AI in K–12: Feedback, Curiosity, and the New Frontier of Teaching

Hi everyone. Michael Horn here. What you're about to hear is a conversation that Diane Tavener and I recorded with Lawrence Holt. And I wanted to highlight just a few parts of the conversation for you as you begin to listen. First, Lawrence named three primary use cases for AI today in education. Number one, generating materials, number two, feedback. And third, is AI tutoring, now the only one of those ready for primetime, in his view, feedback. We then dove into why it's crucial not to conflate feedback with grading and how, if we do so, it will actually undermine student motivation. Another part of the conversation that I thought was important to highlight is that Lawrence observed that to be instructionally useful, AI applications need to deeply understand what students or teachers are trying to get done and then build with that in mind. That means the tool needs to have a lot more context than a chatbot that any of us would just fire up on its own. And Lawrence doesn't believe we've gotten to the point yet where the tools we have understand the instructional context or have the right data on students. Finally, I thought the conversation around why AI tutoring is still falling short was very telling, particularly Lawrence's implicit observation that a lot of the blame is on a system of education that deprioritizes curiosity, developing self efficacy, and creating the time for true learning, and that it will take a lot to overcome that. Hope you enjoy our conversation on this episode of Class Disrupted.

Hey, Michael.

Hey, Diane. Good to see you as always.

It is. And what a fun season we're having here on Class Disrupted. I'm hearing all sorts of comments from folks, I know you are too, about the conversations we're having, which so far I would say have been pretty expansive at a higher altitude or a different perspective, which people love. But there's also a bit of a craving for a closer look at what's actually happening in schools. Which is why I'm really looking forward to our conversation today because we get to stay sort of at that bird's eye view with someone who's been tracking the full range of new AI powered companies, products, tools, programs and schools in K12, but also has been going deep with a few of those use cases. And I think it's going to be an awesome transition and into what I think is, I guess, spoiler alert, the next part of our season where we're going to go deep with a number of folks who are sort of much closer to the action.

Yeah, indeed. I think that's a good summary, Diane. And the person we have on today is someone I'VE gotten to feature on in my writing, my work in the past just because he seems to constantly be doing really interesting explorations and finding out really interesting angles on things that maybe were accepted wisdom and then we find out that, that they aren't what we thought. So I'm thrilled he's joining us today. He's none other than Lawrence Holt, who is a senior advisor at XQ Institute and the Teaching Lab. And along with several others, he created an EdTech Insiders map to track over 60 use cases for Gen AI in education and over 300 Gen AI powered education tools. He was previously chief Product officer at Amplify. And again, what I love, Diane, about talking to Lawrence is that look, he's an engineer by training who went back to school to understand how people learn. So dug into the learning sciences, neuroscience, cognitive science, and then spent years creating products that worked for or as he often says in his own words, didn't always work in classrooms. So I love the background he brings, his experience, his humility, his humor and his ability to, to dig deep. So welcome Lawrence. Good to see you as always.

Great to see you both. Long time listener, first time caller. Thanks.

Now we won't get to say that again, so I'm glad you're here. Let's start high level with the EdTech Insiders map and what it tells us. What are you seeing out there in terms of emerging tools and products? And have the use cases changed much in the past year or two, Just sort of help orient us to what are the big areas for entrepreneurship, product development and so forth?

Yeah, that's actually you hit a really interesting area straight up with a number of use cases. So we actually organized this map around use cases, meaning instead of just listing all the tools that are out there, thinking about what AI could genuinely help with and then cataloging are those indeed things that people are creating. And so you can, you know, anyone can see that for themselves. It's on EdTechInsiders AI. It's free with the help of our friends at Overdeck and we started in June 2023. So just after really six months after ChatGPT, Jacob Klein and I were trying to figure out how do we track all of this stuff that is bubbling up. And the first version had 40 some use cases and now we're up to 60. So it's not actually been that many. We've added hundreds of new tools. The number of use cases is slowing, which I think tells us that the sector has gone broad. We've sort of had a look at almost anything that you could improve with AI. And now we're going more deep. And in particular, the areas I like to think of sort of the big three use cases that have emerged over time, only really one of which is sort of is ready for primetime is AI good enough for. And the three I think of are generating materials. And when you interview teachers, there's survey, there's a great Gallup survey that shows that's the main thing teachers say they're doing with AI, so creating quizzes, assignments, lessons, role plays. There was a teacher who wanted to teach that science teacher wanted to teach vacuums in middle school, and AI suggested to her that she should do a role play where the kids were 1930s vacuum salespeople going door to door and had to explain to families like, how does this thing work? Which I thought was like, that's a really cool case. So that's on the map. And there are lots of others that might tweak your interest. But generating materials is number one. Number two is feedback. So actually commenting or giving input to students based on their work. So not just right or wrong, not just multiple choice, but could be their writing, it could be their math written work, which AI can now do. It could be a presentation they've made, so they're just able to get way more feedback than previously. And then the third is AI tutoring, where we've seen just a huge upswing in the number of tools. A lot of them were around coding originally. We're now seeing a lot around early reading and math. So those are the big three areas.

Super interesting. I'm curious if you see differences in these by grade level or subject areas, or also if you'd give some commentary on those three big areas, like where are they really good today, these AI tools and where are they still primitive and not ready for primetime and maybe won't be ready for primetime.

Yeah. So I think the one that is very definitely ready for primetime, in my view, is feedback. And this is partly because if you look at the amount of feedback the average student gets on their writing or their math homework, it's actually very low. And the reason for that is because it takes a huge amount of time and teachers just don't have the time to do all of that grading. So in a way, any feedback at all would be better. But there have been studies that show feedback is already AI feedback is already as good as, say, a median teacher. And if it's on writing, writing is the thing that these, that LLMs, large language models are really good at.

Does that depend on grade level or is it sort of equally distributed across a student's age for how good is it feedback?

I think it's been tested mostly in middle and high.

Okay.

But I think, I mean, we're certainly seeing feedback on your reading in very early grades. So I think it's like a lot of these things, it's kind of a jagged frontier that AI is good at and you wind up with specific point cases where it's very strong and others where it's not so great. So I really think of feedback as the first sort of, you know, fluoride in the water opportunities for AI. If we could just make feedback available free to every student K12 in the US or beyond K12, that itself could be transformational.

Lawrence, let's spend a moment on feedback because I actually totally agree with you, but I think that sometimes people don't understand the importance of feedback because I think feedback gets conflated with grading. So to your point, like as a teacher, it's, there's so much work to do and it takes so much time to get feedback. And oh, by the way, I'm actually not held accountable for feedback. I'm held accountable for grading and getting things in the grade book. And so often I think grading just like, did you do 1 through 10? Did you get, you know, gets conflated with feedback. But feedback is actually at the heart of learning. So just spend a minute there about how this could be literally game changing if we could get regular, constant quality feedback to kids that we're just, we literally cannot and are not doing right now.

Yeah, no, you hit it exactly, Diane. Because in most studies, meta analyses of what drives learning, feedback is either at the top or very close to the top. And if you think about it, whenever you've learned something, it is often because you didn't do it very well. And someone explained and pointed that out to you and told you how to do better or maybe multiple ways of how to do it better. That's the fundamental cycle. Grading, however, if it means coming up with a score we know can have a detrimental effect, it's so strange that these two ideas, which are very closely related, actually have almost opposite effects as grading can result in students focusing on the grade and they almost, they only read the feedback in as much to justify why they got the grade they did rather than actually taking it on board. So a critical part of feedback is having another chance. So if I, if you produce a page of writing and I give you feedback on it, you, I really need to Give you a chance to revise that, to incorporate the feedback. That's the learning. And with AI, it'll very happily generate to go over and over as long as you like.

Exactly, exactly. It's transformational. That was at the core of Summit Learning when we built it was this idea of revision. We called it revision and redemption because it was such a break from sort of traditional. You know, I remember as a teacher having my red pen. I was an English teacher and I would spend, you know, labor over giving all these feedback this. And then kids would look at the grade and then in the garbage it would go because there was no reason for them to read the feedback in their mind. The whole system was oriented, you know, towards just getting the grade and moving on. Super helpful. How many of these, you know, tools, products, etc. On your map go beyond chatbots? You probably know that I'm very skeptical of chat. Michael and I both sort of sit in this camp of. It feels like that's all anyone or not anyone. Lots of people only understand AI to sort of be a chat bot. And it's so much more. So how, how, how are you seeing the division happening there? Is there hope that we're moving beyond chatbots? What, what's it look like?

Yeah, I think that's, that's, that goes to the sort of. Sometimes it's called sort of horizontal versus vertical applications, where horizontal is ChatGPT. Right. You can ask it anything and it'll do a, you know, decent job in many cases. But then that has actually, I think, been the case for the, maybe the first year plus of what we were seeing on the map. Most tools were either chatbots or they were kind of thinly wrapped versions, let's call them, of existing large language models, which, you know, and again, those models, underlying models get better, so the tools get better. But to go further than that, we need, and it's not just our sector, I think all sectors need to start thinking about vertical applications, which is much harder. And that involves deeply understanding what, what kids or teachers are trying to get done and building with that in mind. It means a lot more context than a chatbot that you just fire up has. And in particular, I think we have not yet got to the point where we have tools that understand the instructional context. Like, what am I trying to teach today? Where are we in the curriculum? The pacing calendar and number one, and then number two, data on students. What is, what is it in particular that my class needs that's different from everyone else, either in terms of interests or Maybe assets gaps. Those there are I think of, I think no tools at all today that can take all of that into account and then use that to suggest the next most effective step for you or craft an activity or suggest a warm up. They are mostly doing that based on really, you know, almost no info. Mm.

So let me, let me ask this. You listed two other use cases that you're seeing as sort of the big ones out there, generating materials and AI tutoring. I'm curious how both of those measure up in terms of effectiveness. It seems to me on the I'll give you my prior and then you can push back on both. But on the generating material side, it seems like this is actually one of the things that the HQIM high quality instructional material movement has almost been trying to push back on. Right. Is we need more coherence, not sort of just lots of random walks of materials. So I'm curious how that plays itself out in classrooms. And then on the AI tutoring one, it's one that several of our guests have mentioned that they're quite bullish about. But I confess, at least what I'm seeing about like in actual schools, it seems like it works great for the autodidact learner who's like going to choose study mode. But most people are not engaging outside of, you know, when I'm walking my dog and have a nice conversation on a just in time topic that I that I'm curious about. I don't see a heck of a lot on the AI tutoring that has me convinced that this is really working. But I'm curious your take on both of those because you've looked at them much more seriously than I have.

Yeah, I'm hopeful for both, but I don't think either are there yet in materials. We've got. I think if materials means give me a quiz on, you know, on unit rate for my sixth graders, AI is pretty good. But if you go beyond that and you want it to adapt a lesson, let's say to take in particular context such as, you know, my kids need a reminder of fractions and also need to learn unit rate that involves, that's really hard task that involves knowing, learning science, knowing developmental psychology, empathy, what active learning, engaging kids, as well as the content knowledge. The models are pretty good on content knowledge. You know, they win math Olympiads, but they, they don't know the rest of those things and we lack evals, which is the AI community term for an evaluation, a way of measuring whether what the AI just gave you is actually good. In particular, we lack that for materials. And so they're actually worsening the coherence problem right now, for the most part, tending to generate yet more stuff, and the teacher's left trying to fit all those pieces together.

Gotcha. What about on the tutoring front? And I know you've been running some personal experiments here, I think so I'm really curious to learn from you.

Yeah. I been working recently with a group of middle schoolers in the Bronx, many of whom are multiple years behind in math. And I wanted to have the experience of being a long way out of my zone of proximal development, like they are. They're being taught on grade level, but they're missing many building blocks.

Yeah. Yeah.

So I thought, well, where am I? Horribly outside of my zpd. And of course, you won't be surprised to learn there are lots of places where I'm. But one in particular I chose was quantum mechanics. So I asked Claude actually give me a graduate level problem on quantum mechanics. And it did, and I could make absolutely no sense of it. So then I said, okay, so you're my tutorial, and I won't understand all the math, but I want to make sure I get an intuitive sense of what's happening here. Step me through it, never tell me the answer, and let's see how far we can get. And it took, honestly, about 45 minutes. But it was a fun 45 minutes, and I kind of solved it with so much scaffolding, I'm not sure it was me that solved it, but I definitely got a sense of what was happening. I then said, give me another problem. And I couldn't make any sense of that one either, but. But I had the feeling that after maybe 10, 12, 20 of those, I might start to be. At least I'd be ready for a course on quantum mechanics. So what I think I took from that was obviously I had something you guys talk about a lot. Curiosity that kept me going for 45 difficult minutes. And I knew how to ask and answer the questions. And when I could just say, nope, I could not understand what you said at all. Let's try again. Remember, all I have is high school math. And Claude would go with that. But the thing that I took away from it that I really had, that I see is much harder to get in middle school, is I had this utter conviction that I could get it however long it was going to take. I thought, really, there's nothing here that I couldn't, given the time I could get. So I just kept going. Whereas of course that's not true of a lot of kids who've been told for years that they don't know math and no one around them is a math person. And so they may not have that same sense of self efficacy to battle through.

It's what you're saying so important I want to make sure people aren't missing this. Let me think how to, how to ask a question that is, is going to surface that. So. We have a system of education that in many ways like disincentivizes curiosity. Right. Like we have so become so focused on like student, well, so many things. But like basically the, the well run classroom means that every five minutes or so a teacher is prompting a student to do something. There's like never a moment where they're actually just following their curiosity or, or doing that for a reason. And so so many of the pieces you just said, whether it be mindset or belief in myself or curiosity, are not things that we're encouraging or, and in fact we're actively discouraging in our classroom. So one of the things I get confused about is how do we think AI is actually going to come in and quote, change education when the uses of AI right now require all are literally counter to what the system and the model is. I know we are thinking about this. That wasn't a good question.

No, I can, we can riff.

We can riff. Go for it.

Yeah. So I think often when I see kids asking a question out of curiosity in class, it is seen by the teacher as sort of not on topic for today. Right. And I've got to get through this material. And I've heard some really great questions that got passed over. One of them in a lesson on the human body and circulatory system, a kid asked, so the body stores some of these things like energy. Why doesn't it just store oxygen? Then I could breathe underwater. And that's like, okay, that's a really good question. But the teacher had to move on. So AI of course very happy to answer those things all day long. And I think, Jayenne, this goes to something that I see in the classrooms that are used, not all of them, but the ones that are starting to use AI now I see a sort of AI effect which is the energy shifts. So if you go from a sort of teacher led discussion with only a few kids involved to okay, now let's write some short answers on this close reading we just did. And AI will give you feedback on that and engage you in a conversation and kids really are on task and are, you know, they may not always be on point because they kind of follow their interests and the AI has the job of kind of nudging them back. When I ask kids, do you like, would you rather go back to the old way of teaching? They say no, because. Well, firstly, interestingly, they say because I get more time with my teacher, which is interesting and counterintuitive. The reason being the teacher's spending less time just leading whole class sessions and actually can now circulate. And then the second thing they say is, I don't think anyone has ever paid such attention to my thinking as this, which again, sort of makes sense that who has time in a school when you have a class of 25 kids? But they really feel like it's someone, they say someone is paying attention to what I'm thinking and engaging with it. And that's new.

That's promising though. I think what you're just outlining, it goes to an intuition that Diane and I have had, I think, which is we've been most excited around AI in sort of the potential for using AI to create de novo school designs or de novo classroom designs that escape. Right. The traditional model. And that our contention, I think, has been that getting into new models, we would be actually very key to cracking the 5% problem that you've written about around edtech usage. Right. It may be great in the study, but only 5% of students in fact use it in the recommended doses. And it's not just simply layering the AI over the existing practice such that you still have the whole classroom model and perhaps not the room for that sort of individual attention you just described. In many ways, maybe you have to describe the 5% problem a little bit more in depth from your perspective for our listeners. But like, is that similar to how you see AI? Maybe could solve it, but it's not the AI, it's actually the redesign itself. What's your take on that?

Yeah, so much there, I guess I first want to say one of the issues, there's definitely several issues that we face with these sort of AI enabled classrooms that don't really require a new school model. I mean, I think that helps, but you can still introduce that into your high school English class. But one of the issues is when you walk into the class, it looks like a lot of kids looking at screens. And that's not what school ultimately should be. We don't want to be doing that all day. And I think we lack tools that can be more social. So imagine actually what I'm Doing is I'm debating with two other students this idea I have about what we just read. And there's an AI helping and nudging and just making us better collaborators and listeners. That feels like, A, that's a really important, durable skill, but B, it's just a better way of learning. So we don't. Right now there are no tools that do that. I think they're coming because technically it's possible. But the 5% problem to turn to that, Michael, that I wrote about was simply the finding that there are many tools out there. Khan Academy, iReady, IXL, several others that have actually great evidence that students learn when they use them, if they use them at the recommended dose. So it's a dosage question. And that dose is usually just as little as 30 minutes a week. And so they've shown that if for kids who use 30 minutes a week, they will learn, they will accelerate their learning. But then when you read the small print, it turns out that the percentage of kids who use these tools 30 minutes or more a week is about 5 or 6%. It's extremely low. And so the question is why? And the truth is we don't know why. But when it goes to implementation, enactment and any good. So literature is full of practices that we know can be more effective in classrooms, active learning, long list of things that, when done well, are very effective, but it's extremely difficult to scale them. So the really interesting question, I think, for AI is can it make it easier for teachers to implement, well, things that they. My experience would love to be doing, but the preparation would take too long. The core program doesn't really allow it. So I think that we haven't. Again, that's another area where we haven't seen any tools so far. There are some that will listen to your class and give you feedback on it as a teacher, but so far they are fairly rudimentary. I think I'm really excited about that area getting much deeper.

I'm gonna ask you to spend a minute more here on two examples you gave, because again, I think they're so powerful and I think they illustrate some of the blockers and challenges we have and maybe why people don't build these technologies. So the one you just said of how do we, you know, how do we have three students in a, you know, high school English class who are having a debate or a discussion, and what can AI do there where they're not looking at the. At the screen? But I think what you're hinting at, what comes to My mind is AI can actually listen to that conversation now, literally. And it can then offer feedback, literally real time to the three participants about everything from their amount of participation to the quality of their answer. It can prompt more questions when they get stuck. It could. In my mind, people aren't building this because they're terrified of like the privacy implications. What's the hardware that we're actually using that does that, what does that do to a classroom and all that? What do you think the blockers are and the limitations to this type of, you know, you've built things on the commercial side before. You know, what, what's, how's this, how's this market going to actually emerge?

I think, yeah, I think demand is the, is the question here. And the map that we created is really about supply side does give us some signal on if we see lots more AI tutors, then someone must be using them. And we do see that. But for this kind of social learning tool, there are some examples out there, but in a way we haven't structured the curriculum or the lessons that have been written today. We're not written with any of this content capability in mind. So I think it's up to publishers and others to start rethinking what could this look like. Now we have these capabilities. What you described an AI listening to me could be. It could be sort of like Alexa, but maybe less annoying. It could be your Chromebook. The technology is already there and it's actually already in a classroom. We now have great bandwidth in many classrooms. Not all of them, but it's more. At what point do I turn to that? So I think that is a question comes back to coherence. Because I know if I just introduce these new clever tools into my classroom, I may actually be damaging coherence. We might not be getting giving kids learning experiences that reinforce the big message, the things, the big ideas that we're trying to learn. And that comes back to my sense is the core curriculum providers really need to rethink how all of this can work for the new age. And I'm very excited about that.

Interesting, super interesting. We're talking about limitations and what you are seeing, what are you not seeing at the moment that you wish you were seeing? You know, you just alluded to some things that aren't getting built yet, which is these more collaborative. What else? What you know, when you look at your map, what categories are not there that you wish existed?

Yeah, great question. Right. Right from the start, we deliberately included use cases that we couldn't find Any tools that did, and there are still many of those gaps have been filled, but we touched on some of the big ones. Social learning is still extremely sparse. Coherence tools for coherence tools that help you implement. We talked about, I think also durable skill, you know, things that are close to both of your hearts. I know durable skills and experiential learning, which you know, is such an obvious use case that these tools could help with. But again, there's a demand question. If I'm trying to get through the academic content and even that's quite difficult to do in a year, in 140 days of school, then where am I supposed to fit in? An opportunity for kids to learn, to collaborate or to be creative or to think critically. Even though again, coming back to feedback, AI can listen to your collaboration and give you very simple pointers. It can help you be creative, it can listen to your presentation and help you improve it. That's all possible now. It's just finding a place for it in the minutes in a school day and maybe adjusting priorities so that, that's something that we care about. But I would love to. I know you guys focus on this a lot and I think part of what you're seeing is it's happening maybe more in micro schools and some other places, but do you see that any signs of that happening in the sort of typical traditional public school?

Not a ton. I mean, I think where I see it, Lawrence, is like when I think about some of the tools that have been out there, they're more around, they're more efficiency plays. Right. So they are framed to listen to the conversation in the classroom and be a teacher's aid to the work that they're already doing, which that's a perfectly good use case and probably helps a lot in a traditional classroom, but it's not doing the sort of rethinking of helping a student move from novice to expert learner and be able to have these sorts of conversations. I've seen some entrepreneurs approach me with the belief that they have these tools, but I'm not sure there's a market for it at the moment. I don't know. You know, to your point, maybe if the core publishers of which there's, you know, it's a different number and different names than it was 15 years ago, which is, is a good thing. Maybe if they led with it, maybe there'd be something different. But right now it feels like that's a really cool application. How are you going to get it into market? Is my. Is My observation.

Yeah. One of the CEOs of the, of a, of a big publisher said to me when I asked, why don't you already include durable skills and more and better experiences in your curriculum? And he said, just as soon as a large district calls me and says that's mandated, I'll do it.

Right. Yeah. Because they're following as well. It is why I think that the de novo designs, what John Danner, for example, is doing at Flourish is where this is a focus of his. But that's going to be a small market for the years ahead. So I don't think you're going to see maybe the commercial volume for some time.

Yeah, we're working on it. That's what, you know, I advise, as you mentioned, at XQ Institute and that's our key focus. So we're confident we'll get there.

I hope that you're right because I personally am not seeing anything that feels exciting or interesting to me yet on school design and that really sort of has a sense of what is possible now and then designs around that. That said, lots of conversations with lots of amazing people and some upcoming events where I think we're going to try to design with big imagination and see if we can just hopefully, you know, inspire some, some new models and directions. So I knew it.

Diane's solving the whole thing.

She's going to spur the field to design lots of different models, which, that'll be a good. We just need a lot more creativity and shots and goals these areas. I think that's, that's a big piece of it.

So, and it is a really, it's a sort of target rich environment. Really the number new opportunities that now you could not have imagined three years ago, things that are possible are all over the place. So I really think this is the time to be trying to grasp them.

Awesome. Well, we could talk to you for very long, many, many, many more minutes or hours and so, so let's make sure this isn't the last time that you come back.

Lawrence this season of Class Disrupted is sponsored by Learner Studio, a nonprofit motivated by one question. What will young people need to be inspired and prepared to flourish in the age of AI, as individuals, in careers and for civil thriving. Learner Studio is sponsoring this season on AI in Education because in this critical moment we need more than just hype. We need authentic conversations asking the right questions from a place of real curiosity and learning. You can learn more about Learner Studio's mission and the innovators who Inspire them at www.learnerstudio.org but for now, let's wrap today.

And as you know, we have this tradition of sharing books. We're listening, we're reading things, we're listening to. We try to stay outside of work. And I'm so proud of myself. I'm going to do that today, Michael. For it's a miracle. But. But let's start with you. Anything interesting to share with folks that that's come across your. Your screen or through your ears lately?

Yeah, so much. But I'm gonna. I'm gonna pick some things a little nerdy.

Okay, good.

Okay.

I'll be the opposite of it from what I'm thinking about at the moment, so.

Which is I've been sort of revisiting some classic books that I really felt I should. I should have read. Brothers Karamazov is one that people tell me is, you know, just so amazing. And indeed it is. But I've never managed to get to the end. But I've been doing that with an AI co reader. Now there are, and there are apps that let you do this, but I've actually found that that always winds up feeling like you're sort of trying to impress your professor. Which. Which I don't want to do when I'm reading. But if so I just have now Kindle open in one half of the screen and you know, and GPT say open in the other. And while I'm reading, I just ask it questions. So for instance, Dostoevsky was talking about the fourth estate, the press and how they were worried about it. And. And so I was asking GPT why were they worried about the 19th century? Didn't Pan out that way.

Yeah.

We got into a conversation about is the true same true about our worries about social media. You can tell I'm optimistic, but it was just a really interesting experience. I would encourage people to give a shot.

That's cool.

I love that. Yeah. Not dissimilar in that. That book in particular. Wow. I have quite a memory of a piece of that book that was very provocative for another day Today. So Slow Horses is this great series. This is not the one I'm recommending though, but I hear about it all the time because the lead character there's name is almost identical to mine. So everyone always asks me about that. I have no relation whatsoever. But those people who are behind Slow Horses have now created Down Cemetery Road with Emma Thompson. So if you're. If you're waiting for the next season of Slow Horses actually highly recommend this. It's the first season's not even done yet, but it's great. And Michael was showing me up and being more up to speed, so I had to come back with a little competition there, and. And this one just started in October, so I'm. I'm on it.

You are on top of it. That is awesome. Well, I'm gonna go back a little bit. I've been just sort of watching movies and shows with my kids, and so I'll see your Emma Thompson and go to 2022 with Matilda the Musical. That's one of the ones that we watched recently along with LEGO Masters, a few series and. And Karate Kid because I had to bring him back to a classic.

There you go.

And give him a little education while we were at it.

Was it the original Karate Kid?

The original Karate Kid? Yeah, yeah, yeah. I. I was tempted to give him one of the more recent remakes. There have been a few now. But I said we got to start at the beginning, just so you have some cultural references for what's. What's. What's to come in the rest of your life. So with that, Lawrence, huge thank you for joining us. Fantastic conversation. We touched on a lot. A lot more to dig into. But I like that we left it on an optimistic note as well. And all of you joining us, we'll see you next time on Class Disrupted.