Empowering Intellect Over Labor: Syed Hussain on SHIZA’s Decentralized AI Revolution | S2 Ep. 158

Summary

Podcast Summary: Founder’s Story – "Empowering Intellect Over Labor: Syed Hussain on SHIZA’s Decentralized AI Revolution" | S2 Ep. 158

Release Date: December 14, 2024
Host: IBH Media
Guest: Syed Hussain, Founder and CEO of Shiza

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Introduction

In this compelling episode of Founder’s Story, host IBH Media welcomes Syed Hussain, the visionary founder and CEO of Shiza. Syed shares his unique journey from childhood entrepreneurship to spearheading a decentralized AI revolution aimed at transforming the future of work and personal value generation.

Early Entrepreneurship: The Genesis of Syed Hussain

Syed Hussain’s entrepreneurial spirit was evident from a tender age. He recounts his first foray into business at just 8 years old in India.

Syed Hussain [02:04]: "My first foray into it came at the ripe old age of 8 years old when I was actually in India at that time."

Syed noticed a gap in the market for comic book collections. To capitalize on the episodic release model, he initiated a comic book rental service, allowing peers to read comics at a fraction of the cost. This venture not only honed his business acumen but also provided him with early lessons in customer engagement and value creation.

Transition to Technology: Embracing the Digital Frontier

As the .com boom of the mid to late '90s unfolded, Syed delved deeper into the world of technology. His collaboration with a family friend from IBM introduced him to the vast potentials of the Internet and Web 1.0.

Syed Hussain [04:16]: "I started reading and really understanding more and more about technology and the power of this thing called the Internet."

This period marked Syed’s evolution from traditional entrepreneurship to a tech-driven visionary. He immersed himself in various aspects of data management, from data warehousing and ETL to big data and eventually Web3 and blockchain technologies.

Embracing AI and Agentic Solutions: The Birth of Shiza

The advent of GPT-3.0 was a pivotal moment for Syed. It enabled him to overcome significant infrastructure costs associated with building predictive analytics engines.

Syed Hussain [05:32]: "When GPT3 auto came out, that's where I decided to start playing with it."

Leveraging GPT-3.0, Syed and his team developed agentic solutions, leading to the conception of Shared Human Intellect Zonal Agents (Shiza). This innovation aimed to harness AI's capabilities to automate processes, tasks, and eventually jobs, thereby addressing the impending shift to a post-labor economy.

The Future of Agentic AI: Shaping a Post-Labor Economy

Syed deeply considers the societal implications of agentic AI. He emphasizes the necessity of transitioning from a labor-driven to an intellect-driven economy.

Syed Hussain [09:57]: "We start thinking about a world which is going to be a post labor economy. That's going to be coming up."

He predicts that while a small segment of the population will leverage AI to become extraordinarily successful, the vast majority will utilize AI for convenience, potentially leading to decreased individual productivity and the emergence of novel societal challenges akin to those seen with the advent of social media and mobile technology.

Syed Hussain [12:29]: "The vast majority of people are going to use the technology not from an entrepreneurial perspective, but because it's convenient."

Shiza’s Vision: Decentralized Ownership of AI Agents

At the core of Shiza’s mission is the belief that individuals should own their AI agents, especially as these agents start replacing traditional labor. Syed introduces the concept of Individualized Learning Models (ILMs), which ensures that AI agents are personally owned and not controlled by centralized entities.

Syed Hussain [26:42]: "Our slogan is 'Own your AI before AI owns you.' We are utilizing Web3 rails with decentralization to provide individuals with AI agents that they themselves will own."

This decentralized approach ensures that personal data remains secure and monetizable by the individual, preventing large corporations from exploiting user data for profit.

Monetizing Intellect in the New Economy

With the rise of agentic AI, Syed envisions a future where human value is derived from intellectual contributions rather than traditional labor. Shiza aims to monetize these digital intellects, allowing individuals to earn value through their AI agents.

Syed Hussain [25:27]: "If that labor itself is replaced by these agents, how are we going to earn our value? How are we making money?"

By enabling users to own and monetize their AI agents, Shiza seeks to empower individuals to thrive in an intellect-driven economy, ensuring that personal value creation remains a central aspect of human existence.

Conclusion and Call to Action

As the podcast draws to a close, Syed Hussain extends an invitation to listeners to join Shiza’s journey towards a decentralized AI future.

Syed Hussain [28:51]: "The future is very, very bright and we can't wait for you to be a part of this with us."

Listeners interested in being part of this transformative movement are encouraged to join Shiza’s waitlist or connect with Syed on Twitter and LinkedIn.

Final Thoughts

Syed Hussain’s insights provide a thought-provoking glimpse into the potential upheavals and opportunities presented by agentic AI. His proactive approach with Shiza underscores the importance of decentralized ownership and intellect-driven value, positioning Shiza at the forefront of the next technological revolution.

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Notable Quotes:

• Syed Hussain [01:30]: "It's an absolute nightmare from the inside out."
• Syed Hussain [08:22]: "We want to build out a predictive analytics engine without worrying about infrastructure costs."
• Syed Hussain [09:47]: "It's going to be a very proactive approach to plan for a post labor economy."
• Syed Hussain [16:59]: "An AI agent is essentially a process that can execute a specific task."
• Syed Hussain [26:42]: "Own your AI before AI owns you."

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Connect with Shiza:

• Website: Shiza.ai
• Twitter: @SerialTechX
• LinkedIn: Syed Hussain

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Join Shiza’s Waitlist:
Visit Shiza.ai and sign up for early access to be part of the decentralized AI revolution.

Transcript

[A]

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[C]

Welcome back to Founders Story. Today we have said Hussain, who is the founder and CEO of Shiza and Shizza, is doing something very unique. This whole agentic AI, all these things. I mean the world is moving so fast and you and I had an incredible hour plus conversation just around how we see the future. Why did you even get into entrepreneurship and why did you start this company?

[D]

Yeah, great question. There's probably a, a simple answer to this and the simple answer of why I got into it is because I'm, I'm mentally challenged and I'm a, I'm just a sick person to want to.

[E]

Put myself through this and put the.

[D]

Rest of my family through this as well. So for anyone that's, that's an aspiring entrepreneur, the first thing I will tell you that it's very, very glamorous.

[E]

It's very, very sexy from the outside.

[D]

In, from, from the inside out.

[E]

It's an absolute nightmare.

[D]

Especially if you, if the ones that are going to be affected by it are your closest ones. So if you're crazy enough to convince them that this is the path we want to embark upon, then certainly entrepreneurship is for you. So just to just sort of lay the, lay the groundwork there for you. For you, Dan, How I decided to get into it was, you know, I've.

[E]

Always been fascinated, I've always been intrigued.

[D]

By the world of entrepreneurship and the world for entrepreneurship. My first foray into it came at the ripe, at the ripe old age of 8 years old when I was actually in India at that time. And the way that I got into it was, it was just, you know, for, for me it was just being an entrepreneur was just finding a solution to a problem that People had and people really didn't realize that the problem.

[E]

Was so just coming up with novel solutions around it. So what I did was I was.

[D]

Big into comic books and the only way that you could sort of. There was no concept of collecting comic books in India. Um, and people. The only option you had was to buy a comic book. But people would, there were, those comments were episodic. So every month there would be a new episode that would come out and I was totally into it and I was like, me and my friends were like, oh, can't wait for the next, next episode of these, these comics to come out. And what we ended up doing was we would just buy the comic, read it and then after we were done reading it, it's like, okay, you chuck it. You wait for the, the next episode to come the, the following month. And then something hit me where I'm like, well, instead of me sort of just, just buying it myself, what if.

[E]

I were to buy it and allow.

[D]

People to come in and just read.

[E]

It for a fraction of the cost.

[D]

That it would, that they would pay.

[E]

To actually buy it?

[D]

And that was sort of my first.

[E]

Entry into the world of entrepreneurship where.

[D]

I'm like, oh, this is pretty cool. Oh, I'm actually pretty good at this stuff.

[E]

Right.

[D]

So what would started off with as a comic book rental eventually ended up becoming a cafe where I just started to open things up and people are like, are coming in and out and utilizing it. And as a result of it, I ended up getting the most value from it as a kid that you can.

[E]

Get, which is what popularity points.

[D]

And I was, I was the man at that point and who doesn't like, you know, being a, being an 8.

[E]

Year old kid who doesn't like being.

[D]

A man when, when you have to pay people or try to convince them to stop calling you boy.

[E]

Right.

[D]

So for me it was, that was sort of the first foray into it. And then fast forward we get into the, the, into the mid, mid to late 90s and that's when this whole.com boom was starting to come about. And that's where I started reading and really understanding more and more about technology.

[E]

And the power of this thing called.

[D]

The Internet, which was essentially just connected computers with one another and giving people.

[E]

Access to be able to share the.

[D]

Data from within it and get that out to the outside world. So I start off with the Web 1.0 era. Excuse me, Started off in the, in the Web 1.0 era. And that's at that point was where I collaborated With a family friend of ours who got into, he was working for IBM at that time. And I said to him, I said, look what you're trying to build out.

[E]

Here, we could do this for smaller.

[D]

Businesses, so let's do it that way. That's how I started to get into the real world. And that was sort of my entry into the world of, of technology. And from there just got heavy into the data side. So started off on the networking side, then I got into the data side. From data warehousing to ETL to business intelligence to geospatial analytics to advanced analytics and then to the world of big data. Eventually finding my world into the world of web3 and blockchain. I started getting into that. And then from there we started to realize with this explosion in data solutions, this thing called GPT 3.0. When that first came out at that.

[E]

Point was when we were like, okay.

[D]

We want to build out this, we wanted to build out this predictive analytics engine, but the cost for doing so was significant. But then when GPT3 auto came in, that's where I decided to start playing with it. And before we knew it, we were able to build out essentially agentic solutions as a result of it. And then at that point was when I realized that there was going to be just an explosion in terms of these agentic solutions that are going to be coming about. What is that going to lead? What are the second order and third order effects of this going to be? And based off of that was essentially what the concept and the premise of shared human intellect zonal agents or Shiza.

[E]

AI was, was born out of.

[C]

You know the funny thing, it doesn't matter how successful someone becomes, you can always trace it back to when they were a kid. You could ask anyone like what is the first product that you sold right, or you resold. It's really, I think like every entrepreneur has a story of when they were a child, they were reselling something. They were the entrepreneurship. I feel you're almost born with these traits and then as those traits, then you realize that translates really well in the business. But I was listening to a recent interview with Eric Schmidt from the previous Google CEO and he mentioned just how groundbreaking it was even for them. When ChatGPT came out, how did you feel going back to the days of when you started using GPT3 and when you started using this tool, what was going through your mind? What were you thinking about in terms of what this could change for the future?

[D]

You know what's funny is when I was Running my previous company, we had actually heard of this thing, there's this company called OpenAI and they were taking on, they had just opened up for access to their platform. So I had signed up pretty early on onto their, onto their wait list. But it wasn't until ChatGPT3 came out that I started to actually get exposure to the API. The story behind, behind why I decided to play with ChatGPT 3.0 is that again in my previous venture, one of the things that we were looking to.

[E]

Build out was we were looking to.

[D]

Build out this, this deal recommendation engineering. And in order to build that deal recommendation engine I knew that the, the cost of infrastructure was so significant that we had in term in on our roadmap we had put it all the way towards when we get to our.

[E]

Series A or series B because of.

[D]

The cost that would be required for it. But when, when GPT3 auto came out all of a sudden that infrastructure cost we didn't have to worry about because here they were providing all the infrastructure was already provided to them and they were giving you. Essentially it was just the cost of inference, right?

[E]

To be able to use and to.

[D]

Be able to build on top of. So really what we did was we, the first product that we started to build that I started to play with where I saw the real value of it was essentially a GPT wrapper, right? We took that API, we built on top of it. But what I started to realize was two things. One is that this is going to be one of many that are going to be coming out to it where everyone is talking about GPT with Chat GPT, Chat GPT everyone was talking about that. I knew that these, this, this, these transformer based LLMs that were coming out, they were going to end up getting commoditized.

[E]

So this was a very, very early.

[D]

Thesis that we had where I was saying that LLMs are going to end up getting commoditized. So if they end up getting commoditized and people have access to it, that's going to give, give rise to this birth of agentic solutions. And if that happens, what are, let's not worry about today what everyone is.

[E]

Building, but what are the second order.

[D]

Effects of this are going to be like? And to me it was immediately I saw that this is going to allow for the automation of processes. These automation of processes would lead to the automation of tasks and then the automation of those tasks would ultimately lead to the automation of jobs. So if that automation of jobs is, it's for me it Was it's not a matter of if, it's a matter of when. And that when was going to happen very, very rapidly. And if that's going to happen, then we need to have some sort of an infrastructure to plan for that.

[E]

Right.

[D]

We start thinking about a world which is going to be a post labor economy. That's, that's going to be coming up.

[E]

And in order to do that, how.

[D]

Do we start focusing, shifting our mindset away from being labor driven to being more, more intellect driven. And that was essentially for, for me, that was the, the, the light bulb moment where I was like, holy shit, it's coming. And instead of, instead of us having to worry about it, you know, 10, 15 years from now and sort of trying to reel it back and thinking from a reactive perspective, it makes a lot more sense to be proactive and take a proactive approach to it. And that was essentially where this, this.

[E]

Whole notion around what it is that.

[D]

We'Re building came about.

[C]

Yeah, and I find it interesting, right, because everyone's talking about the future of work, agentic AI, like these are topics that obviously are going to impact future generations. But when I think about a lot of younger people like Gen Z Alpha, I don't think they want to work a lot. I don't think they want to work 40 hours a week, 50 hours a week. Hustle and grind, it seems they want this balance of being able to enjoy life, Travel, dance on TikTok. They don't want to sit in an office, I don't think, and work 24, 7. You have all of these things happening.

[F]

At the same time.

[C]

You have generations who I think will be more embracing because it's probably hard for you and I to even imagine a world where we're not working 40, 50, 60 hours a week, we're not grinding because that's how we've been built. How do you see future generations taking up with agent to Gai and the solutions that you're, that you're bringing?

[D]

So I think there's going to be, there's two aspects to this, right? And there is going to be. And look, I mean what I'm about to say, it's nothing revealing this happens with any sort of a technology revolution, right? Which is there's going to be a very small portion of the populace that's going to actually leverage this to their advantage and end up becoming the next sort of, you know, where they would use technology to become the next millionaires. And then with, and then they would, with the next generation, they would end up becoming the next sort of billionaires. And in our generation we're starting to see is the next set of trillionaires that are going to be coming in. So you're always going to have a small populace of the overall, of the overall population that are going to end up becoming that. But the vast majority are going to leverage it, they're going to consume it. And it, look, it sucks to say it, but, but the vast majority of people are lazy. That's just who they are.

[E]

Right?

[D]

And I know it's not the politically correct thing to say, but it is the truth and the truth hurts. So the vast majority of people are going to end up utilizing this technology and it's going to end up making them even less productive than they are from a, from an individual productivity perspective. So, but, but the consumption of the technology is going to increase, right? So Mo, my point is that the vast majority of people are going to use the technology not for, not from an entrepreneurial perspective, not from how they can build it up, but because it's, it's convenient. Right?

[E]

And it will be absolutely the next.

[D]

Set of technologies that are going to come in. They're, they're absolutely going to become technologies that are going to make things a lot easier for. But then there's also going to be negative second order effects of that.

[E]

Right?

[D]

And we're seeing that with, take a look at like your, your, the mobile phones. Take a look at what social media has done to people, right? Take a look at what, what all of these things have done. I don't see AI as any, any different than that.

[E]

Right.

[D]

It's just going to create a new set of novel problems for people. What those specific problems are, I am not smart enough to anticipate what those are, but I can just take a look at what history has told us and those patterns aren't, aren't going to go away.

[C]

So a friend of mine who's been a few decades leveraging AI and he's pretty advanced when it comes to voice AI. He was telling me a story recently where his company solved the problem. And when he asked these really smart people how it was done, they said it just happened. They didn't even know. They couldn't tell you exactly how it solved itself. How do you see AI as we continue to advance and as it advances on its own?

[D]

Look, there's going to be some, you're always going to hear those kinds of, you know, crazy stories. But then the reality also is that AI is a lot easier to figure out these kinds of things than a human being, right? So the real novelty of this is.

[E]

If I were to say, if I.

[D]

Were to associate that to a human being and said, well, how did you just come up with this idea? How did you come up with this creative concept, right? How do you explain someone like a Steve Jobs, right? And then people will try to do, you know, all kinds of analysis and psychoanalysis and socio, you know, sociological analysis on, on them and try to figure that part out. Figuring out human creativity and human problem solving is astronomically more difficult than figuring out a machine, right? So like when your friends and when people talk about these things, right, These things sound great, you know, like for a story. And it creates sort of this fear amongst people, like holy shit, we can't figure out. But the reality is if you do enough analysis, there's absolutely a way for you to be able to figure out. Because at the end of the day, it's all about the data, which is what these things run off of. So I think these things, you know.

[E]

These are great sort of media headlines.

[D]

For people to think about and for people to highlight. But the reality is that these kinds of things are easily, you know, if you put, look, the reality is if.

[E]

You assign an AI to figure out.

[D]

How an AI thought of, that's a lot easier to do than if you were to put a human behind it to do it. The point is the human is the one that created it. So it's a lot easier to be able to figure out machine based tasks and machine based creativity than it is.

[E]

To figure out human creativity.

[D]

So I, you know, I, I certainly am not one of those who's like, oh, you know, how did a machine figure that out? And I don't know what it is, you just haven't had enough time, you haven't put in enough time to be able to figure that out. But if you put enough time into it, there's a very easy way for you to be able to do so.

[C]

I love how AI can analyze things on the next level that we can't even imagine. The fact that AI can possibly figure out how to talk to animals or figure out your dreams that you had and analyze the brain because I think we don't really understand much about the brain as we probably should, right? The fact that it can figure all these things out, create drugs that we probably need in the future to solve maybe cancer or something. I mean, it's, it seems an incredible future and I can't wait. But let's talk about agentic AI. I think there's people, that many people have no idea what that even means. Can you explain that?

[E]

Sure.

[D]

So the way, that way that I like to explain to people is it's an agent, an AI agent. For those who are sort of the technical nerds here, the easiest way I can explain is think of it as.

[E]

A demon, not D E M O.

[D]

N, which is what the vast majority of the world thinks AI is going to end up becoming, but D A E M O N. Right? Within which is essentially a process. So think of it as being able to execute a single process.

[E]

So if you can create something simple.

[D]

Enough and you're passing a command to.

[E]

Be able to say, okay, do this.

[D]

Specific task, this is what you're responsible for. That's essentially what an AI agent is.

[E]

Able to do, is it handles a.

[D]

Specific task, then what you're doing is you're combining that agent with another agent that can take the output of the, of the previous agent as an input.

[E]

And then take the task to another level. Right?

[D]

So what you end up having is.

[E]

You end up having this chain of.

[D]

Agents or the swarm of agents that's.

[E]

Able to do one task and followed.

[D]

By another that's being taken in as.

[E]

The input for that.

[D]

So it's intelligence being built on top of additional intelligence.

[E]

You end up having the swarm of.

[D]

Agents that does the assigned work.

[E]

And then of course, then you can.

[D]

Have that particular swarm, the output of that becoming the input of another swarm form. And that's essentially what an agentic system ends up becoming.

[E]

Right.

[D]

So we have, if anyone who's a coder, if anyone that's actually developed code, right? That's what we do. We form, we formulate these arrays and we start to package them together. What AI is able to do. The beauty of AI is it's able to automate all of those and instead of a human being at the back end to create it, you're providing it.

[E]

With a set of rules.

[D]

And then what it's doing is it understands in that because of advances in nlp, it's able to understand what it's, you know, what it's going to be doing. And then it also has to its advantages. This is the beauty of LLMs is that it has a, to its advantage, it's sitting on top of human based solutions captured from all kinds of public data that it's also learning from and it's continuing to enhance that. So agentic solutions are really, they're, they're essentially, it's where all of these, these processes are coming together. Intelligence based processes that are coming together, being packed together.

[F]

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[D]

And understand how to interact with one another.

[C]

I can't wait. I don't wanna say perfect employees, but it's having perfect solutions that can execute the tasks that I need to get done, but are just like hyper focused and very good at that one task and then it gets to another task. I mean, we all need that in business. We all really need that, right? What is the future of shiz? I know you explained what you're doing, what you're working on, but you know, when you look a few years out, how do you see this company transforming?

[E]

Oh boy. Okay, so look, we have a very.

[D]

Very grand vision for where things are going, right? Minding my background and the majority of my team, right, we are all capital markets guys. So that's the background that we come from and we're really the way that we're looking at this is not from where things stand today, but where things are going to end up going. And as we start to think about, you heard my definition of agents and agentic solutions. And you can very, very quickly start to see that as these things start to, if you have these agentic solutions that have been created, then they're essentially going to end up replacing existing processes which to my earlier point is going to lead to the replacement of tasks, which ultimately a collection of all of these tasks is ultimately what people's jobs are, right? What we're assigned to do. So if that happens, and that will happen if that happens, or sorry, when that happens, what does that mean for people like you and I who are regular humans and who earn our value? And where, how do we derive our value?

[E]

So for the vast majority of the.

[D]

Existence of humanity, how we've derived our value has been labor driven, right? So the, it's been based on our output, right? So the, and that output is what we're compensated for, that output has been in some form of labor, whether it's, it's physical labor, whether it's creative labor or whether it's intellectual labor, whatever you want to call it, nevertheless, it's always.

[E]

Been in the form of labor. Well, if that labor itself, the output.

[D]

Of that labor is replaced by these agents, by these agentic solutions, well how the hell are we going to earn our value? How are we making money? Especially if these agents are owned by.

[E]

These centralized entities, right?

[D]

We spoke about open AI. There's others, you know, Gemini, Google, Microsoft, all these companies that are there, right, that own their own LLMs, that people's, that these agentic solutions are being built.

[E]

On top of, they're consuming all of your data, right? And we certainly don't want to make the mistake that we made with web.

[D]

2.0 within social media where people were just giving away their data, only to realize a lot later on, by the time it was too late, that holy shit, these other companies are monetizing off of my data. Well, fine, you could do that with.

[E]

That one mistake made.

[D]

We certainly don't want that to happen with, with, with your own AI agents which are going to be running around.

[E]

In the billions, right? So if that's the case, then it.

[D]

Becomes very, very crucial for me that labor that's going to be replaced for what it's being replaced by is owned by me. I'm the one that owns it. And this is why our slogan, which is own your AI before AI owns you. So what we're doing is we are.

[E]

Utilizing Web3 rails, right, with decentralization and distributed technologies for utilizing those Web3 is.

[D]

To be able to provide people with.

[E]

AI agents that they themselves will own.

[D]

And there's a couple of moving parts to this. The first part is that what we're doing is you want to capture the human experience, but that human experience that you're capturing, it shouldn't be a part.

[E]

Of a large language model that's centrally owned. Instead, what it should be is it should be owned by you, the individual, and should be novelly yours.

[D]

It should be owned plainly and simply by you. No one should have access to it, including the builders behind it, like a Shizza, for example.

[E]

So this is where we're introducing the concept. We're shifting away from large language models.

[D]

To individualized learning models or an ILM where you will own it, only all of your experiences are being captured by it. And if anyone else wants to have access to it, that you are the only one that can give access to certain components of it. What we call these intellects, these custom knowledge stores off of your, the entirety of your data, right, that you, that you have. So what we're envisioning then is a future in which these intellects that you have.

[E]

Right.

[D]

Will then be shared by others. People will have access to it.

[E]

And every single person that has access.

[D]

To that intellect, you as the individual who owns it, are being, have the ability to be able to monetize off of it. So this is how we're seeing, how.

[E]

We'Re envisioning the shift of a future.

[D]

Economies as we start to move away from a labor based economy into an intellect driven economy where you have all of these digital intellects that people will.

[E]

Be able to share off of, that.

[D]

People will be able to monetize off of.

[E]

And with shizza, what we're doing is we're laying the infrastructure, we're building that.

[D]

Out for this, for this post labor.

[C]

Economy, man, the future is bright. I'm excited. I think we've learned from mistakes in the past. We just freely give out basically priceless data. We've just given it out and now, you know, it's the ability to take some control, hopefully. So I can't wait. If people want to get in touch with you, they want to find out more information, they want to see how they can be a part of Shiza. How can they do so well?

[D]

The best way to do it is as of right now, we're our, our waitlist is open. So go on to Shizza. AI S H I Z A AI and sign up for our waitlist. You can, or you can find me on, on Twitter. You can catch me on LinkedIn. On Twitter, it's serial Tech X S E R I A L Tech X Find me on Twitter. And like I said, the best way to do this is sign up, sign up on our waitlist. I look at it every single day. Yes, I do look at it. And if you're interested in getting involved in some capacity. The future is in the words of in your own words, Dan, the future is very, very bright and we can't wait for you to be a part of this with us.

[C]

Saeed, thank you so much for joining us. Shiza AI agentic Billions of agentic AI is going to be everywhere in the future and you don't want to not be a part of it. So I appreciate your time today on FounderStory.

[D]

Thank you brother.

[A]

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[B]

We all need a moment to really breathe, so here's your chance to take a deep breath in. Now give a nice long exhale and repeat another 10 or so times. This healthy suggestion is brought to you by Regents Blue Cross Blue Shield of Oregon. Together we Health.