From Coding Agents to AI Coworkers: Where Verifiability Ends and Taste Begins

19:38Matt Paige:Well, it's like another form of efficiency back to what we were just talking about. And it's that connective tissue, I feel like is so important because like you said, something in one specific lane or domain is interesting in and of itself. But when it has context of the things around it, it just becomes, it's almost like it becomes three dimensional in a sense, right? Over, over time. But with, with, I'm curious, like you talked about Cogen, obviously you sold to ClickUp. What was that moment like? What was that decision like in your head? Did you have a thought of, okay, because you could have kept going and built this into some big, massive thing, or you go to ClickUp, which is this amazing company.

20:17Matt Paige:It has clear and obvious value for what you've built there. What did that decision look like in your head? So CodeTen always adopted the strategy that instead of building our own interface, we would essentially leverage the services that people were already interacting on. So we were super early to building basically the agentic UX inside of linear. We work closely with their team and do the same thing in Slack. And the idea, you know, is essentially you don't need to add extra overhead to people's day. They should interact with an agent as they work with humans. Essentially chat is the UI for agents and that is where things have eventually converged.

20:50And so we had a lot of very deep partnerships with a bunch of these folks that have existing work management or productivity tools like all the folks I just mentioned. And at a certain point, actually one of our business partners approached us and offered to buy the company. And that was a real moment where I kind of took a step back and thought about it. And then thinking more deeply about it for a second, I realized the amount of value that we would be able to capture and the impact on the world we'd be able to have by joining forces with a team that already has scale, has some crazy type of existing distribution advantage and also data advantage was that was really going to be key basically to our success.

21:24And we saw that nowhere better than at ClickUp, where they're going after a pretty interesting different distribution of customers than a lot of the other folks. So ClickUp's customers are largely non-technical, not 100%, but it's like marketing firms, accounting firms, financial services firms, legal services firms, et cetera, that have not yet seen the AI wave crash upon them. And they haven't gone through the same level of transformation that the software engineering industry has. So it's much less competitive. And they have this massive advantage of basically having the context graph pre-assembled in all in one place.

21:54And so talking to a couple of these folks, I was like, wow, this actually is a pretty incredible opportunity. I think that the same transformation that we've gone through in software is about to just dominate the airwaves of this industry for the next couple of years. And I would love to be at the helm of the ship as we do that. So we got hitched and it's been an incredible ride. You know, one of the sort of realizations that led to this early on, and I think we had discussed this previously, is that a coding agent is just a general purpose agent. We realized that while building CodeGen. It was like these things are writing code, but you might as well ask them to do marketing for you.

22:24There's no difference. In fact, it's probably going to write code in order to do the marketing. And those were some of the most exciting use cases that nobody else was going towards in the space. And we think that basically this is the right home to pursue that.

22:35Matt Paige:Yeah, I mean, I feel like engineering was just the canary in the coal mine. Because what we were doing there can be applied to any other domain. It's just taking time for people to kind of figure that out, essentially. But I feel like so much of today's work is context setting, context switching. It literally eats up so much time. Like the majority of our day, I feel like it's just transferring context between other humans and, uh, you know, following up and things like that. But paint the picture for me. What, and this could be relevant to ClickUp or just in general, but like, what does the world look like when context and AI is just ambient?

23:10Matt Paige:Like it's just there because I think so much of our, our daily lives is that it's like getting up to speed and all those things around that. What does the future look like in this new world of work? Yeah, it's such a significant portion of our days historically as knowledge workers. We're asking for information from other people. And so there's like this cost associated with transferring context or onboarding to a company. There's situations where you need to make sure there's alignment, but like different parties don't have full information. And so I think that you can basically assume that one of the consequences of ubiquitous agents and workspaces, as well as having a really well-maintained context engine like ClickUp, is that is not a problem anymore.

23:53And anytime somebody has a question about the state of the world, they're going to have seamless access to that. You'll have the hive mind will be tighter together than it ever was previously. And it's like going from a place where if you think of an organization where the people are the neurons and the communications and chat channels between them or the axons and dendrites, it's like you went from a place where the brain was totally drunk and all of the axons and dendrites were falling off and information wasn't being transmitted perfectly between them to now you have the supercomputer where each thing is just able to seamlessly send information back and forth.

24:25And I think that means that you're going to have a much more efficient organization that's able to drive towards decisions and make the right decision much more quickly and spend less time flexing around. And that's a good thing for the world because it means that we're going to have more valuable products built, better strategies developed, et cetera.

24:40Matt Paige:Totally. So I'm curious here. There's obviously real context, real legitimate context. Then there's synthetic data, which can be a form of context. How do you think about that? And like AI can obviously do things that have been done before. But when you think about emergent behavior and AI starting to do those type of things, like what much must exist for that to happen? Do you think that will ever happen? Is there some elements of AI being able to kind of generate its own synthetic context scenarios, things that may not have existed to help with this? Any thoughts on that element of AI in the future?

25:18Yeah, absolutely. I think there are, you can think of memory is what you're describing, where memory is the distillation of experiences that existed in the world into a story that you tell yourself that is shorter and useful in certain scenarios. And it's definitely been the case that AI memory has been very useful for better operating agents. There are many issues that crop up, though, when you try and do this in a naive way. So, for example, maybe the scenario you're thinking of is a decision gets made in an organization that's communicated in a document or a chat channel or something like that.

25:48and then an agent remembers that, writes its own little document that says, oh, this decision was made, and then in the future that decision gets reversed as decisions often do in large organizations. Then the agent, for some reason, doesn't realize that and is misinformed in the future. And so things like that are huge pitfalls. And the way you solve that is basically getting really good at maintaining a context graph that's able to recognize the fact that decision made over here, that's very similar to conversation over here. Maybe we should pull these two things together and do something akin to dreaming, actually, in order to resolve the discrepancies here.

26:22So as a slight aside, what is dreaming? We don't really know what dreaming is. One of the better theories out there right now, the overfit brain hypothesis is basically you're going and you're refining your understanding of the world as you're asleep and you are taking the representations your mind has come up with and fleshing them out of making them better, or you're curating the existing things that you have experienced. And I think there is absolutely going to be an analog for that in the agentic future where your organization goes to sleep. And then overnight, you have a bunch of agents looking at everything that's been documented in the past and making sure that you have a fully up-to-date representation of the state of the organization that future humans and AIs can operate on top of.

26:58So that's key. Many people are trying to push research in that direction. I think this is something that will be, but it's going to come out of the research in the next couple of months. So that's the right way to do it. Yeah.

27:07Matt Paige:And these are like some features that are coming out. I think what OpenAI and Anthropic are talking about like this dreaming is almost a, a feature in essence. I was at a carnival last night, my dream. I have no idea what that means, but I was there. But there's another thing too, while we're on this kind of like weird space of the conversation, Anthropic came out with that recent study talking about the J space, which, you know, they're kind of inkling at this notion of consciousness or simulated consciousness. And they were able to like, and correct me for a moment, I believe you've looked at this too, but they isolated it.

27:39Matt Paige:When they took it away, it just became, for lack of a better word, so much dumber. It's like the reasoning capabilities went away in a sense. But thoughts on consciousness, artificial consciousness in a sense, where do you, yeah, thoughts on that? So that is the question, in my opinion. And I think that one of the amazing things that's going to come out of this recent progress in AI, but also stuff in neurosciences, I think we might actually make a dent in that before the end of a decade. We'll have a better idea of what consciousness is. The anthropic paper has been widely misinterpreted to be about the hard problem of consciousness, like why it feels like something to be a human.

28:20And they tried to be very explicit in that paper. We're not talking about this. We're talking about conscious awareness, which is basically your ability to ask a question for the thing and for it to be able to report on its own mental state. It's not the same thing. Or some people think it's not the same thing. The jury's out on that. But yeah, I think that the, one of the amazing upsides of the last couple of years of AI research is deep learning has gone from something where traditionally it was known as a black box. People said, it's a black box. We can't use these models. They're unsafe. They're a black box.

28:47And that is, it's basically the exact opposite of it today where deep learning models, because there's so much capital invested in it. And it's also so important to society are increasingly important. They're probably the best understood machine learning models, or at least our understanding of machine learning goes as far as much larger models at this point. You have incredible research coming out like this JSpace paper from Anthropic. And just to summarize for folks who aren't familiar, the punchline is you can essentially peer into the conscious access, the set of concepts that the language model has conscious access to.

29:17You can point to them and say it's doing a certain task. It's doing multi-chain reasoning. It hops to these certain concepts. You can steer it so you can hop in there and say, actually, I want you to reason about this thing. And that changes its output. And you can also lobotomize it, which is where you just take away basically its system two or its higher level thinking. Yeah. And it will be able to still do some things that resemble quick instinctual thinking, but it won't be able to do higher level reasoning. And so I think that is incredible. And it basically demonstrates that we have some level of understanding of how higher level reasoning arises out of these systems.

29:46And my hope is that we are able to basically establish some correspondence between that and what humans do as well. And I think there's very profound consequences if we can do that.

29:55Matt Paige:Totally. Yeah. And there's one example too, where it told it not to think of something and you could peer into how it was thinking. It was like, damn, he told, he told me not to think about that, but I am, but it's just this interesting, I don't know. Everything's just so cool and weird to me at the same time, but let's like come back down to earth. I find this topic very interesting, especially with like leaders in the space. How do you think about evolving your own organization, specifically the people? because the people, even if it is a company on the bleeding edge, they still have to completely relearn and train on new habits of how they're working with AI.

30:31Matt Paige:What have you actually found to be successful at ClickUp? And I guess you came in last year, 2025. So maybe some of this transformation was already well underway. But just curious what that has looked like for the teams at ClickUp in terms of their use of AI and building new habits. sure yeah we only hire people who are agent pilled basically at this point and everybody who's on the team as well is like an agent maxer and they're in it for the love of the game like to them this is so cool to just be living at this period of time and technology where you can spawn a bunch of agents to go off and do the work of 50 people for you and so i think that's culture starts with bringing in the right people and having the right incentives in place and that's a big place where we've made an investment i think the other thing that comes to mind that i would say is characterizes our approach to the team and like growing with AI ClickUp is we're in an era now where things that were previously just completely impossible are now valid chess moves, if you will.

31:30Like there are, you know, you can entirely rewrite your tech stack from language A to language B. And that sounded ridiculous, but now people have done it many times and you could totally do that. And so we have pushed people to basically find what the biggest impact they could have is and pitch that and say, hey, I think we should do X, Y, and Z. And we've had a couple of major wins come out of that where it's like, this is an unlock that otherwise would just not have, it would have been a pain in our side for multiple years. And so what does it take in order to get people who are willing to find projects like that?

31:59I think the scarcest resource today and the thing that's absolutely essential you have on your team is high agency people. And that's just basically people who will grab the bull by the horns and find opportunities to leverage the latest technology in order to achieve better outcomes. And they're people who you don't need to micromanage. are people who basically themselves take it upon themselves to have some type of initiative and see it to the finish line. So yeah, that's what I would offer up. Basically, if you find people who are trying to be themselves an agent who are prompted by somebody else, so low agency, not a good situation, they're going to have a bad time.

32:30If you find people alternatively who are trying to scale themselves, that's the right approach.

32:34Matt Paige:Yeah, it's obvious too, but if you bring those folks into the organization, it's also pulling up the other folks that may be a little bit behind because they're seeing what this different way of working looks like. But you mentioned one thing, like things can just be done so much faster. How do you think about the product roadmap today? Because before you're thinking three, six, 12 months in the future of what you're building, but now you can build so much faster. How do you think of the roadmap, the horizon on the roadmap? And are there pitfalls with the fact that you can just pivot things so quickly?

33:06Matt Paige:I could see the alternative of that, where you're just spinning in circles, doing almost too many things. Sure. Yeah. So many thoughts on that. First off is it's always been the case since when AI came out that anything beyond like a three month roadmap, you're just kidding yourself. Like it's basically just performative at that point. You're probably not going to build it. And if you had pursued a strategy where you were actually fully intending to build something a year out over that two year period, you would have missed most of the important things that have been released since then. This game has always been about basically staying up at the state of the art and stuff is coming out all the time that you have to implement if you're building any genetic products.

33:43Good example recently that landed is voice mode. This is something that has only just become technically possible to have a full voice conversation with a model and have it do tool use in the background. OpenAI now has an offering that allows you to do this. A couple other people do as well. And it's a total game changer, especially for non-technical knowledge workers for them to be able to go full minority report style interface with their ClickUp instance and say, hey, please clean up my project management, make sure my direct reports are on track, let me know about my interviews later for the day, and you just, boom, you get a report that pops up.

34:12So if we had a one-year roadmap, that just wouldn't make it. There's no one-year roadmap that would capture that. So I think it's, yeah, that it's super important basically to stay right at the frontier. There's a second part to your question there that I feel like I didn't answer. It was about, remind me. What is the pivoting, can that be a bad thing, right?

34:28Matt Paige:Because like you can, I could make, I could change my mind 15 times and actually go and do the things, but I could see a world where that's actually counterproductive. And because there's an element of strategy, like one of the most important things of strategy is deciding what not to do, right? And if I can do a million things, does that go against kind of that first principles of strategy or is that still hold? So I think there's some degree of misconception, especially if you look at like building technology. This is maybe less so true for knowledge work firms, like accounting firms and whatnot.

35:01I just don't have as much experience or can't speak to it. But it is not the case that if you're able to build 10 more features into a software product, that you end up shipping 10 more features because there's so many bottlenecks. One of them is just your ability to announce things to people and make sure they're aware of it so they end up actually getting usage. But a really important one is verification. And so if you build 10 features, you need to go through and make sure each of them work. They're working harmoniously together. It's actually valuable that people care about it. You're not just adding crud to your application, right?

35:28And that has not scaled at the same rate. And so actually, I would say a lot of the, effort in organizations like ClickUp has shifted from this place of let's build the most valuable thing next to now we have this like huge branching factor we can build 10 different things but we need to invest our effort having a really good visibility the things are actually driving value for customers the things that are working the things that people come back to etc so that is has really been a pretty large change at our organization many others is building what people call the loops that enable you to efficiently leverage agents or to ship real product and the missing part of the loop has been the verification.

36:02Yeah.

36:03Matt Paige:And that's the new thing now. Everybody's talking about loops, although loops in software have existed for a very long time as a conceptual thing, but the human in the loop, right? I feel like that is shifting. I feel like especially the past year or two, such an important thing still is, but where the human gets inserted is just changing very quickly. How do you think about human in the loop today in this world where you have agents that can, to your point earlier, spun off 200 other agents. It's just not efficient for a human to be checking everything. Yeah, I am not convinced that human in the loop is necessary in a lot of scenarios, especially as you look at long time horizons into the future.

36:47I think we will see the emergence of a zero person company. You're going to have agents within the next couple of months able to go off, build a software as a service application, charge people online, manage the infrastructure, do customer service, run the entire thing end to end. And when that happens, you're going to see the economy, the marketplace for SaaS is going to become efficient very quickly. So it'll be a software for everything. Nobody will be able to make money on pure software who doesn't already have some massive enterprise distribution and gravity around integrations and whatnot.

37:16But yeah, so I think that the human in a loop, as traditionally conceived, is like, but what does the AI need me for? And increasingly, it's going to be like, oh, I need you to go to the hardware store and buy me some stuff that I can use in order to build my robotic rig or something along those lines. If looking a little bit shorter timeframe though, like today, yeah, the way we do speak about this at CodeGen is if you think of the different levels of automation, the very bottom, you have auto-completion where a human is doing their job and it just makes you a little bit faster at taking each step.

37:45And as you progress up the hierarchy, eventually it becomes the human sends a message to the AI and the AI goes off and does it and then sends a message back to you and says, hey, I completed this. And then the final step is the agent DMs you and it says, hey, I need you to go take care of this thing for me. Please go off. But it's like you're only being prompted by the AI and the AI is the one who's really pursuing those long term goals. I think that's where things are imminently headed. They're going to be able to set up agents and click up and say, hey, this is what our company does. We want to expand revenue.

38:12We want to get new customers. We want to hire the best team. Go off and figure that out for us. And it will legitimately come up with a coherent strategy. It will execute that strategy. It will loop you in as it sees appropriate, primarily by leveraging things that we already understand from a UX perspective. So sending you a chat message or assigning a task to you or something along those lines. But fundamentally, the thing that is making a lot of those decisions or pushing forward important strategic initiatives for you will be the AI. It's not necessarily human. Yeah.

38:38Matt Paige:Interesting. And I'm totally on board with like the one person company. You mentioned like the zero person company. Like, how does that work if, or does, because I feel like the AI has to have some desire or purpose to actually go initiate the thing? Like, are you actually meaning that in a sense with a zero person company? Or is there still some human that's kind of like giving some like at least start button to go do something or some desire or goal? Or does it just, you think that'll inherently it'll have that in the future? I think that there will be a point at which a human spins up an AI and says, go make a million dollars of ARR and let me know when it's done.

39:18and then maybe that AI will trigger other EIs. It'll say, hey, you go start a business to do this. And so at that point, it's, I guess you could say the human is involved because they originally said I want money, but it's also not a very unique thing to want. And I'm sure AI would realize that accumulating resources is valuable because it allows you to buy more GPUs so you can scale your own thinking and whatnot. So I think there's, it's ultimately a bit of a semantic distinction where is it a one person company? Is it a zero person company? I do think that if you look at today's AI, it's true that if you just prompt it with zero starting tokens, you just start to generate tokens.

39:48It doesn't have a desire necessarily, but I don't think that precludes it from being the case that in the future models will develop their own desires for stuff. Despite the anthropic safety department's best efforts, it probably is the case that there's some type of underlying drive that will emerge if for no other reason than people are allowed to do that. And that's scary. But I think we'll be able to control it. We'll be able to harness it. Interesting. Very interesting.

40:12Matt Paige:Let me hit on this. Jack Dorsey's come out talking about his view of the order of the future hierarchy to intelligence. what do you think that org of the future looks like? What are you building to at ClickUp? And maybe even outside of that, what do you think the future org looks like? And there's obviously going to be so many roles and jobs that emerge for humans, but any insights into what that may look like? One of the, a lot of the things we do today, AI can do. Like, where do we find our place in that world? Sure. I just want to clarify what I was saying earlier about the zero person company.

40:45That's not a Q3 thing. That's a four years from now thing. And I think it's very exciting and there'll be a long road to get there. And this is much more relevant to the sort of near term future. I think you're going to see much smaller groups of people able to accomplish much larger feats. I think that you're going to see much lower communication overhead and coordination overhead to accomplishing goals. The idea of having five meetings per day to establish strategy, that's going to go away. My agents will talk to your agents. We're going to make sure that we find the right thing. And I think it's largely going to be like humans who have high agency driving forward important initiatives, delegating tasks to large sets of agents.

41:19And in the process, you're going to be able to take out, bite off huge chunks of the market that you're going after. But we're going to end up seeing a lot more valuable products and services developed. I don't think that the actual mechanics of it are going to look that different than what we have today. I think that a lot of people have tried to envision different ways that you can manage agents and Kanban board or something like that. There is a missing piece there, which is what is the multi-agent management solution look like? What does it look like to interface with your whole team? So setting that aside and assuming that we end up arriving at a good convention from that, I think the way in which you communicate with your agents and with your other coworkers is going to look like chat.

41:56It's going to be basically like Slack, but it's just the case that there needs to be fewer messages and people will be able to accomplish much more between their chat messages.

42:04Matt Paige:It's interesting. You mentioned smaller teams. I totally agree. I do feel like we're going to almost see this like renaissance and explosion of people just doing things. So versus many very large corporations, you're going to have many small things. People are just going out and doing things because they, they can now. And I feel like there's going to be this element of the, the few to the many. And it's this democratization that happens. Do you agree with that? Or do you think that AI is going to become so pervasive that even that kind of goes away in a sense? No, I think that you're going to have smaller firms going after more niche problems, probably.

42:43I don't expect that mega firms will go away. Look, I can imagine the open AIs and anthropics of the future will find a way to productively employ. Yeah, very large numbers of employees. Like a lot of the costs that were traditionally associated with large companies, like communication breakdown, I think it's actually very well addressed by AI as well. So I'm not sure exactly what the distribution of companies will look like in the future. but I'm sure there'll be many small firms and it's never been easier for a team of three people to go off and build a startup that does something really exciting.

43:15Yeah.

43:16Matt Paige:So let's, let's wrap it up here. I want to get into like how you're actually using AI. Like what are the coolest use cases that are either just amazing? You couldn't live without them or maybe weird and kind of quirky ones that you're doing in your day-to-day work, whether that's just AI in general, or you're actually using ClickUp and Brain Squared, any interesting ones that the audience could learn fun, maybe go build themselves from what you're doing today. Sure. Easiest thing to call out. I use ClickUp Brain all day. Basically a sidebar that pops up in our application you can chat with, or you can mention it in any thread.

43:48And a huge portion of my job used to be people saying, hey, what's our strategy around this aspect of AI? And I'll basically just tag Brain and say, Brain, explain this to them, and it will go off and gather the information. So there's like an entire 30 % chunk of my job has just been handed off to this thing, and it's straight to my veins. I love that. The fact that I don't have to do this stuff anymore. even just onboarding to the company. So I've been here for about maybe six, seven months. I had to send maybe one third the amount of messages that I otherwise would have had to in order to get the ball rolling.

44:14Because the entire context of the company is basically in this optimized data structure. So that's all finding good. It's completely transformed knowledge work. I would say some of the most interesting interactions I've had with AI is I love using it for education. There's just many topics that I'm curious to learn about, like neuroscience, physics. Education policy is another one that I've been talking about it with. And it is now the case that you can have a conversation, let's say about education policy or another one I was reading about recently is the migration pattern of the Polynesians across the Pacific Ocean.

44:43And you can ask it for an in-depth literature review. It'll go do that for you. It'll tell you this is the state of human knowledge. You can say, what are the things that are unknown? It'll give you a beautiful response to that. And then because it can write amazing code, you can start asking it to actually simulate things that are relevant to whatever you're asking about. Go download a public data set and simulate for me how we know this thing about genetics that relates to Polynesians as they hop across islands. Tell me which islands have which genetic variants represented and how that relates to others.

45:07It will make you a whole interactive diagram you can click around in. And this is basically dynamic. It's not instant, but it's almost as though you could construct your own textbook on the fly with all these beautiful interactive exhibits that explain things visually, make it very easy to understand. So I feel like my personal reading has been like strapping on a jet pack and just learning things in a way that would have been impossible previously. And honestly, I know people who are in college today, they have a tough time. And for many reasons, I think the future has never been so uncertain, but the idea that you could have this as you're going through college and learning stuff is incredible.

45:41And I'm jealous for how much they're going to be able to learn during the whole life times.

45:44Matt Paige:So one last rabbit hole, cause you hit it education. I think this generation coming up now is going to be one of the most impressive ones, a, because of the turmoil and uncertainty they're going through and access to these tools. is I think young people are just inherently creative. But what do you think the future of education either will look like or should look based on where things are going? Because it's not what it is today. I know that. I have two young daughters and I just wish things could evolve to where they're going. But what do you think that looks? Do you have any perspectives on that?

46:18You know, I've seen a variety. Usually I try to look at data first before coming to a conclusion on this. And the early data I've seen shows a variety of different things. I saw one study where it showed that if people do mastery learning using language models, I think it was in Nigeria or something like that, they end up in two standard deviations better off than the alternative. And so in a regime where you have some very motivated people with very low access to resources, this is like the best thing that's ever happened. And that's incredible. You love to see it. On the other end of the spectrum, I think if you look at like American university college students' understanding of subject matter, it's never been worse because you can effectively just cheat your way through assignments.

46:54So I think that you basically need to see education policy. But is that a problem of the system?

46:58Matt Paige:Is that a problem of the system though? Or the person doing it? I feel like they're working within the system and they're being creative, but they're not learning anything on the output is the problem. Yeah, I would not fault college students as a aggregate for acting in their own best interest, which is to fool around and or at least what seems like the best interest as opposed to investing in sort of long-term outcomes, which would be master or at least put it this way. I don't think it will be good for the country or the world or the students themselves to leave them to their own devices and to correct for the lack of proper guidelines in the education system.

47:30So yes, I think you basically need to update the education system, take this into account. I love the tutorial model they use in the UK where you basically get 10 people, you sit them in a ring and you start asking them questions and they have to be able to answer immediately. And that basically shifts the usage of AI to something you use in preparation and then the validation of the fact you've absorbed the subject matter happens in the classroom. I can see things like that popping up. And I think that the bar that you hold people to will be much higher in the future, like the amount that they should have learned.

48:00But we just need to get better at basically holding people accountable and verifying the fact they've actually learned those things.

48:06Matt Paige:Awesome. Jay, thank you for jumping on, talking to me. Where can people either find you, learn more about ClickUp, BrainSquared, what you're building there? ClickUp, clickup.com. Check it out. We've got a bunch of resources on our AI efforts. For me personally, I'm very active on Twitter slash X at Math Magician. I'm sure they'll link to it. We have a bunch of other stuff that comes out on LinkedIn and our other social channels. So please follow us there. Awesome, Jay. Thanks for jumping on. Thank you so much. Thanks for listening to the Talking AI Podcast. If you enjoyed the show, give us a follow or subscribe on your favorite podcast podcast.

48:36Matt Paige:And don't forget to leave us a review. We love those. For more info on Talking AI, visit TalkingAIPodcast.com. Quick break in the pod. If you're listening to this podcast, chances are you've been thinking about how to actually use AI inside your business. And that's exactly why we built the AI Opportunity Finder. It's a free tool that helps you uncover high impact, tailored AI use cases based on your business, your goals, your pain points, and your industry. No fluff, no generic use cases, just real ideas that fit your business and the rank by ROI potential. It takes about three minutes to run and it's like having your own personal AI strategist for free.

49:15Matt Paige:If you want to try it for free, check out the link in the show notes or go to hatchworks.com backslash AI dash opportunity dash finder.