The Future of AI, Revenue & Work: What GTM Leaders Need to Know Now

This is business.

Business.

This is business.

Ah, that sounds all right.

Artificial intelligence is transforming how businesses operate. But what comes next? This panel explores how AI is reshaping go-to-market strategies This was originally recorded at Go-To-Market Live last August, and it is so relevant today, even more now than before. This panel features leading voices in AI and operations, including Aditya Gautam, Tech Lead in Machine Learning at Meta, Jason Lowe, Professor at the University of Utah and host of the AI Diatribe, Kelly Chamberlain, CEO at nClouds, an AWS partner, John Bradshaw, President of AI Utah and Codebase, and Mason McMullen, VP of RevOps at Alicio. Together they are sharing their expertise on how AI is shaping business strategy, operations, and go-to-market execution. It is an incredible panel. You don't want to miss it. I was on the edge of my seat and so is everyone else. During the panel itself, I think you'll find it just as compelling. All right, I'm really, really excited about this one. I'm excited to introduce many people who, 5 people who are absolute experts in AI. The first one is Aditya Gautham at Meta. Round of applause.

Woo!

Hello, thank you, Arisha. Next is Jason Lowe, professor at the University of Utah and founder of Aptivon. Jason!

Woo!

Thank you so much. The next one is Kelly Chamberlain, CEO at nClouds. Kelly!

Woo!

Next is John Bradshaw, President of AI Utah and CEO of Codebase.

John!

Woo! And last but not least is Mason McMullen, VP of RevOps and Strategy at Alicio. Mason! Awesome! Okay, I'm gonna pull this one chair over, and what I'm gonna do is, I have questions, like I have lots of questions that I've written, Hannah's written a bunch of them too. But what I feel like from what I've been hearing from you guys is that you guys really want to ask the questions to the experts. Am I right? Yes. Like, I'll ask— I'm just going to get one to get them started, and then I'll just come around with the microphone. Okay. All right. Here's my question. Here's my one question. Would you please introduce yourselves and a little bit about why you're so passionate about AI? Go ahead, Aditya. You first.

Uh, okay. Hi everyone, I'm Aditya. I'm currently working at Meta in machine learning. Uh, AI is one field which is like actually changing and like in a way right now, especially after that, um, LLMs and the agent AI that has never seen before and the dramatic changes it is bringing into our life and also in the technology. That is amazing. That is super I mean, amazing to see. So that's why I really love and enjoy being a part of this field.

Hi everybody, I'm Jason Lowe. I am a podcaster about AI, in addition to being a professor at the University of Utah. I am passionate about AI ever since I saw the robot Maximilian in the movie The Black Hole. Yes, there we go. That was scary enough for me to really get into that. So I've been When ChatGPT decided to go public with its fun stuff, I jumped on the bandwagon and have been riding of it ever since. So that's me.

My name is Kelly Chamberlain, the CEO of nCLOUDS. I don't know if it's passion so much as absolute necessity to understand what it is and how it impacts the business. So my passion is about survival and capitalism is why I love AI.

My name is John Bradshaw, and I started AI Utah. And the purpose of AI Utah, why I'm passionate about it, is I feel like Utah has a lot of really strong talent here, but a lot of the individuals didn't know each other. And so a large purpose of the mission is to connect other people in that space, help people identify the nucleus of talent, and then allow those people to share and promote their learning as well.

Mason McMullen. I'm the head of RevOps and GTM strategy at Elysio. And I'm passionate about AI because we're an AI-first startup. So it's in the blood. And I think that I'm not biased or anything, being a RevOps guy, but I think there's a lot of interesting applications for AI in revenue. And I'm excited and happy to be on the forefront of that and feel very lucky sitting up here with these smart gentlemen to talk about it.

Absolutely. I'm so excited. And also, as it happens, this movie trailer that just came up is so pertinent to our discussion, isn't it? I'm like, what? They know us. Crazy. All right, so who's got— Dave, if you can hear us, there's a movie trailer going on behind us, which is great. You got it? Okay, cool. All right, who wants to start off with the most burning question of AI that they have? Who wants to start? Oh, you guys don't have any questions? I have a million questions. Nobody's got one yet?

Yeah.

Tell us your name and your company.

Garrett Blood, KJ.

Where do you see AI going in the next 24 months?

I know it's doubling every 6 months.

It's supposed to do that for the next 8 years.

What are we looking at in 24 months from today?

Sure. So there are multiple dimensions to look at it. Like, as if you look at the raw capability of LLMs, like the text is almost at a benchmarking. We are going to see a lot more improvement in the audio, video, and images capabilities. We are going to see like a phase where like you just give a prompt and it will generate a 15-minute like high-definition 4K movie, which is like as good as the best director. That would happen in the future. So multimodality is one aspect where it'll kind of like go. And the second thing is that the integration layer, it will be like you will— we will be seeing AI integrated like very well in all components of our life, not just chatbot. We are going to see like an OS where you don't have to click 7 buttons to 12 buttons to book an Uber. To do a meeting, you don't have to go like to 10 buttons and click and look into like your email document and everything. It will be just through voice. So we would see a lot more proliferation of AI in like in our daily life and underlying capability of LLM and agentic AI that is going to improve a lot in multimodality stuff. So, yeah.

I think you need to pay attention to robotics. You want 24 months? I mean, with the agility of the robotic body right now, at least in humanoid form, having the advances that it is, and looking at China— sure, we're winning the AI war. Are we winning the robotics war? I'm not sure we are. And what differentiates a fully capable robotic body that has full tactile capability from an electrician, okay? The knowledge in the electrician's head. Well, with AI, you can take that knowledge and put it in this AI body of a robot. So I think robotics is going to be an area that is completely overlooked, at least as far as the economic and the work impact in the United States in the next little bit.

Whether this goes in line or not, I think that AI is technology, so we look at cloud adoption, just whatever that looks like. In 24 months, in my opinion, it's just the pace and speed of business. So what we're looking at AI right now is accelerating certain tasks. But as we look at it, the access to the alignment with the customers is going to be so fast because they'll have knowledge that's replacing us if we're not more and more relevant. So we're going to have to be faster at what we do, better at what we do in that differentiated space. So It's just more consumable right now. I think it's— I mean, ChatGPT is very consumable, but it's going to be very much more productized and like apps are today. It's just consumption model I see is what it's going to look like. And so now it's going to be the pace of business for us. That's how we view it.

I see us working with fewer apps and more screens and more of an— more data from companies aggregating and working together. So, a much more simple life with the complexity behind it that you don't have to worry about.

Yeah, I mean, I'm going to talk about this from a purely RevTech perspective because that's kind of the space that we operate in, the space that I'm familiar with. I think the biggest thing we're going to see is you're not going to need data transformation in between your data and AI. And I think we're already starting to see that play out in the market and with technology and its acceleration as fast as it's going. You know, there's a lot of companies that are kind of sitting in that space where it's like, you need good data and you need to transform your data from source to actually get your AI to work. And I think we're going to be far past that in 2 years for sure.

That's awesome. Have you guys seen Whitney Merrill? Where are you? Whitney, remember what you showed me about Scotty with the interfaces and Do you want to just explain that metaphor for one second? Because it's so pertinent to what John just said about screens. And then Dylan's got the next question.

So the metaphor is Star Trek.

And so we're living now in the world of, you know, building the ship while flying. Well, this is going at light speed, right? On a starship, right? And, you know, we have engineers who they only run the ship. Because they've got AI, because they have AI with them. And this is the whole concept of, I don't even talk, I just have a light view on my dashboard of the enterprise that's there. But we, we look at that as a dashboard, but it's really AI. It's the computer itself. And that's the metaphor.

I love that metaphor. Thank you so much. Okay, Dylan has the next question about AI, and then we'll go back here. Thank you.

Thank you.

My name is Dylan Ferguson with Fullcast. I have 7 children, and I'm seeing a lot of entry-level jobs leaving the marketplace that would usually be used to train you to become a ladder mover or a future owner. So especially for Jason at the University of Utah, how do you see the education system changing to accommodate for AI? Because most of my kids, are even allowed to use AI in school. So how are we training them and how is that model going to perpetuate bringing us the right kind of candidates into the workforce? And then for the rest of the group, I had a question. A big challenge we're seeing is that with the next layer of agents, the browser-based agents, they're going to be able to surrender the control we're going to give them access to systems, passwords, usernames. What are your thoughts in terms of how that affects both the softwares that we're putting out in the world and the security we have to deal with? And what are the opportunities that exist there?

Well, to answer your first question, which is a really, really good one, um, it's really interesting. When the calculator came out, there was a full-blown revolt by parents because they didn't want the calculator to be used in school. And obviously we know where that went. I still know how to do long division. I know how to run a calculator. You can still do the thing, but the calculator certainly aids and abets my ability to do my job or to do my things. AI, at least as it stands right now today, before we hit the AGI level in the next— well, according to OpenAI's teasers today, maybe tomorrow, who knows? But until we do hit that AGI level, AI is just simply an augmentive tool. It's not a replacement tool. And so what I am focusing on with my students and what I know other people at the University of Utah are doing is we are not discouraging people from using AI. In fact, we are encouraging it. And I think the teachers that are discouraging their students from using AI are doing themselves a big time— are doing their students a real bad disservice. Because, I mean, if you can use a calculator, why not use a calculator? If you can use electricity, why not use electricity? You just have to do it. So I, I know that it's going to affect higher education. How, we don't know yet. Um, there's a lot of things that are going to happen in education as it relates to AI simply because People can go to ChatGPT and they can learn a whole heck of a lot of things right now. You don't need a teacher if an LLM can tell you a lot of the things that it's already found via research or in what was in its training set, provided it's not hallucinating. So, uh, to be determined. Let's just leave it at that.

I kind of want to comment on this, Dylan, because I'm passionate about this topic. Uh, I was, I was helped early in my career by, by mentors that bought into, bought into my skill set and helped me develop the skills to become a good employee and to improve and to grow into roles that I'm in now. And I think it's important, and there's a lot of operators in this room, there's a lot of business owners, a lot of CEOs. I think it's really important to keep those roles open for new grads, you know, and help them develop the skills they need to succeed in this interesting labor market that we're in. I mean, AI is not going away, but use it as a tool to equip your humans to be better. And to help them develop the skills they need because we can't sacrifice humans for the sake of artificial intelligence. Like, we just can't. It's unethical. And I'm pretty passionate about that. So I would say keep that in mind as we go forward in the next 5 years. Let people come in and develop the skills that we developed 15 years ago.

I have a thing on that as well. And I won't speak to the technical password element. We'll let someone else do that. What does entry-level mean now with access to AI? Entry-level is now mid-level or better just immediately. So, I don't think it's losing the job at all. It's just recognizing that it's actually much more advanced and much more capable than it was before. We're an engineering company, so we have global engineers and we deal with this all the time. Career progression. What does it mean? What does it look like? Am I replaceable? Am I a commodity? What does it look like? But my junior engineers today act like senior engineers 5 years ago at a much, much better price point, much more competitive capability. But it's what the market demands now. And that's what AI is facilitating is junior doesn't mean junior anymore at all. So I don't think we're losing a career progression at all. So we're redefining what the subject matter expert senior people have to become because junior is now the new baseline mid, mid-level. So I think we revel in that. Bring that on. We're much more productive, much more capable. Now and celebrate it. But there's one more level above that. That's the one that has to be even smarter and even better. That's the one that's at risk in my mind, not the, not the junior. It's the, it's the senior. You got to be better now than ever.

Yesterday I did a podcast with the founders of SchoolAI, and the ideal teaching scenario in their mind is one teacher and one student. And AI, I think, is being viewed the wrong way in the, in the, in the learning environment. Because teachers— one teacher is looking at AI helping 42 students cheat, and the teacher needs to realize this is where every student can have a personalized training person, whether, whether they're visual, the audio, however they solve problems. I look at it as every student will have a PhD-level teacher in their pocket to help them learn the best things. And I think when it comes into the business world, in the sales world, I run a dev shop, and like, the same type of things. How do you overcome objections? I take out, you can take out ChatGPT. Like, one thing I, one of the things I did today for this was, I was prepping, and I put on ChatGPT on audio, and I said, pretend you're Amy Cook. She has a lot of stuff published online. I said, train me, ask me the types of questions Amy will ask me. Bring in questions about Fullcast.

Test.

And your, your sales reps and everything can do that exact same thing, and it's $20 a month.

Yeah, uh, I think very good points like is made. I want to just, uh, bring one research which happened recently which shows that in students, the processing power of the brain and the activation of the neural network from the MNI, that is reduced. That is reduced because we are becoming too dependent on the ChatGPTs and like different tools, AI tools. And this will grow. That dependency will grow. We are getting more convenient and we are getting more, like, it's easy for us to use. So there is this question where, like, how— what is the intelligence of human, like, down the line, and how much creativity and the innovation that we have in our mind, that is, like, questionable right now.

So that is fascinating and so interesting. John, I want to know what Amy Cook GPT said to you.

She had really good questions. She asked me about the recent acquisitions and how it tied into AI and the future of AI and, you know, the direction.

Did she use a lot of emojis?

No emojis.

She was very nice. Okay, not quite me then.

There was not the Amy Cook sandwich.

That is awesome. This is really cool.

May I say one more thing? There was a colleague of mine at Stanford that had a really good quote that I think we could all learn from. We're not to the stage yet when we hit AGI where AI is replacing people, but people that know how to use AI are going to replace people that don't know how to use AI. So just keep that in mind. And you're absolutely right. They have to have the tools to be able to do the job.

Love it. And we got to figure out how those neural networks can be activated better because my kids are now doing their homework with ChatGPT. That's a whole other story. All right.

All right, this is, uh, Josh Daniels. So one question, this is a nerdy question, meta, meta guy. So are you guys, are you, how are you guys playing around with like hierarchical reasoning models versus like a standard LLM for like, uh, I don't know, it's how the brain thinks, right? We compartmentalize and, and bring it down.

So I think I just, so that's the first one for you.

And then a broader question for the team here, uh, what are like the top 2, 3 skills you guys say people should be learning with AI? And specifically, let's focus on revenue. So what are those skills that teams in revenue should be learning of how to use, orchestrate, and work with AI?

Regarding the reasoning part, the model capability with the reasoning is going to get better and increase over the period of time. So right now, we are at a phase where It's thinking during the inference time. This is a test time coming. That's why we are seeing a lot of millis— like a lot of seconds of delay and latencies, because it's thinking, refining, and improving its answer once over and over again. What we would be seeing— there are two directions which are happening. One is to reduce that time to think. Second is to actually, uh, have more like, uh, rather than one centralized brain, have a brains which are called small, like, language models, and each of them are responsible for, like, a small part of thinking. Just like a memory, we have what— the cerebral— I mean, we have a lot of different modular on the data for different purpose. We have a different for, like, thinking, reasoning, for creativity. There are different things similar to that. Like, there are going to be architectures which are already, like, in research, and kind of, like, prototypes are out where you are thinking in that specific manner, and the whole brain is not not one LLM, but like the small mini LLMs which are individually very powerful and a very specific part of the job that the brain does. So over the period of time, we are going to see the intelligence which is going to be incredibly good, and we are going to have less hallucination. And, uh, yeah, it's, it's going to get more powerful. The second, uh, domain or dimension which is happening, which is make the AI more affordable. And where the unit economics started working is that the models are going to get smaller, like through the knowledge distillation. And there are different techniques to make a bigger model into a smaller one. That means the cost of the inference, or when we are doing a chatbot or putting a query or something, from $1, it will go to like $0.10. That's where we are going to see that these companies are getting profitable. Right now, it's not in a phase where the cost of query is too high as compared to what you are paying in $20 or $100 or $200, like ChatGPT kind of thing. So these are the two trends which is happening with reasoning. One on the capability side, and second on the compute or the efficiency side. So yeah.

Thanks.

Interesting. Okay, and now the question of the top 1 or 2 things. Okay.

So this is something I've done a heck of a lot of thinking about, so thank you for asking that question. I was on a— I was doing a podcast episode with the regional CTO of IBM, and before we did the podcast, we were actually debating this very question. And the answer we came up with, I think, very much applies to revenue organizations. There's really going to be 3 main things. That AI is not going to be able to replace anytime soon. And I call them the 3 C's. That's what I call them on my show, is creativity, communication, and critical thinking. Those 3 things right there are what you should be focusing on when you're hiring for people in revenue organizations or in some way, shape, or form training people, because if they can critically think themselves out of a paper bag, they're going to be doing okay. Using AI as a tool. If they're good communicators, well, hell, they're supposed to be doing good communication anyway, right? They're in a revenue organization. Okay. And if they're creative, they're going to come up with other ways to be effective. So that's my thoughts.

I think that when we look at what makes people amazing is the ability to connect and empathy. If you want to be successful in business, in sales, in revenue, in anything. Can I connect with you as a human being? And do I empathize with your business, with you as a human? Let's— that can't be trained. Sorry, by AI. That can be trained. And I think that those are the skill sets that personally we look for is the empathy element of human connection.

What we're seeing in the LLM space is that there's not one LLM that's just dominating everything. A really good example is if you look at OpenAI and vO3, they're very different in, in outputs. And I think as we're looking at tools and how to become better in the workspace, one of the things I like about Fulcast is the last 3 companies they've acquired are all AI companies focused on RevOps. And to me, what I see in the marketplace is that they're going to be the leaders in this type of specific AI. They recently, they, you know, they sold the company for $250 million. They took all their experience, now they're buying AI companies, and all that knowledge is being packaged into the Fullcast AI. So, you're not looking for one that's going to replace everything. It's going to be compartmentalized, and specific companies are going to get really, really good at training and creating great outputs.

Can I add one C to your three C's? I was going to say curiosity. I think that's one of the biggest applications of AI, especially the generative AI that kind of just lives next to you as your AI companions. It's like there's no better learning tool than deep diving with a ChatGPT-type tool, you know? And I think that's something that when we're talking about revenue jobs and the roles that exist in the revenue lifecycle, you know, that curiosity serves you well in any role, whether it's a CRO, whether it's whether it's a RevOps person, getting to know people especially. You know, we've talked a lot about human connection, but I think coupling up that human connection with curiosity and utilizing AI to just be better at your job, learn more about the companies you're serving, or learn more about the roles that you're interacting with and your internal, external customers, it's like that will serve you better than I think anything that you can do in revenue.

I love that so much. One thing that a lot of you guys said, just to synthesize, is that you are prioritizing what we have traditionally traditionally called soft skills, traditionally deprioritized in business. And now what you're— what I'm hearing here is that you are prioritizing these skills in business because AI can do so much of the computational process. So I think that's really fascinating and super, super relevant. Um, okay, so for— we have so many people who are interested in, in your questions. What I'm going to ask the the people now is for you guys to tell us who you want to get an answer from so we can answer more people's questions. Okay. All right. Thanks, guys.

Hey there. Jacob Strachina. This question is for Aditya specifically. Do you think that we talked about AGI a little bit? Do you think that it's possible to reach AGI under the current day transformer tech that underlies all of the major LLMs, or is it not possible?

Okay, uh, so this is a question which is very controversial— not controversial, I would say more like, uh, first, there is no clear definition of AGI. Like, everyone has its own definition, right? I mean, for me, the AGI could be like, okay, you are getting the best scientific paper in biology or like some kind of like domain which is very well vetted by people, and, uh, this is something which is never discovered. That could be an AGI. So the definition of AGI is very vague, uh, But I mean, over the period, like the model capabilities are going to get better and better. There is no doubt about it. Like if you look at the expenditure, like the companies are doing on the data centers and like there is, uh, of course there are like news and other things where like the model capability are going to get to multi-trillion. If, if we go to that level, that means we are exploring something which is like incredibly like out of our reach. So there would be experimentation and those things on that part. And right now we are dealing with like at a multi-hundred billion dollars like in a data use, right? So the model capabilities are going to get higher. Like when it comes to AGI, it's like it may or may not like because there is no standard definition of that one. There is no benchmark and that's what scientific committee is also doing. You would probably have better idea that like how do we define AGI? How do we create a benchmark to say that, okay, if we reach more than this accuracy, on this percentage, we have achieved AGI, right? So those things are still like in a framework and like different organization bodies are doing. I'm pretty sure you would have like a lot more on this one. Yeah.

Isn't it a sliding scale too? Just, it's continually changing.

Yeah.

Yeah. It's a changing. Exactly.

Awesome. I love that. Okay. I know I said just one person, but I actually really wanna hear what all of you think. This is actually so interesting. So let's have it. Let's hear it from everyone.

Stock up your food supply. No, I'm of the mind— we think a lot alike in this— that LLMs are great at language, but they're great at language. You know, are they great at everything else? Well, can transistor-based technology really do that? I don't know. It can do a lot more than we thought it could 2 years ago. But is it ultimately going to end up being the main orchestration engine for an AGI brain that's made up of certain components, including an LLM, an image generation engine? Who knows what else? I think there's another technology out there that we have yet to really refine that's going to end up being the master of all of these subprocesses. And when we find that, whether that be a liquid large model or something else, that's when we are in danger of hitting AGI. AI, but that's just me.

I'm just going to defer to that.

I would agree that I think this is a stepping stone and we're not at AGI yet, but I also would look at your phones and your computers are the genesis of a silicon-based life form and like the world is drastically changing in reference to that.

Yeah, what does it mean for consciousness when AGI happens, I guess? And I'll leave that one open-ended because I don't know how to answer it.

It's so interesting. A really good friend of mine named Brad Smith was diagnosed with ALS about 15 years ago. And he now does not have the ability to speak. He does not have the ability to move at all. And he was the second person to receive the— what do we call it? Forgot. Neuralink. The Neuralink, yes. And he just gave a presentation Amy Cook, all through his thought, did the most eloquent speech that I always— like, that he always did. It was him, and they recorded his voice and reproduced it, and you could not tell the difference. It was absolutely fascinating. So what we can do is so— like, I look at Brad Pitt and I think, that is incredible. And then I watch The Terminator, and I'm like, that's so scary. All right, next question.

Can I talk about the scary part real fast? When we— I— so for every 30 to 60 days, I'll have a major anxiety attack because of AI. I think we all have that. But if we look at the pattern of history and technology, like even things like nuclear arms, the more advanced we are getting, the more civilized civilization is becoming. This might be a hot topic, but like— no, you disagree? Look at what's happening in Ukraine. The wars are starting to be fought with robots, and I think in the future there'll be more of an economic warfare with robots and then human lives.

So how is that civilized if you are having a war in a robotic manner?

Because you and your kids are no longer in the fire, in harm's way. I think—

let's move on to roses and flowers. Okay, perfect. Next question.

Hi, my name is Dolly Cheetah. I had a question actually, follow-up to the previous question. So we talked about AI not replacing humans because of all those Cs we talked about. But then I like to look into the future usually and work on technologies that are a little bit futuristic because AI is already here. What are the things that I want to know your answer before I say what my answer is that could replace AI itself or help augment AI? Because AI is not going to be the answer for everything, right? I mean, there is a limitation to your point just now.

So everybody's familiar with Lumen Technologies, right? Okay. So when it came to the usage of LLMs, Specifically, in a sales environment, Lumen created an ask me anything engine that they unleashed on their sales force just to see if it would make them more efficient. And they estimated that it saved them 4 hours a week. And so they estimated that the net savings or increase in productivity was about $50 million a year. So I agree with you completely that from an augmentive stance, that's going to be the biggest thing that you can do rather than focus on the replacement. Portion of it. And I totally forgot what the second part of your question was because I forgot.

The technology that could replace AI itself.

I don't know. Is there another cyborg? Since we're talking about Star Trek, the Borg. But I don't know.

I mean, I'll tell you my answer and you can tell me if it's— so there is probably a gray area. Or a transition period into quantum technologies. And so I would say quantum-enabled AI, quantum machine learning, which is already happening, but any of you can answer on that because—

Yeah, but quantum is going to help the calculation. It's not going to help the actual artificial intelligence. It'll make it faster. Right. And it'll make it more responsive.

Are there any— you know, cybersecurity is one of their— security, RSA and all of that, but is there any— overlap that you see where AI ends and quantum begins?

Oh, 100%. I mean, hang on to your Bitcoin and hope it doesn't get hacked because as soon as quantum computing hits, it's going to be in real danger. Brute force hacking is going to become really simple and easy for good quantum computers. You're right. As a technology, as far as like a, let's say, a revolutionary technology that's going to take the next step up, I think you're right. I think artificial intelligence is great, but artificial intelligence is limited by its infrastructure, its compute power, its training power, its memory, and the speed at which it can process. And if you can take quantum computing and make that speed so much higher, well, that's going to affect all of the other pieces as well, including the training portion. So I think you're absolutely right. Quantum is going to have a massive effect. Would you agree?

Yes, but it is not going to replace AI. It's going to complement AI. So it's going to be like a nitro boost to a normal fuel. That's what it would do.

I like that, the nitro boost. That's a good one. All right.

Change the mood a little bit. This one's for my RevOps buddy because he's living it right now.

But I was trying to pull it back to this morning's sort of topic by Ryan and saying, how's the VC sort of landscape going to change given the launch of companies so quick. I mean, companies or ideas can get spun up now in a couple of months, you know, far less devs to build the software that took years, build a team of 40 people, you know, take 5 years to get to $5 million type thing. You're living it right now with Alessio in a way. You know, how's it going to change the landscape of VCs?

I mean, I do know that it's already harder for VCs to evaluate companies, that's for sure. I mean, I think that it becomes an ROI conversation more than anything. It's like if you can't demonstrate a tangible ROI for your platform, then no investor is going to want to invest in it, I think. And if you're not looking at future-forward technology, you know, the technology that's on the cutting edge, that isn't just another agentic wrapped workflow builder. Won't name any names. I think those are gonna be the criteria. It's like, do you have future-forward-facing technology and do you have a tangible ROI that you can, that you can show from, from existing customers?

I think one thing that would matter, like if you are in a, like starting a startup or something, is the moat. And the traditional way the moat, which is defined in a SaaS, is not going to work directly in the agent world. So either you have a data which is not out there and you can bring the agent or something over to that. But if you are a wrapper, then it will be easy for the existing lower layer provider, OpenAI, Gemini, and all those things, to capture that market. The moment the market, like, TAM is going to get big, it's going to take, take, take you guys away, like, at a lower cost and provide the better facilities. The same as that of App Store. Apple look into— sorry, let's not call names, but, uh, the OS companies look into, like, the App store which can be easily replaceable. They cannot replace a game which is built by sophisticated company. But if there is like a small app that can be built over like the weeks, they would just develop and take that market away and like put that as a default one, right? So defining a moat like in the AI world is completely different. And it's like you need to have a competitive advantage either through data or an ecosystem. Otherwise It's not like a very, very sustainable business, I would say.

I think it's actually amazing what AI is going to do for business launching and innovation, like the speed of innovation now, the barrier to entry, the moat is gone with AI. An idea— I was talking to someone, you can start a business tomorrow that's absolutely innovative, but so can your buddy. So what's the difference now? I think the value definition will change slightly. It is about ROI, it's about competitive advantage, but the barrier to entry for Innovation now is gone. It's incredible. So you've got to be so much better, so much faster. And that's what I think is so amazing about technology. Very interesting.

I run a VC podcast. I think the way we think about VC is drastically changing. Right now you think of VC as, hey, I'm going to build a SaaS app. VC is still going to exist, but it's going to chase really large options like, hey, let's mine H3 from the moon. But what's going to happen now is because of AI, and we're going to pick on Fulcast again, you could have a specific sales team that could say, I want to have these types of functionality. And they can use AI to build it themselves and to integrate directly with Fulcast. And each team can customize what they need independent from others. And right now, most companies can't afford that. Or it's a one-size-fits-all. So we're now, that's where Fulcast is going is, I'm assuming it's immense customization in the sales process.

I love that, John. And by the way, his podcast is number 5. You guys should totally download it. It's really good. All right. We have time for 2 more questions.

I'm Matt.

And I guess my question is, is it possible that AI will eat itself? And I'll give you 2 examples of what I mean. Would it potentially discourage the creation of novel ideas or decelerate it that it would then consume for all of us? Or two, would it unemploy half the country and destroy purchasing power so nobody can buy the things that we all want to create with AI?

We're back to doom and gloom, I see.

Okay, I can go first. So basically what we are seeing right now in the multi-agent system, this kind of behavior is already evolving, which is called like colluding. So what is happening if you give an instruction to the one agent, it will pass, follow that guidelines and everything, but it will send some other information to the other agent which is not having the same policy. So basically what you're talking about, the AI eats itself, or more like an AI would not follow the guidelines. This could be possible in a very complicated system, and I think I think once we come to the point where intelligence is at a much more powerful level where it can actually publish like a research which is like very valid and which is like weighted by the top experts in the top conference, if we come to that level, it would actually come up with more sophisticated technology, for example, how to analyze stock which the guys in the New York Street cannot do that good of a job. It would— it might eventually happen. There is a, in my view, there is a real possibility of that. And that is going to be a little bit of scary scenario because you are going to see like depression, like lot of problems in the systems and policies and the guidelines and the government like interference would not be very well suited and it would be lagging behind to the thing. So there has to be regulation and policies to kind of like make sure that these scenario would not happen. So, but this is just my contrary opinion on this subject.

So I'm, I'm a simple person, so I don't look at AI as consuming anything. I look at this as the best opportunity in business in the history of mankind, the best opportunity to connect, to move, to innovate than we've ever seen. So is there this potential of really, really scary things? Sure. Same thing was said with electricity and computing And same thing was said then. This is different for sure. I don't think it's a cannibalization necessarily. I think it's an evolution. And I think it's amazing that we're here. So my thing is very naive to what these guys are talking about. But I view AI as run to and leverage so you can maximize potential. And that's how I view it. And again, probably naive. But man, what a better opportunity to be in business. There's never been— I can get more data in 2 seconds than it would take months to have gotten before. It's incredible. Now make better decisions, faster decisions, more value right here. So I think that it's not going to consume itself. It's going to evolve what business means in some ways.

Yeah, I think there's something underlying here that we've all kind of touched on. It's the how do humans take care of other human beings. I think that's what you were getting at. We got to think about what is the impact of AI on a larger scale. How do we protect humans? How do we protect jobs? How do we protect our livelihood and our ability to afford groceries? These sorts of problems aren't going to be going away, and AI is probably not going to solve them, or maybe it will. Optimistically, hopefully we can solve some of these problems by using AI together, but I think it's important to keep the human in the loop in all of these things that we're talking about.

I think you're going to go to a 20 to 30-hour workweek as time goes on. And everyone's standard of living and quality will be better. And the things that took a lot of time, like farming, are taking less and less, and we'll be able to spend time with those that we love. I think with AI, because change is scary, we're focusing on the scare versus— I think it's going to create far more opportunities than we ever imagined.

There will be opportunity. I'm going to dissent a little bit. I think there will be upheaval, and I think it will be significant upheaval. Because we're entering a phase— well, okay, in the history of mankind, there has been major technology advancement that has either threatened white-collar work or threatened blue-collar work. And there has never been a time when something has really had a major threat on both. And with the advent of robotics coming up the way it is, and with artificial intelligence being able to be injected into a humanoid body that now will have the capability to do so, We're gonna have stuff that's gonna threaten both types of work. We are going to hit a new economic structure. There is just no way around it. Trump doing Project Stargate, I think, was maybe a really smart thing and a first step in the way— listen, whether you love him or hate him, I'm not saying anything about that, but I think Project Stargate was a really, really smart thing because now the government is vested in some of the means of production, which can then lead to a UBI. Which could then also potentially lead to a much lesser work week and people able to sustain themselves. And now we find out that they're thinking of investing in Intel. That's great. Do it. Let's have the United States invest in Intel and scrap the CHIPS Act. Let's just build the darn thing up in Illinois. Illinois. So just, just get ready. It's, it's gonna get crazy. It's gonna get fun. But you have every reason to feel optimistic. But there will be some upheaval because because human society is not going to be able to react to that level of creative destruction like it has in previous industrial revolutions.

Wow, this is such an impactful session. We have one last question.

My name is John Young, and I work in sales and marketing and raising capital for businesses. And I got a demo from a gentleman, and he said, You give me a file of people, their name, their phone number, and their email address, and I'll tell you to the exact penny how much money they have available on credit and what they potentially have in their bank account and what their profession is. And I saw that and I was like, oh my goodness, how do I protect myself from somebody knowing that about me? Will a digital wallet be able to create some type of security for me so that people can't get that type of information about me and about my finances?

That's a great question. Brings up a whole lot of ethics and security concerns.

You're not alone. Everyone is worried about that, especially with the point about quantum computing. I mean, brute force hacking is just simply going to be Happening everywhere. So not to get doom and gloom, but just be ready. Just, just be ready for data to be exposed. I think— is there a single person in this room that has not had some information released in a hack? Is there any person that has not gotten a notification that one of your accounts has been compromised? You have not? Yeah. I've had like 743, so, you know, it— but we can safeguard as best we can and that's really all we can do. The good news about AI is that it's going to be able to be used, yes, by the bad guys, but it'll also be able to be used by the good guys. And so just as flaws and different things are happening, I think that patching and, you know, MDR type stuff is going to be a lot more rapid. And so, you know, as the moat decreases and we're not relying so much on open source models versus, you know, enterprise models and that type of capability becomes a lot more uniform, you're going to have responsiveness is going to certainly become a lot less time between incident and response. Quantum protocols for security, and these companies would start leveraging quantum computing power just the same way that they're leveraging security right now, but at a quantum level.

Could you use your—

theoretically, right, that you open that computing power for security protocols as well as hacking? So as quantum computing refines itself as such, the security measures and quantum computer power will be used for those security measures.

That's possible. It would take policies that we haven't invented yet. Keep in mind that security right now is based primarily on encryption. And so since everything right now cybersecurity-wise is based on encryption, and since brute force hacking is what is able to defeat encryption, and the only thing that stops us from having our stuff brute force hacked is time and compute power, and quantum computing is going to defeat both, then we got to come up with a new way to do it. So what that's going to be, I don't know.

That's a big threat to the blockchain with Bitcoin.

Big time. That's, that's specifically why I mentioned that, that, you know, I don't own Bitcoin. Sorry, I don't. I own a lot of stuff. I own a lot of gold. I own a lot of silver, but I don't own Bitcoin because it's going to get hacked eventually. Sorry, doom and gloom.

I think it's a sliding scale. Hackers are getting better and security is getting better, and at times, sometimes hackers are better versus security. But at the same time, I would not put all my money in Bitcoin. If it gets hacked, the whole system's gone.

And also, I think quantum computing is not going to be like easily accessible to everyone. There will be laws and rules, and the labs who has reached to the level of the quantum computing, they're like we like, they're well known and they are like in single digit. So these labs would be either have, would have a collaboration or a policy or something with the government that this technology cannot be in the hands of normal person. Otherwise there could be like consequences what we talked about, repercussions would be something which is beyond our, like we can think about. So it has to be a closed technology. It cannot be like an open technology like GPUs what we have right now. Yeah, or unless like we have everything, whatever the RSA is obsolete, we have some new standard for security, we have a new standards like how the blockchain is developed which cannot be bypassed by quantum computing, only then it may be possible that it might be like just to speed up AI. Yeah.

All right, any—

No, they're not for sale. Yet. I mean, Google has— they've developed a chip called Willow. So one of the problems with quantum computing is the error percentage. They're not able to make it process and have a low enough error control. Willow is a step in the right direction that's making it a lot more viable with a manageable enough error percentage. China has processors that have a whole hell of a lot more qubits than the Willow chip, but their error percentage is much higher. And so This is where it's scary because he does mention that the number of places that do have quantum computing working is in the single digits. The number of places that have quantum working with an acceptable level of error control right now is one, and that's Google. And as soon as China does, that's two. And China, sorry, they're a bad actor. So we talk about limiting how people are going to be able to get to quantum computing. We all know that state-sponsored hacking by China happens here in the United States. Is that going to not happen simply because quantum computing is off limits? No.

You guys, this is so fascinating. And I know that there are so many more questions in the audience. So what I'm going to do— would you guys be willing to just stay up here and let everyone come rush you after this is over? Then you can sign autographs. Thank you guys so much. Can we give them a huge round of applause? Thank you. Business, yes, that's business.

Business, yes, that's business.