

  And your, your technical site could only have a hundred kilowatt hour hookup, but you could have multiple 150 or 250 kilowatt hour chargers because you can charge this and level out that peak. You're basically doing the same thing that you're doing with the data centers, trying to make this a level uh, energy draw for a longer period. And then when you get a load, say a vehicle showing up and wanting to fast charge, that's your spike, but you're buffering it with the battery energy storage so that the grid doesn't see it.

• 50:04Jason Calacanis?

  And if you, uh,

• 50:05Speaker 04

  That's the duck curve.

• 50:06Jason Calacanis?

  And here's the duck curve, as you can see.

• 50:08Speaker 04

  Yep.

• 50:09Jason Calacanis?

  Um, you know, in the morning, uh, nine A M., uh, then it goes 12, three and six. The energy usage can go down and you're like, wait, why is it going down? Well, people return home, solar stops working and you peak.

• 50:24Speaker 04

  Right at the worst time.

• 50:26Jason Calacanis?

  At the worst time. So the sun goes down, everybody returns home, Alex. They decide to do a load of laundry, maybe they put the air conditioner up or in the, I guess they could also put their heat on.

• 50:39Speaker 04

  Sure.

• 50:39Jason Calacanis?

  And it looks like a duck.

• 50:42Speaker 00

  And that's It's a brilliant analogy, but also it just goes to show how complicated the power question is between base load power, variable power sources and storage. But between XO watt storing industrial heat, base power doing batteries at the house and hydro storage and compressed air energy storage. And now we have on the fly energy using fly wheels. Jason, I'm actually a little bit optimistic right now.

• 51:02Jason Calacanis?

  You know, here's the thing. We talked a little bit earlier about truth and the search for truth. And how, you know, generative AI during this weekend protests or anything, you know, during the debate over the southern border, people can use data sources that aren't true to try to manipulate and or fight for their position or their, you know, tribe, whatever it is. And with energy, one of the interesting things is the data is the data, Chris, right? Like there's a price of energy that you cannot fake.

• 51:37Speaker 04

  Yep, and it's well metered and it's reported at most places easily accessible.

• 51:41Jason Calacanis?

  Literally with ERCOT, you can pull up ERCOT's data in real time, Alex, because it's a real time exchange of energy. So when, you know, I'm interviewing Chris Wright and we're talking about, you know, the, the administration's love of clean, beautiful coal and, you know, solar is intermittent. And then Elon is saying, well, look, solar is the best thing in the world because you can just build it and it, you know, it's cheap and clean and there's, it's free. And then other people are like, well, what about geothermal? Or you have a new technology or a new approach like base power or here, what Chris is doing. You can just start to pull together reality by just looking at the data.

• 52:26Jason Calacanis?

  Of course, it's become very political and very sharp elbowed. What, what's your take on overall if our country needs to invest a massive amount of money in energy? And you were in charge, I make you the energy secretary.

• 52:44Jason Calacanis?

  How would you think long term? And when I say long term, you know, 10, 20, 30 years for America. And let's say you have a trillion dollars you're going to deploy over those 30 years. Just on a percentage basis, where would you, you know, hey, get us the short term energy, get us the midterm, get us the long term. How would you advise doing it? Obviously, you have your own book and you know, that's a portion of it. But just broad strokes, what should we be doing with energy? I'm sure you think about this all the time.

• 53:11Speaker 04

  I do think about it all the time. And kind of the broad strokes, the way I see it is kind of like you mentioned. So, short term, we need a solution right now. Whatever that looks like, whether that be natural gas, peak your power plants. I don't believe that whole is the solution. Maybe we're looking at other, other forms. There's all these solar, wind, renewable things. And if you can have a way to store it, that's kind of where on the fly energy's fallen in, you get to, get to play on that game. But then, on the broad stroke, as we're going, America needs energy independence. And how do we get there? We really need to be self reliant. And if that means we can generate all of our energy as we need it and store it. I mean, that's the biggest thing. If we can have renewables and be able to take

• 53:53Speaker 04

  out the downside of renewables, that is, production fluctuation and unpredictability, depending where it's at, and being able to store that and being able to redistribute that across the grid to where you need it. That's kind of the solution that I see. So if you could do other renewable options, being wind, solar, and then kind of base load with nuclear power.

• 54:12Jason Calacanis?

  Yeah.

• 54:12Speaker 04

  You'd be able to cover that entire grid and be able to be essentially entirely energy independent as a country.

• 54:19Jason Calacanis?

  Okay, I have a question about scale here, because in your, your deck that we went through, which by the way, very nice, appreciate that. It looks like a small device, 18 inches by 18 inches, spins inside of it, very, very cool. Why not make a really big one? Like, I mean, huge. Like, why can't we make one of these at a city scale, for example?

• 54:38Speaker 04

  So, the physics of it get really limiting. So, kind of what has advanced in the last Fifty years from the heavyweight flywheels is really a materials question. And where we've come is these composite high-tech aerospace materials. And what you're getting is a higher strength option here so that you can spin it faster and faster. And one of the limiting stresses here is basically how fast the surface of that rotor is actually spinning. So the larger diameter you make this, the faster the surface speed actually winds up going. And because that fact, that higher surface speed is there, there's something called hoop stress. And I'm hoping Claude will hop in here and give you a little definition.

• 55:18Speaker 04

  That hoop stress is basically a function of the tensile strength of the material that you're making it out of on the outside diameter. And it's basically what's trying to burst this thing. It's basically why, like a hot dog, when you cook a hot dog, why a hot dog splits down the seam? And doesn't split in half the other way.

• 55:35Speaker 00

  So what if we put a large iron rod, like an old wheel, around the edge of the? I'm kidding with you, but like, my question is, why do we have to make this in small units? Why can't we just make large ones?

• 55:45Speaker 04

  Well, we can make large units, yeah. You can make significantly larger ones that are, uh, power density actually works out kind of similar. But you'd get other scale factors where you have lower, lower, uh, number of components that go into it.

• 55:57Speaker 00

  Okay, well, I'll just say, I like the small ones, I like the big ones. And I think, you know, AI data centers is a great place to start because it'll attract investor attention. There's a lot of money there, but also like, I want one for my house, because this sounds awesome.

• 56:09Speaker 04

  I do as well, that's where the first prototype's at.

• 56:11Jason Calacanis?

  Chris, what's the story here with funding? I mean, I'm an investor in this company. I feel like this is like, uh, gonna be, if you figure this out and it actually works, you've raised a lot of money so far. You're funding it yourself, you were at Tesla previously.

• 56:22Speaker 04

  I'm funding it myself right now.

• 56:23Jason Calacanis?

  Really?

• 56:24Speaker 04

  Yeah.

• 56:24Jason Calacanis?

  That's my kind of founder. What's going on here? Maybe I can, you gotta, can you save a slice for J Cal? I might want to get in.

• 56:31Speaker 04

  I will save a slice, I'll put a little sticky note right on the, uh, the cap deck for you.

• 56:35Jason Calacanis?

  I'm not saying like I have to have the whole pie. Like, if you order a giant pie, I'm just, you can even cut me a half a slice is better than no slice. I love what you're doing. This is great. Let's stay in touch and thanks to our friends at Gamma for making great pitch software and then helping us find great founders like Chris and great startups. Really well done. You can build amazing presentations in just minutes using Gamma. And they hosted this incredible pitch competition, which Chris, I don't know, you might be the leading, uh, you might, you might wind up taking this down and winning.

• 57:10Speaker 04

  Hey, I'm, love to hear that.

• 57:12Jason Calacanis?

  Oh, okay, maybe. I'm intrigued. All right, Chris. Great job, and we'll talk soon. Let me know when you're in Texas. Thank you, guys. Yeah, come on. Will do. Let's get some, uh, I'm gonna take you out for some barbecue and try and weasel my way onto that cat table. Uh, great, great job, Chris. I'll drop Chris off. Uh, and if you're feeling inspired, head to gamma.app, A P P, G A M M A dot A P P. So you can start working on your idea and you can change the world like Chris is doing. And maybe we'll see you on a future episode of This Week in Startups. Well done.