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

23:16And you have, I'll just pull it 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 to 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? Mind you, this is not the message for students. That is the message for teachers. Ah, lovely. Okay, good.

23:49So yes, yes. You should be fair to her. I would never say that to students. Like they need to be doing 100 % of the cognitive lifting. Okay. 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 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 get in front of children because of the things we know. Like there can be bias, hallucinations. So still trust your expertise.

24:18But yeah, that rule would definitely not apply to students. And that's something that we're encouraging. 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 side, they get better education via more tailored lesson plans and so forth.

24:50Okay. 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-12 education in a positive sense. So I'm kind of curious to deal, like what do you want to build the next couple of years? Because one thing you said in your funding announcement was we're going to go build stuff. So I'm really kind of curious what the next year or two of a product looks like for Magic School. So one, like I mentioned before, I think one of the most important things we're going to 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.

25:25So that's going to be a big focus. And that is not cheap. 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 one, we think that there is a huge opportunity to contextualize the use of both educators and students with a product. So if you think about like a unified knowledge graph for a student's experience with a product, That could include maybe their grade level, their categorization as a student who has, who needs a certain level of text complexity because there may be a special education designation or an ELL designation or a language learner.

26:04And then all of the tools in Magic School can very much directly support the student in their zone of proximal development. So they're not, you know, the material isn't below their grade level or so far above their grade level that it's inaccessible. But it hits that zone where it's stretching them and helping them grow in a way that is incredibly valuable to, you know, to the student. And it 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 test score.

26:42their last SAT score, 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, deeply contextualize to their world? And then on the educator side, 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 maybe LMSs. And then you can 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 system for students, as well as a teacher's system for teachers.

27:23If we're going to end up in a world in which there is 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-5, 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 onto 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 for the student at that point, because the AI would know lots about them.

28:10It'd have the context. Yeah, it'd have incredible context and still be driven through the teacher, right? The teacher would still have to ensure that the 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 the students in 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.

28:47That's fantastic. Huh. How far from that do you think we are in terms of bedrock AI capabilities and also Magic School's ability to take advantage of them and implement them and bring them to market? Our technology team would tell you. I think that we're I think we're pretty darn close. We're doing some really, really cool work. I expect that some of these bits of what 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.

29:27We have really incredible partnerships with the foundation models who are really excited to support us. It ends up being discounted. Do they subsidize? You guys at all, 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. You hear that OpenAI? We could use it as Cal. Sam, we've met a whole one time for seven seconds. That makes best friends. Come on. There you go. Yeah, no, we do not. But we have a very sustainable business model that allows us to do this work and great funding.

30:01So it's been, we don't feel like these things are outside of our capabilities. And while they don't give us 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. All right. All right. One last question to deal before I let you go. The U.S. 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.

30:31So we're not heading towards, you know, opening tons of new schools in the U.S., 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? So we will absolutely take the step to the world. We have a massive amount of usage internationally without any marketing 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 U.S.

31:03adoption. We'll find countries when we look at our data sometimes and like the UAE, we have reason to believe like 80 % of educators in the UAE are using Magic School. the UAE is not the largest nation in the world, but 80 % of any nation. That's insane. With no direct marketing, no presence there whatsoever. And that's why the$45 million Series B was led by Valor Equity Partners and Bain, Adobe, Atreides, and Smash all kicked in cash because everyone loves low-cac. 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.

31:40And that ends up being a really big superpower. All right, I deal. 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. Lots of good stuff coming. Thanks so much for having me, Alex. Your startup needs custom software, but building your own secure production-ready apps is hard, right? And not every founder has the expertise or time to get started.

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32:43So 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 Zyte 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 Zite.com slash twist to get started. That's Zite.com slash twist for 50 % off your first project. We like to do founder questions here. We have two good founder questions. Let's do it. Thanks for having me, Jason. I really appreciate it. Okay. So number six, we got a founder question I think is pretty interesting.

33:15Yeah. 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? 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.

33:59And every year they kind of re-underwrite where you are. But they're kind of a public company. It's a little bit different. They're essentially offering the Google RSU. 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 an earlier stage company, to your point, Alex. 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.

34:36And so you may be willing to elongate it. But I think to 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, in-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 and want to be there for this period of time to see where this goes.

35:07Six years is a long time. Jason, do you recommend the company is going through the launch accelerator, offer employees four or six year investing schedules? 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, and you're like, oh, I can innovate on this. 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 Ruloff said, you know, my best advice over at Sequoia is the best advice, just keep everything standard.

35:43So 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 Coulson brothers or somebody like really unique in the world, maybe keep it simple and focus on the product innovation in your product, 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 get 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.

36:30You'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? 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.

36:58If 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. 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.

37:25So like, you're like this person's killer. Like year two, you're like giving you another four year grant. So now you have them for six. Yeah. You know, you have just overlapping ones. And then it gets really costly to leave if you're that employee because you got double grants. You've done Eric. That happened to be 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? Well, before we get to that one, I want to ask Eric if he's done the layered grants.

37:55First 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 Rulof 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 as valuable. They will be 50 times as valuable. 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.

38:28But 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.

38:38We 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? Good. How are you? Welcome to the show, Chris. Chris, why don't you go ahead and put on your presentation here, Powered by Gama. 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.

39:10Hi, guys. I'm Chris Gennady, founder of On the Fly Energy, and I'm here to tackle one of today's toughest emerging challenges. 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 0 to 100 % in milliseconds, destabilizing the entire system. The data 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.

39:42Industry 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. 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. 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.

40:13Now, we're targeting over a$100 billion energy market, consisting of over 100 ,000 U.S. facilities, from AI data centers to manufacturing hubs. All where batteries fail, diesels lag and uptime is priceless, leading to capture just one-tenth 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. The rotary seed units are offered as a monthly subscription and collect revenue on demand shifting and energy delivery.

40:42Additionally, 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. Paths 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.

41:09And in 28, we expand into large AI data centers and full grid scale storage capacity. I'm Chris Connetti, 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. 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 a$100 billion market with hardware that outlasts batteries, outpaces diesel, delivers protection where America needs it most.

41:41The grid's future doesn't burn, it spins. Thank you. All right. I'm a little confused as to what the physical product is. I understand the problem. Yep. People need extra energy. I understand there's a flywheel involved and there's like a cutout of it. What is this physical product that you're making? Yeah. So the physical product is essentially a battery energy storage system, but with a kinetic energy storage rather than chemical. So we're storing rather than lithium batteries, we're storing in kinetic energy form. Explain what that means to somebody who's not an expert in this. You're basically putting batteries into data centers, but they're different types of batteries?

42:20Essentially. 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 level out these spikes that the AI dinosaurs eat. 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?

43:00So depending on the size of the system that you're using, we see about a 95 % return currently from the power that you put in to the power that you get back out. And that's in our... Sounds very good to me. That is pretty good. 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 made? It's a carbon fiber composite. That sounds light. Wouldn't you want something to be heavy and kind of... 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.

43:38So 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. And how big is this rotor seed, the 10 kilowatt hour module that you're describing? If I went to put it in my hands. Yeah, so the current version that we have is basically an 18-inch diameter by an 18-inch long length, and that makes the 10-kilowatt-hour base unit. That's not very big. It's not very big. Does it vibrate? It does not vibrate. It is on magnetic bearings. So you can stack these. 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.

44:18So as long as they're not moving, there's no pushback from the wheels motion itself. So, okay, that's pretty awesome. What does it cost to build one of these? 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. Okay. And then for a 10 kilowatt hour battery, what does that cost today? 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 uh legitimate way and say you're buying like a fesla powerball that's pretty close to a similar uh energy density you're probably in the 10 to 15 000 okay so this is interesting i i asked producer claude to explain 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 etc yep 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 yeah so the original the original bit of this technology it did exist in buses, I believe, before the trolleys in SF existed, is by understanding that there were large mass spinning flywheels that existed.

45:55Wow. So this is like you're bringing back an old energy source with new modern materials. 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 fill these up, right? At certain times during the day. So you can do that arbitrage. You can fill them when energy is cheap, correct? Exactly. You can fill them when energy is 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.

46:36Every time someone wants to generate 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 let's 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. We saw this, Jason, with base power and Zach Dell. Oh, yeah, sorry.

47:09No, no, go ahead, finish it. Oh, I was going to say, we just had base power on, Chris, 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 lived with. 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 - ERCOT being Texas's. Yes, being Texas's. Which is completely deregulated and you can add and take energy out in a much more fluid way. Yes, they're much more free.

47:43Much more free. So I guess, would this also work for air conditioning in places where it's very hot? So you go Mexico City, Dallas, Houston, Austin, Phoenix, 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 yep you could power all the air conditioning you can do exactly that and something that if you weren't what there's a model like that or you can do something that's following what's the duck 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 tail end of the duck that curves up that is a high demand peak right when solar and generally solar starts to taper off.

48:40You can kind of play that arbitrage game where you're going what makes the most sense to charge up? Do you charge up at night when the base load is steady and the peak is 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 you can dissipate that when everyone's coming home and turning on their AC? 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 ai data centers are starting trying to get ourselves into it you look at um all these ev fast charge 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 to do 250, 350 or 500 kilowatt chargers.

49:29So 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. And your technical site could only have a 100 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 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.

50:04And if you... That's the duck curve. And here's the duck curve, as you can see. Yep. You know, in the morning, 9 a.m., then it goes 12, 3, and 6, 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 - Right at the worst time. 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 I guess they could also put their heat on. Sure. And it looks like a duck. And that's - It's a brilliant technology, but also it just goes to show how complicated the power question is between baseload power, variable power sources, and storage.

50:50But between exowatt storing industrial heat, base power doing batteries at the house, and hydro storage doing compressed air energy storage, and now we have on-the-fly energy using flywheels, Jason, I'm actually a little bit optimistic right now. 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 tribe, whatever it is.

51:28And with energy, one of the interesting things is the data is the data, Chris, right? There's a price of energy that you cannot fake. Yep. And it's well metered and it's reported at most places, easily accessible literally with ercott you can pull up ercott'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 You can just build it and it's cheap and clean and it's free.

52:09And 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. Chris, it's become very political and very sharp elbowed. 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. 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.

52:55Just on a percentage basis, where would you, you know, hey, get us the short term energy. get us the midterm, get us the longterm? How would you advise doing it? Obviously you have your own book and 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. 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 or power plants, I don't believe that coal is the solution.

53:24Maybe we're looking at other other forms there's uh 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 is falling in you get to get to uh 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 out the downside of renewables that is production fluctuation and unpredictability depending on where it's at and being able to store that and being able to redistribute that across the grid to where you need it.

54:04That'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, you'd be able to cover that entire grid and be able to be essentially entirely interdependent as a country. Okay. I have a question about scale here because in your your deck that we went through uh which by the way very nice appreciate that uh 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 uh why can't we make one of these at a city scale for example so the physics of it get really limiting so kind of what has advanced in the last 50 years from the heavyweight flywheels um is really a materials question and where we've come is these composite high-tech aerospace materials.

54:53And 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 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. that hoop stress is basically a function of the tensile strength material that you're making it out of on the outside diameter. And it's basically what's trying to burst this thing.

55:27It'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. So what if we put a large iron rod, like an old wheel, around the edge of the... I'm kidding with you. But my question is, why do we have to make this in small units? Why can't we just make large ones? 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, uh, scale factors where you'd have lower, lower, uh, number of components that go into it. Okay. Well, I'll, I'll, I'll just say, I like the small ones.

55:59I 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. Cause this sounds awesome. Like the first prototypes. Yeah. Chris, what's the story here with funding? I mean, I'm not an investor in this company. I feel like this is like a, going to 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. I'm funding it myself right now. Really? Yeah. That's my kind of founder.

56:26What's going on here? Maybe I can, can I, you got to, can you save a slice for JCal? I might want to get in. I will save a slice. I'll put a little sticky note right on the, uh, the cap deck for you. 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. Uh, 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.

57:01And they hosted this incredible pitch competition, which Chris, I don't know, you might be the leading, you might, you might wind up taking this down and winning. Hey, I'd love to hear that. 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. We'll do. Let's get some, I'm going to take you out for some barbecue and try and weasel my way onto that cat table. Great, great job, Chris. I'll drop Chris off. And if you're feeling inspired, head to gamma.app, A-P-P, G-A-M-M-A.app. So you can start working on your idea and you can change the world like Chris is doing.

57:40And maybe we'll see you on a future episode of This Week in Startups. Well done.