Latest / The Innovation Philosophie Podcast / Agentic AI and Human Capital: Who Counts as a Worker?
Transcript
- Nathan: Hello and welcome to the Innovation Philosophy Podcast, the show where we look at the economics of innovation and the conditions that produce genuinely new ideas. I'm your host, Nathan Reardon, and today we're asking a question HR was never built to answer. What counts as a worker when part of your team has no passport and no pulse? The usual story is that AI arrives and jobs disappear, but... something quieter is happening first. Companies are putting AI agents on the org chart. Before agents replace anyone, who counts as a worker is becoming a design choice. Joining me today is my co-host, Pat Villaseran, founder of innovation philosophy, The Move and City Jam, who builds ventures by mixing worlds most people keep apart. Now Pat, if an agent can be onboarded, measured and switched off, is it a worker? PAT: The answer is yes, operationally speaking, if it's doing a function, it is a worker. However, we have to create a distinction around the definition of the word. This is where this entire episode is going to circle around. When you say worker, operationally speaking, the reason why, and we're going to repeat this again and again and again and again, because technology. is not the enemy. It should never be the enemy. We've gotten progress from horse riding to again, I love the Ford analogy three episodes back. We're still bringing that in in this episode. Nathan: Yeah. PAT: Because that's the most kind of like concrete era shift that most people have seen and ha can still remember. We just couldn't fathom the close analogy of that to what's happening with the technology right now because it's moving. so fast when before it happens from one lifetime to the next generation to the next generation. My grandfather to my father to me that's how the change in the industry used to happen. Nathan that is how the change in the entire markets and the entire industry used to happen. Right now, in both of our lifetimes, you know, as a seventy eight year old person right now. we are seeing probably, this is a probable number, about five generations worth of shift in a matter of two years. 2027's gonna look different, Nathan. 2028 is gonna look different. How scary is that? And so when we use the term worker as a Simple answer is yes, but we need to start redefining what that word means. Worker, in terms of operational efficiency, the answer is yes. They're making things efficient, they are cutting down the probability of human error. From a clerical standpoint, the data and the records are cross referenced across four different QAs, quality assurances. You can put that in a genetic workflow. Over agentic workflow, over agentic workflow, and the agents are solving the entire thing on their own. How incredible, right? They are a worker. But when we talk about human capital, that is where the difference happens. Nathan: So that sort of human in the loop phrase that everyone uses PAT: Mm. Nathan: to make AI sound safe does just putting a person at the end of the chain actually make anyone accountable? If I have an agent do a huge amount of work, but there needs to be... someone at the end who has a little prompt pop up, they click yes or no. If they click yes, are they responsible for everything that that agent has done? Good and bad. What does PAT: That is a really good question. That is a really good question. Yeah. Nathan: real accountability look like for an agent? PAT: Hmm. That is a really good question. That is a really good question. And this is why tech technology is not the enemy. However, it is also our we as humans, right? As the human capital. We have An accountability and a responsibility to match our skill set to the speed and how technology is evolving. For Nathan: Yes. PAT: me, Nathan, innovation is always about accountability. You can always blame someone else. You can always blame the market, you can always blame the thing, but that's the problem solving, that's where innovation really happens. And so for the context of humans versus agenci workflows. Right, this is where everyone in the chain of the process should now be knowledgeable on base foundational theories on how AI technologies work. If not, that question around accountability, that's going to be the biggest. And you have a data in here. You have a data in here, Nathan. Around by 2027, there's going to be a fatigue around agentich. And so actually, there's going to be a little bit of a slowdown in how agentics are going to be implemented across workforces, right? I have a different prediction around this, but let's let's let's go over that in the next few. Questions, but to go back to accountability question, the answer is the person doing the prompting is one hundred percent accountable. Nathan, on every single thing, on every single thing, right? So you and I have been testing on bots and agentic workflows over the past week. Whatever is supplied by that bot in terms of data. Maybe it's hallucinated. The hallucination happens with AI and agentic bots. Hallucinate. But if I didn't catch that, it is my accountability if I, you know, make a wrong calculation around something. It's going to be my 100% accountability. If the statistics are not matching the data set, it's my accountability. If it's saying something wrong to the audience, is my accountability accountable? crossboard. So human in the loop is the driver. Nathan: Right. Do you think we could potentially get into a world where you have all of these agents that are doing stuff for you PAT: Hmm, mm. Nathan: and then you have another agent who is the accountability agent before it then reaches you? they can, yeah. PAT: Another the thing. You know, I had a very interesting thread on LinkedIn, and it says if AI agents are so incredibly efficient right now, shouldn't we just be replacing CEOs? And another CEO said, Yes, we should. Yes, Nathan: Yeah. PAT: we should be replacing CEOs. And Nathan: You PAT: my I I actually do support that answer. Replace the C like take our jobs away from us. Really, because Nathan: Okay. PAT: we we're doing so much. We're doing so much. And so Nathan: Mmm. PAT: for us, like for sure, if you could do if you could do the job, then please take the job away. However, right? However, you don't you cannot strategize from top down still without the driver. We've got sports sports cars, different like 100 miles per hour. You have like You know, Toyota cars, sedans and everything, six seaters and then hybrid, again, right? We want to make it into a a consumable analogy. Mason. You have all of these forms and shapes of cars. I see them as cars, you know? But without you, you you drive. You do. I do I do drive too. I'm a very fast driver. I drive really scarily fast. The way that we it's the same car, Nathan. It's the same car. It's a sedan, it's a it's the same make across it's the same car. But the way you would drive, the way I would drive on that freaking countryside would be Nathan: Mm. PAT: different. Our passenger seats, princess, would feel very different Nathan: you PAT: in our driving scenarios, Nathan. That would be entirely Nathan: Yes. PAT: different as an experience. So agentic, yes, agentic. They they get you from point A to point B, even safely so. The car would get you there safely so from point A to point B. We're not even talking about the complexities of the, you know, the language models and this one and then agentic on top of agentic. Do that. Do 45 levels of quality assurance and agentic on top of each other. There was this testing that was done to benchmark all of the top AI. platforms in the world. And what this testing has done was to create, use different models, Nathan. And Nathan: Yeah. PAT: then they made their own cities. And then they let the the the agentic then built citizens of that world. Nathan: Bye. PAT: Yeah. Nathan: How did that go? PAT: This is how it went. So I'm not gonna name the name but everyone Nathan: I'm sorry. PAT: on listening on this episode today you could research this. This is available out there. But across the top three agents or agentic or AIs that we know right now, there was one Nathan that basically had didn't survive the civilization. Everything was burned Nathan: You're telling me that everyone wasn't just nice and pleasant to each other? No? PAT: It wasn't. They were voting on the type of government that they want to build and everything burnt down in one of the in one of the models. Nathan, everything burnt down. Okay. There was one that has transitioned into a unified kind of the i it is a whole sci-fi story that Nathan: Yeah. PAT: happened in real time. That happened in like right now, it happened. In our year 2026, it happened. The sci-fi thing happened. Okay. Nathan: Yeah. PAT: That you let just the AI do the thing. It was just incredibly curious that one of the models had burnt itself. There were fires because there were there were there were they used like a visuals on the on the cities and the thing, kind of like Nathan: Okay, yeah PAT: yeah, the the I forgot Roblox, kind of like Roblox kind of like reference and imagery and kind of like Nathan: Gotcha. Yeah. PAT: a game. So you could really imagine how the the citizens had built the thing together. There were debates around the thing. Civil wars, it happens, basically. The human history had happened. And the testing, it is insane. And so if we let them be, that might happen because the language model can only process data. It can process data at large. It can. It's Nathan: Mm. PAT: the biggest. Data pool in the entire world it can. The problem is there's no driver in it with human experiences. It per I mean, you know, I still cannot tell you that our society is perfect and humans are perfect and everything in between. But having the driver in the car allows us to still check where where are we going? Nathan: Right, yeah, yeah, that's true, that's true. Also, for the record, Pat's the CEO, she'd be being replaced by the agentic, I'm just the host of the podcast. Please keep me in a job, benevolent PAT: Tomorrow Nathan: AI. PAT: Not an AI. So this is actually a very important conversation for Nathan and I to have. But yeah, it is the driver, Nathan. It is finding the right drivers. And so if we go back to accountability 100%, everyone should be and also there there are new data points too, Nathan. When it comes to Because Chat GPT has, let's just say, has already had this adoption period across society. It's like you can chat with it, you can sudo use it as your therapist, yeah. talk about it as if Nathan: Yeah, yeah, definitely. PAT: it's your best friend, and it gives you a little bit of sort of comfort because it supports you. It's not it is for you, right? It's not it is biased for you, right? However, with with that, there are new very, very rough data right now that points to the to simplify the term, it dumbs you down. Because you're no longer thinking. You are you are from a human capital standpoint, you are giving away the creative thinking patterns that you should be developing as a muscle to a computer. The computer can process data and information way more than human beings, but you as a human, whatever. career you're in, whatever the thing is. And that's why even for for us, right, we have like massive reading assignments as if that that's that's part of like the reading assignments is not a joke. Read, read, write, read, podcast the thing, talk about, let's talk about this, right? Nathan: Yeah. PAT: Without that, we are going to be stuck. And our brains and our muscles and the formation of the brain too, you this, Nazin. That the human brain doesn't have a learning capacity. It doesn't cap out on like 40 gigs of RAM. It doesn't cap out in terms of like, I have this much data centers that can process this much data. It doesn't. That is the advantage of human brains. That's the advantage of analytical creative thinking for humans. And therefore, therefore. If our brains are so powerful in terms of development physiologically, how can you ever say that we are ever replaceable by technology that could get, in worst case scenario, you know, like in sci-fi versions, this data center burnt down, all of the data is done in. Where then is the, you know, the humans that's solving the problem? So you can replace CEO approvals. CEO functionalities in terms of workflows, Nathan. CEO data compilation. CEO, you know, the grub work that it takes to work a C-suite leadership position. But the leaders, imagine yourself, Nathan, being led by a chat robot. This Nathan: Yeah. PAT: is where we're leading the company forward. This is the thing. That doesn't move people. It is ne i you can you can agenda this on like one hundred levels of CEO functionalities, be the best CEO in the world. But Nathan: you PAT: that wouldn't move the team. The team wouldn't move from there. Nathan: So on the other end of the spectrum then, Stanford researchers PAT: Hm. Nathan: found that employment for 22 to 25 year olds in the most AI exposed jobs has fallen about 19 % behind their peers, mostly because fewer people are being hired. A junior work is where people used to learn their craft. If agents are absorbing that sort of work, how would you then PAT: Mm. Nathan: redesign the way people Learn, learn on the job. PAT: That is that is a very important question, Nathan. That is a very important question. So in Asia I had conversations with people around academia or people are working in in government bodies when it comes to the education aspect of a country. Yeah. one of the biggest problems Asia has a slower adoption when it comes to education, most especially the public. public educational system in some of the countries in Southeast Asia, for example. and you would see the models of the curriculum that they do have is not adapting fast enough to prepare the workforce of the future to be ready for AI. So your question is actually very valid and very critical cause for concern. For companies. Because if you don't have this segment, even even for my decision making, this is as transparent as I'm gonna go. If a junior staff is not catching up to the productivity of an agentic, where the agentic is doing the function way better, we have our goals, we have our milestones that we need to reach. I I will not, you know, I will think about it, give, you know, growth mentoring, you know, opportunities for growth. But if the capacity of the person could not catch up to the momentum of the initiatives of the firm or the company, we have to make hard decisions. We just have to make hard decisions because it it is a momentum, it is an engine, even with humans in tow. That's why you have collaborations, interdept. interdepartmental kind of like integrations with teams, right? We are gonna make the hard decisions, Nathan, for the the wellness Nathan: Yeah. PAT: of the entire organization. And so this is not a sole or one directional company problem. It is two ends of the spectrum, maybe even three, we need to bring the government into the conversation because it roots in two before they even step into the workforce, Nathan. It roots into education. If you don't have really strong educational backgrounds, really strong. Really Nathan: Yeah. PAT: strong. That's how deep the problem is. It starts from elementary school. It starts from Nathan: It's that foundational. PAT: it is. It is that foundational. So for example, in China, the kindergartens, Nathan, they don't they don't teach or even in different modalities, Montessori teaching, different kind of modalities around education for young youngsters. Finland's best education system in the world, you know, they focus in play, they don't focus on on on grades and like putting putting children into boxed in one hundred percent, ninety eight percentile, all of these things. Yeah. Nathan: Yeah. PAT: They focus on play because we have to be aware That it is the creativity in the process of thinking that moves things forward. That moves things forward. It is not we can, the human mind, it just is a difference around the left brain expertise and the right brain expertise. Right? But everyone, Nathan: Yeah. PAT: if it were just it's if if it's just about passing tests, you can memorize things forcefully so. Some can do it faster, some cannot do it faster. And even memorization, we now have frameworks and modalities on how to memorize stuff in. So if it is just about memorization and our education system across boards still relies on that system, this segment of young junior. workforce, we're gonna lose them very much so. And so and also for for startups, for example, that do not do not have the capacity or the time or the patience to to enroll people for that development program, not everyone has that leeway, Nathan. Not everyone would Nathan: No. No. PAT: It is going to be even more challenging for for the people who are just finishing. College, you know, to adapt, to adapt. So it is so foundational that let me go back to the China, for example, as a reference, what they they are doing at kindergartens, Nathan, is a lot of systematized structure play. So the physiological aspect of the children are trained on left brain, right brain expansion. Nathan: Right. PAT: So how do you write like what do you call that one that you can write from left right? Nathan: ambidextrous. PAT: Ambidextrous, right? It's the same, it's the same kind of training. They're not teaching ABC yet because what you need is the formation of the brain cells, the formation of the brain, and how that works, and then you put the theories and then you put the analogy and you put the creative thinking. It's a muscle forming practice still. And it goes again, Nathan: Okay. PAT: multiple different forms of education that is in advancement to the foundational level of this, Nathan. It really is a big, big, big problem. But if yeah, it is an accountability on the education system, the public sector, the public sector holds this, right? The future of workforce. So if they are not taking action, the public sector. Not everyone is enrolling in private schools, Nathan. The public sector has to have a massive accountability in terms of making sure. That from that foundational level, what we are developing is not testing modalities. It is the creative thinking patterns of the humans, how we're growing them into competitive beings and talents across boards. And then lastly, the workforce. Lastly, the workforce. How do we then embody a culture where everyone in the workforce is encouraged? and is empowered to approach problem solving from that creative essence. Technology is technology, but then how do you do the creative thinking aspect on your own? Nathan: So Klarna leaned pretty hard into AI for customer service. PAT: Yeah. Hmm, mm. Nathan: Then its CEO said quality had suffered PAT: Yeah. Nathan: and made sure customers could always reach a human instead. So PAT: Mm. Nathan: what does a story like that tell you about how companies are thinking about agents and AI? PAT: The shift around markets right now because AI has become a commodity. It's become A normal happenstance in everyday life. It's become Normal. You build an app, normal in a day. You build a platform, normal in a day. what then happens is the markets, Nathan, are arriving into this fatigue around AI. And so what we need right now is massive and deep human authenticity. So the Karna CEO, kudos to them and their team to be able to kind of shift that top down narrative that every single customer should should be able to talk to a human being. That's very important. That sets the culture up to yes, we're going to use and you and I talked about this. AI in in customer support is very relevant. You know, we can't just route people Because if we're gonna look at customer support, you want human beings to be solving the more complex questions other than did did where's my order? What time did this arrive? You want a human being to be solving more complex questions than it's gonna arrive on Thursday. You just didn't see the email. Right? So for us, it is about that ability to say where do we put the line in to make sure. That our clients and our customers are still served. With that kind of one in one human experience. Nathan: So you've got a company like Deal, for example, that already handles PAT: Yeah. Mm-hmm. Nathan: contracts, payroll, compliance for people in over 150 countries. And when it launched its AI workforce, it talks about a future where employees manage, hire, and fire agents. If agents do really join the workforce, Who should be onboarding them, paying them, auditing them, putting them on a performance improvement plan if they're not doing the job? What would an agent's contract need to say? Are we entering a world where PAT: Mm, mm. Nathan: I, or probably more likely someone who's actually technologically gifted, could create an agent PAT: Hm. Nathan: that then goes to work for a company? PAT: Again, we're going to go to the first two points of the episode today, Nathan. We have to clearly moving forward as a as as society, we need to start defining what workers are. Without that clear definition, even as clear as putting that in the Cambridge dictionary, we would be lost in the conversation because agents categorically. Is part of the workforce. They are part of the workforce. But are they human capital? I do not think so. So putting agents on a contract up if if the agents are provided by a a firm, for example, us, if we're providing the agents, then the contract then goes back to the firm. That is so clear for me because then the accountability for the agent's performance goes back to the provider. Not the freaking agents on their own. Do you see that? Because accountability, the agents would do what the provider asked them to do. The agents would follow what the provider, even with multiple layers of QA's, they're solving the problems on their own. Yeah? Google does this, Nathan. This is not impossible. Google is already doing the thing. Do having an entire massive, massive data center that's just doing the problem solving and then they're the agents are doing the thing. At scale, this is already happening. This is not something that is an impossible thing in the future. This is already happening. But Google still hires a massive portion of the United States GDP. Netflix still hires six seven figure engineers. All of the big, big, big comp tech companies still hire storytellers at six seven figures, Nathan. You cannot replace that aspect around human capital. So if you're asking me about the technical legalese around this, it is the firm or the one that is contracted to deliver the agentic workflow or the agents themselves. The agents could not decide on signing a contract. That's the difference for me because it is it is the difference the defining function of the word workers Nathan: Yeah. PAT: and then signing a con I would not be on a contract, Mason, with an AI. Does that make sense? So Nathan: Yeah. PAT: I don't think I don't think that that Case study, maybe there is a version of it as we're seeing in the next six months. That's how fast things are gonna go. Yeah. However, Nathan: Yeah. Yeah. PAT: I don't think I don't think that that would be relevant. I don't think that would ever be relevant, especially with a agentic fatigue that we're projecting as a downturn in probably Q1 of 2027, but not. I have a different prediction about that. Maybe we can talk about that in the next episode. But not to the point where we're signing contracts with agents. An AI agent. I don't think we are there. I don't think there are so many levels to it. See, could you imagine like the government contracts being, you know, cons constricted to or or or delivered by just agents. The age there's still someone controlling the agents. Mason. That is the person that signs the thing. There's someone still controlling the agents. That's the person that signs the thing. Nathan: I guess that goes back to our conversation earlier about who's responsible for the work that the agents are doing. So you still need that person there. Now you've built across music and consulting. Is there something from those worlds, the way a band or a production crew works, that leaders should borrow for running a team of people and agents? PAT: It is not about the industry. It is not about the industry nasal. It is about the philosophy, which is exactly our show. It is about the philosophy around innovation. And we are going to repeat this again and again and again and again. Finding the right philosophy around innovation is what solves the problem, not the other way around. We could think about frameworks, we could think about industry, on logistics, on the public sector, and the government and education. But it is the process of thinking and pausing, Nathan, that says, let me take a step back because someone is not solving this problem from this unique perspective. And that is why for innovation philosophy, we're always teaching founders. To always go back to what is true for them in their DNA, vision mentorship, yeah, in Nathan: Yeah. PAT: their DNA, and what is true for their experiences, because Nathan, the way you would solve our problems is going to be different than mine. That's why you have agency around our firm, our part of the firm. And so if someone else is doing agriculture, it's not about the industry, Nathan. It is about the identity of the founder. and their unique experiences in life and how you adapt that experience in the problem solving by removing all the noise around you so you're not copying everyone's solution to that specific case problem. Nathan: Right. So a founder listening to this right now wants to bring agents into their team without losing what makes their people original, without losing what sets them apart. You know, they don't want to just copy what everyone else is doing, but they want things to be sped up. What's the first decision that they should make right now? PAT: Good question. I would say Answer these questions. I'll answer the questions that I'm gonna give you, founder. The first is what is the culture about? Because if you are an AI native culture, it is impossible to say, we're we're not replacing a lot of the things with AI. You are an AI company that is counterproductive to the point of the development, really. So it is what is the culture about and what is important in that culture in terms of talking about culture, right? What sets the company and the humans that are going to join that culture? What is the culture about? What do you stand for? What do you stand for first? Because once you know that, what are you fighting for? Why did you build this? What are you fighting for? Why did you build this? What is this? What is the impact, Nathan? What is the impact of this? When you know the point of the build, you can then now create decisions that says, you know what? Customer support. We need people more on the development and engineers. And so customer support from a resource allocation, that's not something we're gonna spend hundreds and thousands of dollars just to have like human customer support at scale. That's not the focus right now. We need engineers who are going to really develop our AI platform. Right? that's the next thing. Now you can now you can say, okay, if the if the company, for example, nasing is a food company, you can still integrate a gentic booking, reservation, preferences, feedback loops. I didn't like the waiter. So now you're improving functionality, ordering systems, Nathan: Right, yeah. PAT: right? Now that is AI. Now you're not wasting. resources for the waitress to say, okay, this person actually likes sea bass and this person likes salmon and then this person likes it's chicken allergic. Everything, right? Now we can have a dashboard that is AI native. You know, we know our customers as if they are best Nathan: Yeah. PAT: friends. They come onto the table on a Friday night. We know exactly who Jessica is. We know exactly that that her uncle is this one. We know exactly all of these things. And so it feels like community still. Nathan: So rather than replacing what the people in the team that you've got, it's about being able to redistribute them to things that are quote unquote more important or will make you stand out more. So rather than just sort of, I'm going to replace everyone with AI. It's, I'm going to, yeah. PAT: Hmm, hm, no. Do not replace everyone with AI. What is the point? Majority of the things could be run by AI, but you have to know. Right? Those those questions at the top. What is the culture? What is important for you? And what matters in the delivery of your company and your Nathan: Hmm. PAT: business? So again, two different models. An AI native business needs AI engineers and crafters of the AI. Right? And creative people answering the ethics of what you're building. Yeah. Nathan: Yeah. PAT: You need you need doctors on ethics. You need doctors on this one. You need doctors on human society problems, right? Doctors. Philosophical doctors, not medical doctors. On the thinking capacity. We we do that with AI. but you have another business model where it is customer support, human to human engagement, optimization on on Food production line, because you don't want to waste anything in the kitchen, right? A different modality. And so the application in AI depends on answering the questions above. If you want, if also, like for example, if this fast food chain, yeah, and this also is already prevalent across boards that you have like waiters who are robots and just like it's running around, you know, they're adorable. But that solves the problem of like if I just if the brand is a fast food chain and I just need to deliver this from here to this table, right? And then my humans are optimizing on the taste of the food, delivery of the food, customer service, and Nathan: Yeah. PAT: not the walking aspect of let me just it's a fast food chain. It's not like a fine dining restaurant, right? Nathan: Yeah. PAT: It's the burger. Put the burger on the table. Put the burger. It's a it's adorable at as an experience, right? But Nathan: I've not seen them yet. PAT: It is. you you you should check those things. It's adorable as an experience, but that company also has a different why at the top, Nathan. It's Nathan: Mm. PAT: about the fun of the experience. It's about the thing. It's it's funkiness of technology. It is different. And Nathan: Yeah. PAT: so at the end of the day, for the founders, for you founder who's listening, impact maker who's listening right now, it is about those things. Answer the top level first and then Nathan: Sure. Gotcha. PAT: Execute. Nathan: So if we're looking far into the future, five years from now, you've already said that you think there will be, or no, that there will seem to be early 2027, some fatigue around agents and agentic. You don't necessarily agree with that. But if we're jumping five years into the future, what do you hope or think human capital will mean. PAT: That is a really good question. I love AI because it forces even for me to be even more intelligent or more competitive, just from a personal essence, Nathan. Nathan: Mm. Yeah. PAT: More intelligent and more competitive. More competitive, more competitive, more productive than I would ever be without AI on my sidebar. I will not be forced to grow. at this scale as someone who leads teams and who who is in the business of innovation without AI. If this was the industrial period, I would not have grown this much in such a short period of time. I would not. Nathan: Okay, yeah. PAT: Because you are not forced by the environment. The environment forces you to change. Right? You're you're in a tropical country, things are different. You're in a colder country, Things are different. The body's different, everything is different. But now the markets and the workforces are different. And so it forces you to become better. So you are on the top of the thing and Nathan: Yeah. PAT: not just catching up. And not just catching up. And so I actually welcome the challenge of it because it makes me grow faster. And so if we're asking about human capital, we could not necessarily we could make finer predictions on how it would go about. But my hope is that it forces human beings to look at the things that we have in life, whether that's education, right? Because students, you know this. there is a there are schools in the United States right now that implement about 98% of the classroom modality via AI. They have AI tutors. Nathan: Really? PAT: But yes, and they have massive high success rates, Nathan, in Nathan: Yeah. PAT: feeding in their students to top universities Harvard, Oxford, Cambridge, from schoolers who learn from AI tutors. So this we have to reposition our thinking into what is the function of AI. How can this make me better versus AA is taking the jobs away from us? Nathan: Right. PAT: So my prediction is not necessarily my my it is an integration of a prediction and the hope on how we are moving forward as human capital in the workforce. It is for us to be better thinking humans. It's gonna force us back to the basics needs and everywhere across board, it's gonna force us to learn how to write in notebooks again. 'Cause we have like no takers right now. You and I, we have no takers right now. But for for you, you let's be honest, Nathan, you don't really read the meeting notes right after. Nathan: I read the action items that the AI says that I need to do, specifically for me. PAT: Some of it. Uh-huh. Uh-huh. Exactly. Exactly. Right? We don't but just having the data is a good reference point. Just I know we talked about this, but like having a data, we talked about this last Tuesday. I know this is a part of it. Having that data, right? Do you see what the function is now, right? It is a function. It's a it's very helpful. Otherwise, hat. I reminded you of the thing. You didn't send that over. That was the thing that I sent over as a reminder. We didn't get the thing, right? But like I could not be accountable and say, like, but did you really? Did you really mention that on the email or did you really mention that on the meeting? There was no record. But now we have all the records. Now we have all of the notes in the world. But for you and I, you really consume the information that I'm asking of you because you're writing down the more important things on pen and paper. There will be a transition where we everything is gonna go analog, Nathan. Music, food. Everything is gonna go back to analog. Nathan: Right. PAT: Let the AI do the thing on its own. Everyone's Nathan: Yeah. PAT: gonna go back to bringing backpacks with just the books and the notebooks back into the offices. Nathan: Yeah. PAT: Everyone's riding bicycles now because everyone got lazy and everyone's got like, you know, flying cars. in five years, you know. everyone is going to go analog, even in the music industry, because you mentioned music. Every there is this big gross, massive growth, exponential growth nasin. Not only in vinyl, but in CDs. Nathan: CDs, really. PAT: People are buying CDs now. Nathan: Wow. PAT: We're going back. We're going back in time. That Nathan: Yeah. PAT: is the that is the prediction. And so the the academia, the workforce is going back to simpler times because Nathan: Hmm. PAT: we are no longer asked to do the clerical grub work of the thing. We are not, you and I, for example, right? There has been in the boomer generation, you have workforces that go in. To the office 95, 95, just entering, click, click, click, clock, clock, quack, clock. And it bores people out of their brains for 40 years. You have seen these kinds of movies and stories, and like working your life away. That's going to transition in five years, Nathan, where everyone is actually fulfilled with the jobs that they do because there is an input of their own feedback of creativity. It's Nathan: Right, yeah. PAT: not just about it's actually exciting. I mean, I gotta look at it from like a An optimistic version of the sci-fi Nathan: Yeah. PAT: future, right? It's so exciting because now I get to be creative. Now we get to play because you let the AI, you let the agents do the edits on the our podcast, Nathan. You let the Nathan: Yeah. PAT: thing do the thing. But we are having substantial conversations that make an impact. And hopefully, for you listeners out there, make a change inspires you. That is ultimately what we want to do at Innovation Philosophy. Nathan: Yeah. My, my optimistic prediction for the future will be if vinyl and CD are making a comeback, maybe one day it will PAT: They are. Nathan: have been cool to have had an iPod shuffle. PAT: An iPod shuffle would be I Nathan: Yeah. PAT: I do a pred I would predict that would be coming back to NASA. And there are other, you know, like more more fancy, fancier brands who are always already going back to the shuffle technology Nathan: Really? PAT: of it. Removing moving out of the streaming platforms because Nathan: Mm. PAT: then you just get to listen to the record, the full record, and you're not Nathan: Yeah. PAT: influenced by algorithm. Nathan: That is all that we have time for today. A massive thank you to Pat, as always, joining me from the move. Who counts as a worker is now a design choice. So design your mix of people and agents on purpose and protect the work that grows people's judgment and imagination. And if you like this episode. And if you have any questions, leave us a comment on the Innovation Philosophy Instagram. See you next time, Impact Maker.