AI Leadership Q&A wth Noelle

Alright. Oh boy. We'll get started here in just a couple seconds. Trying to figure out where— how I authenticate into my platform. Hope this is the right one. That looks about right. Oh my gosh, am I streaming right now? Oh my gosh, I am. All right, awesome. All right, so I have to turn all these on. Let's see here. How's it going, everybody? Oh, let me reconnect. I gotta reconnect some of these real quick. Thank you. Oh, no. Okay, thank you. It's little, the one you bought me. You should look on the bed. Okay, sorry. Thank you. Hello, everyone. All right, looks like we are streaming almost everywhere. All right, we are good to go. All right, welcome. Hi, everybody. Fun day today. Sure, I will record our audio. Oh my gosh, no, don't join a new meeting. All right, we got some chats. Hello, I want you head in and you are here live with me in the Zoom. Go ahead and say hi in the chat. Get your fingers ready, we might have some fun conversations today. I am here in not so sunny South Florida, but I'm headed to Scottsdale, Arizona today, so that's super exciting. Julia, good to see you, my friend. Welcome everyone. Adam's in the house. Hello. Awesome. So Adam, Julia, Kirk, Tara, William. William, good to see you. All right. Welcome everybody. Welcome to our weekly hour that we get to spend together where we talk about AI leadership and what's new and interesting in the world of AI leadership, but also where we talk about some of the fun things that are happening in our I Love AI community. Community and what we have to look forward to through the end of this month and into February. We've got some great things coming up. Actually, the whole first quarter of 2025 is full of exciting and fun things. So I'm gonna try and— I did take some notes so I could make sure I reminded myself to say all the things I wanted to say to you all. As we go through, if I say anything that you have questions about or comments about, please don't hesitate to raise your hand or more importantly, throw it in the Q&A so I don't lose it. If you ask it in the chat, I might not be able to find you. So when— Noelle is here, welcome! So great to see you all. Um, yeah, oh my gosh, there's so much stuff going on. So I always like to start these calls first by giving you a little bit of knowledge of stuff that I have done. I actually want to practice something with my cool technology. Um, I don't— I, I think I said this last time, I never did quite do it, but that's because I'm not on the right device to do the test. We'll do it next time. Um, but I— yes, I'm so glad you made it, uh, Julia. I know it's in the middle of the day, but that's why at least we do it at the same time. So hopefully if you ever can make it, you know, it's at the same time every week during the holidays, meaning during Christmas, Thanksgiving, Easter, and 2 weeks during the summer, we may have some adjustments to the schedule, but the other 43 weeks of the year, we are 100% on, you know, we try to do it every time, the right time, same place, same, what do they say? Same bat time, same bat channel. So thank you all for being here. And what I thought I would share with you today, I actually shared some really cool stuff in the AI Leadership Institute call. I don't know how we came to it, but we were talking about kind of the top 3 questions that happen once you build a POC. And so I shared that with that, that organization, like that community. It's recorded. It'll be in the community. So for those of you there, there, you should go take a look at it. I think those 20 minutes were like gold. I mean, I, I kind of lost track of time, uh, sharing some of those really hard-learned lessons. Um, but today I figured, because not everyone is at the level that our AI Leadership Institute members are at, not everyone's implementing or, uh, you know, already very well aware of RAG architectures and generative models. So I thought I would spend a little bit of time today that I could carve out and share with, um, the community later in the form of like a replay, or maybe I'll cut it out and put it in HeyGen. But one of the things that I am doing right now is I am being asked to come in and talk to clients. And last year I was asked to talk to 90— well, no, I shouldn't say that. I was asked to talk to a lot. I said yes to 90 different events last year around the concept of like, what is this thing, AI? So my talk track was very much kind of the introduction to artificial intelligence and bringing AI into your organization. And in my keynote, my top 3 questions that came out of research that I had done as well as Microsoft had done and that the IDC reported on was like, what are these questions that executives are asking and how do we, you know, what, what's, what is the most important thing to kind of be thinking about right now? Now, I don't know if you've noticed, if you are in my algorithm and you are You know, if you have trained your algorithm as I have trained mine, I didn't really, but I get lots of content around the world of agentic AI. It is the new buzzword. It is the 2025. And it's weird to have a new thing like, you know, 16 days in or 17 days into the year. Like it is a very strong message. So I wanna talk a little bit about that, but more kind of the evolution of it. So the number one question that I often get when I go to an organization before I've even gotten on stage when they're just trying to figure out, can I help them? Is like, how do I get an executive to say yes to this stuff? Like, how do we get funding to build this? So many of us are enthusiasts for AI. I mean, that's really what the I Love AI community is all about. We're all enthusiasts. We're super excited. What happens if you get excited about something and now you need to actually get funding so that you could do it for your job, or at least portion of your job could be dedicated to it? And I wanted to share a couple of the strategies I've used in order to get AI projects off the ground, or at least to get some attention on the type of AI solutions that I wanna build so that my organization maybe shifts some funding in my direction. It's been very successful so far. Now, of course, I own my own company, so I get to choose what I invest in and what I, you know, invest in the people who work with me and my partners and my ecosystem. I get to make those choices, but for 28 years, that decision wasn't helped by me, and I had to influence my leadership. And so a lot of, I think, a lot of the AI leadership skills that you need is in the area of influence. And many of you will say, or I've heard you say to me, that you're not a seller, right? That you're, you don't sell, that you are not a salesperson, you're an engineer, or you're a whatever, fill in the blank. I'm not sales, I'm this. Whatever that is. And the reality is, is that we're all selling all the time. And AI specifically requires us to be persuasive with someone who may either be scared of the technology or may not truly understand the technology, or often a combination of the two. What's up, Okey? Good to see you. And so what I wanna share with you is the strategies I have used. And some of you have been through my courses, maybe will be familiar with this, but it also is a chance for you to ask some questions. But I always like to give you some value, right? Some education, some piece of— I used— I have a podcast called Noelle's Notebook where, um, I, I just pull a notebook. I mean, I have tons of notebooks. I'll just pull a notebook off the shelf and just read you a page of what's in there. And often it'll be a note I took at a conference or an idea I got. Um, and so this is a page from Noelle's Notebook, uh, around how I got and gained traction for AI work in different environments or different scenarios. So the first thing, as a principal, I became someone who, of course, you know this, this is the theme of I Love AI, of our community, is we learn by doing. We don't just, you know, watch YouTube. We don't just watch Twitch livestreams or TikTok. We don't just scroll. We actually put our fingers on a keyboard and we implement. Pardon me. And we implement. And so I think it's a really important part of who I am as an individual that I'm always looking for ways to actually implement technology as opposed to just learn technology. Learn and be curious is a leadership principle at Amazon. I learned so much during my 4 years at Amazon, Learn and be curious was one of the leadership principles. It actually was, I can't remember. I feel like they introduced it in one of the years that I was there, that it wasn't original part of the 14, but they added it. But either way, maybe it's not and I'm remembering it incorrectly, but I do know like that is a strong part of who I am. However, it's not enough to learn or be curious. It sits in tension and in coordination with another leadership principle at Amazon, which is bias for action. And that's literally who I am. I learn, I'm curious, I'm constantly looking for cool new stuff, and then I take massive action. I build. So many of you know at Amazon Alexa, I mean, I've done this multiple times in my career. I did it at VMware when I was learning about virtualization and middleware. I did it at Amazon Web Services when I learned to be a cloud architect. Like, I identify an area of interest, which you will do now in the world of AI. You're gonna have to pick a lane so you can separate the wheat from the chaff, the noise from the signal. Right? So you're gonna have to pick a area you wanna focus on and then not only learn and be curious in that area, but take massive action. So at Alexa, when people around me were building one app, maybe two apps, I built over 100 apps. Like, I over-indexed on building. The benefit of that is, yes, of course, I built a lot of applications. I got millions of users to use them, which I never would've dreamed would've been a thing that I would ever say, cuz I'm not like an indie app builder. But that's what ended up happening as a result. But what I got from it was I got hundreds and I mean thousands of human hours building. And I struggled, I broke things, I fixed things. I then, when I went in front of, you know, and that is in the first year of Alexa, I spent another 3 years talking to clients. And when I would go into those clients, I'd be like, oh my gosh, yep, I ran into that problem. Here's how I fixed it. Oh yeah, I, I remember. Oh my gosh, that was so frustrating. I could speak with complete empathy for their struggle, but I was on the other side. I could provide them the epiphany, right Cynthia? Like I could get, I'm like, oh, I know, I know your pain. Sometimes we say that and we don't actually know people's pain. It is true. Like you can tell the difference when someone's like, oh my gosh, I, And how can you tell the difference? Because they actually give you a solution you can use. And this is why I believe in the philosophy of being a solutions architect. Always be thinking about and inventing on behalf, innovating on behalf of your customers or whoever you're trying to convince. What do they need right now? So I'll take it from a couple different lenses and I've built for all of them. One is for a client, right? So a client comes to me and says, this is a problem we need to fix. I immediately start, hopefully I've already done my homework, I've already put in the reps so I can pull from that experience to help build a solution that'll be helpful. But I, I also implement my learn and be curious. I find out about their organization. I found about, I listen to their earnings calls. No one listens to earnings calls unless they're like financially obligated or legally obligated or employment obligated to do so. But you know how much you learn from a company's earnings calls, their vibe, how they talk about things, the problems they admit to, whether that's the whole story or not, it's super valuable, especially again as a solutions architect where your job is to build a pinpoint solution. But that is usually an entry point to an enterprise-scale challenge that they're having. And so that's one of the unique things that I do. I learn and go outside the typical area for figuring out, like, how do I learn more about you as an organization? The easy— I don't wanna say easy. One option you have for doing this is just ask questions. Ask good questions. This is where the diversity in the way that you think actually will help you. Many of us are like, oh, I think differently than everyone in the room. And in the past, I would say the first 20 years of my career, I would literally be like sitting back like this. And in my mind I'm like, that's not going to work. Oh, I wouldn't do that. Oh, that's a bad idea. But now in the world of AI, I actually feel empowered to say something when I see something. And I hope you do too, because without our lived experience, our lived experience in the world of AI, in the world of ChatGPT, that is actually someone else and often a big demographic of a user base that's gonna use the technology that you're building. So when you have that thought, it's— you can't just sit back and go, oh, let's see how that works out. Like, now we have as AI leaders a responsibility to say, you know what, if we don't fix this, this whole demographic of people, they're gonna fall into this hole and we don't want that. And you're the only one in the room who will have that perspective because you're the only one who's lived that experience. And so I actually, you know, I'm gonna give you, I'm not gonna get on a soapbox specifically, but I'm going to gently dance around it, um, around the topic of DE&I right now, right? A lot of people are a little bit concerned about the dismantling of DE&I in organizations, but here's what I want. I wanna give you some hope is that AI requires diverse and equitable and inclusive teams that are going to test and harden these models for production. We're not in the hardening model production stage yet, right? We're just getting started. We're just starting to put agents together. We're just starting to orchestrate agent workflows. But eventually someone's going to need to be able to say, I represent our customer. I represent a portion of our customer. I represent a new customer base. And that team that does that work, that red team, is going to be the most diverse and inclusive team in the entire organization. And it will look a lot like a DE&I organization. That's my vision. That's, that's what I see. It is also for those who are leading the world in production AI systems, their teams, their responsible AI teams and their red team teams are very diverse for exactly this reason. The more people, the more eyes you have on it from different lived experiences, the better they will be be able to ask a question you do not want to answer in production, that you want to answer in test and in design. So that leads me— so that is a huge question, right? And that leads me to kind of what it turns into for executives is how do we make sure that whatever cool idea you have doesn't end up hurting the company, doesn't hurt our partners, doesn't hurt our customers. And the number one thing I do as a practitioner is I build to help the helper. And this is a tried and true philosophy that has served me very well over the last decade, is that I look inside organizations and try to help people that are already doing the work. This is what Agentic AI is all about, right? Is going in and building systems that help the humans that are doing the work right now. Those humans want that help. It's not like they're like, oh my gosh, I'm so worried about my job. Most of them, if they don't know anything about AI, they start in that fear-centered mentality. Like, what if an AI bot can do everything I do? When they learn AI, they realize there aren't bots that can do everything they do, certainly not in the sequence required by the compliance or company, you know, policies. Like, there are human processes in place that make it very difficult to create a completely autonomous system. I mean, ask Tesla. Like, complete autonomy is very difficult to achieve. And we're just getting started. So even if that is the end goal, right now we need to help the helpers, and that's how we gain traction internally. So what I ended up doing in the organization that I helped build is that we ended up looking at internal organizations and finding out where the friction was. The number one way to find out what friction is, is to sit down with someone and ask them what hurts them every day, what bothers them, what frustrates them, what is the worst thing that they have to do? What takes them the longest? Where's the, where's the friction? Where's the bottleneck? If you go in, and I'll just give you an example from Metropolitan Museum of Art. A few years ago, Microsoft and, and I, we went in there, we brought in a bunch of data scientists from MIT. We brought in, um, a bunch of curators from the Met. We sat down in a room and we did a hackathon to figure out how could we use AI to solve art problems. Art, A-R-T, art problems. And as you can imagine, they, We're like, we're good. Like, we're, we're good. We don't, we don't need AI or tech for that matter. What we do is special. And I hear that all the time. What we do is special. It's unique. You can't use AI. It's not a technical problem, it's human problem. So we're like, oh, of course. Yeah, absolutely. What ended up triggering a change, and I will tell you, the producer came to me at the end of day one and was like, are you sure things are going okay? 'Cause I, I'm not sure they're going okay. Um, I think it might be broken. And I was like, just wait, just wait. We got, we got some time. And so what we ended up doing, and this is what truly becomes the art that you will have to master in the world of AI, is we need— the person we're building for needs to trust that what we're going to do will actually help them. And I'll give you an example. So I, when I was at Amazon Alexa, the year it launched, 2014, in November, November was a crazy month for me that year. November 1st, I gave birth to my third child. Yay! November 6th, Amazon Alexa was born, meaning it went into market. I had already been working on it for 9 months, but it also was birthed that same week. Then 2 weeks later, my dad, a Marine running across the Mercer Island Bridge in Seattle, gets hit as a runner, gets hit in the middle of the road by a car. He's now in the intensive care unit. So now I've got my dad in the intensive care unit, a brand new baby. So I'm in the intensive care unit with my dad and my 3-week-old baby, and I'm launching a pro— a brand new product. Um, and so when people came up to me, and they did when I went back to work, how are you? How's everything going? Anyone wanna guess what I said back to them? It's fine. Fine. It's good. It's all good. Was I good? Look, my cat's like, are you okay? It was all good, right? It was all fine, but it wasn't at all. But when somebody asks you in passing, like, I know they don't really wanna know. And that's literally how the curators at the Met felt about us passing data scientists. Y'all don't really wanna help us. Like, you don't care about me. But here's what happened that week at Alexa is someone, one of my friends, stopped me in the hall at day 1 and said, put their hand on my shoulder and was like, but no, really, like, how's it going? Like, are you okay? You just had a baby. Like, that must be tough. And you know what happened? I like lost it. I was like, and then this happened, and then this happened, and then this happened, and then I went and did this, and I just like unleashed all of this very authentic friction in my life on this person who had the audacity to stop, hang out with me for a few minutes, put their arm on my, you know, hand on my shoulder and ask me truly. And I believed that they wanted to know. And it was the most therapeutic thing ever. I know, right? It was the most therapeutic thing ever. And as a result, now she of course could help me and it all, all worked well. But leveraging that lesson of like, sometimes we don't tell people what we really need if we don't trust that you actually are listening. And in the world of AI, when you're building AI solutions, you need that trust to build something for them. So I have— there's a phrase in, um, in accessibility, never build for us without us. So if you're in an accessibility community, my son is in a Down syndrome community. I wanted so many times to build a Down syndrome app, but I'm not a person with Down syndrome. And my son is now 18. He will tell you, like, I don't have— I'm not— I don't have that lived experience. So me building an app for him, many times he's like, that's great, Mom. Yeah, I'm not going to use it, right? Or people who— technologists get super excited and build something for an audience they don't truly understand. I was sitting on a panel once, and on that panel, I was a bunch of data scientists, and someone in the audience stood up, and it was actually at the AI Data or the Data Salon in Miami. I think AI and Data Salon. Anyway, Data Salon in Miami. And the, someone in the audience was a UX researcher and stood up and said, I'd like to understand your relationship with UX researchers. 4 out of 5 data scientists, I was the one, 4 out of 5 had never worked with a UX researcher, had never worked with someone who would tell them that the tech, the model, the capability that they were building would never inform them how the people who would use it would actually use it. They'd never even interacted with one. I literally, when they all were like, "I don't know, I don't even know what you're talking about," my mouth like fell off. I was like, "Wait, what?" As a data scientist, that's a huge, like, opportunity for us to not build something for a group without a group. So I learned that from the accessibility commit, like, commitment that I have with my son and my dad. But it now permeates through everything I do. That as I go to an organization like the Metropolitan Museum of Art and I talk to those curators, I now need to, number one, build trust with them so that they tell me what's hurting them and then use their input. I didn't then go, thanks for the ideas, I'll go build something. We sat side by side for another 24 hours. We built 17 projects. Two of them became so popular, one of them made it to NBC Nightly News. If you go to my X or Twitter, uh, page, my pinned post is the day that that went live because they promoted a video, a longer video where I got to talk about my son. And that part was truncated in the one that went live on, uh, NBC Nightly News. So creating this as an AI leader, yes, of course it's about the model and about the tech. We ended up building a GAN that generated, art. This was all before, you know, before ChatGPT launched or Midjourney or any of these models. But, um, but at that time it was a struggle because without that trust, those curators were like, that's not art. You can't use AI to build art. Like that's, that's not art. You can't call it like, that was literally the friction. They didn't even quantify, they couldn't categorize it as art in their mind. By the end of our hackathon, they realized that the artis— the artistry actually can come in different formats, from the art we use to train a model to the art of configuring a model to demonstrate, like in a GAN, to actually generate the images and transform the images. So it opened their mind, but none of that would have been possible unless we got the team to actually go, oh, you actually do care about our outcomes. So we built a model for the Metropolitan Museum of Art that allowed people with special needs shocker, um, to navigate the Metropolitan Museum of Art. Eventually was then, uh, also, um, we did it for the Louvre, we did it for MoMA, um, and so these different museums, it's very difficult for someone with cognitive disabilities or physical disabilities to kind of walk around for hours and hours on end, something that I used to love to do. So how do I get them to have an equally enriching experience without having to use that UI, if you will, that user experience. So it was really good. But that trust, I think, became a core component of how I built everything after that. So once you know that you have to build trust, now I'm building— now I'm in a company, I'm creating a brand new, uh, generative AI practice. We need our CEO to go, oh, I like what you're doing here. I wanna give you more money. So what's the first thing we'd wanna do? Build something. Remember, help the helper. Build something for the CEO that makes the CEO's life better, where, where that CEO looks at it and goes, okay, that's pretty cool. And again, in order to do that, you either have to have a great relationship with the CEO, which is hard to do sometimes, but you can become close with their direct reports. What do you report on? What are you trying to give back? How often do you do that reporting? One of the flexes I did, uh, in demonstrating to a CEO that we wanted to build for them is that we created the ability for them to move from monthly reporting to hourly reporting. Real— it's not even real time, it's hourly, so it's still not real time, but it, it seems like real time because the CEO's not gonna look at that report every hour. Anytime they look at it, it seemed new to them. They're like, whoa, it's already refreshed. There's already new data. I know what happened this morning by 3 o'clock in the afternoon. We invented use cases that served the very person we were trying to convince. So if you have a manager, what are their pains? If you have a chief risk officer, a financial officer, I mean, I've built for any of these kind of groups or, or roles within an organization, but you have to build trust with their teams to find out what's the big friction that you can build for when you build something that resonates with them. And this is not new to AI. This is like solution-based. So we call it solution sales or consultative selling. Like, find out what they need. And then I always say, like, help them by actually helping them. Like, just build something that's useful for free. Yeah, I know, I know. Uh, but build it for free. Again, this is not for free because your time— they're paying for your time if you're an employee. I call this intrapreneurship. And if you recruit the right people to help you build that thing, you bubble it up to the CEO. The CEO's like, okay, that's pretty awesome. And if you want to know the details, you can let me know. I can tell you. But we built this application that truncated something that took 4 weeks into 2 days. And even the 2 days was a stretch because I'm like, technically, the data we gave was good the day we gave it, like, within an hour. But it took 2 days to validate that the information the model created was good. Now you don't have to do that. Right now, there are technologies available that help you do groundedness detection. But that, those philosophies, right, of learning and being curious, but then taking massive action, gaining trust with the person you're trying to, or community you're trying to build for, and then build iteratively with them side by side, demonstrating to them the value that you're creating in an agile way, right? Agile. There's that word. I don't know how many of you have ascribed to building in an agile way, or I, last year I got a chance to be on, on the stage at Safe for Agile, Safe Agile implementers. And it's such a powerful framework when you build this way, truly, right? When you actually build incrementally that you identify the, but you have to know what you wanna do, break it up into small pieces, work backwards. Some of you were in our work backwards session at the beginning of the year, right? When we work backwards. Yeah, right. I agree with myself. When we work backwards, from the problem and then break it up into small pieces and deliver value incrementally. I always say like these generative AI projects that I'm selling, they, they deliv— I, I make, you know, I might sell a million dollar project, $300K, you know, $300K at a time or $50K at a time or $20K at a time, right? I wanna deliver incremental value that proves that, hey, what you're doing is working and now we do more. So that's for the CEO, for founders that are trying, you know, gaining, this kind of respect with clients, it's a little harder cuz you don't have, you're not an employee, so you don't have access to a lot of the same information you would have if you were an employee inside the company. If you're going externally though, it's still not that difficult because we have generative models that understand kind of the basic human psyche. Um, but we also have an opportunity to do things we know they have a struggle with. And again, if you don't know, maybe I won't presume, you can ask generative models like, hey, This is my customer, supply chain manufacturer between $100 and $500 million in revenue. What are their top struggles? Like, it knows because we've done research on this. Public published research has been done about this. So you can use a generative model to help you brainstorm on what is the most important problem you can help solve. And then when you get on a call with these people, or when you start doing your own webinars, or when you start creating content, The only content you wanna create is the content that answers the question in the mind of your customer, in the mind of your manager, in the mind of your leader. What are they thinking about right now? And can you build a model that helps them solve that problem? Yes, you can. Is it hard? Uh, yes, but it comes to practice and you get better and better every time you do it. That's why I built 100 apps. I always ha— I have a challenge, um, that we're gonna run this year to build 100 custom GPTs. I am writing a book with a few people in our AI Leadership Institute I literally picked them in the institute because they were my early customers and I said, let's write a book together. And it's called, it's an OpenAI GPT builder book. And I was like, let's build 100 GPTs. Turned out we can't build 100 because it's too long. So we are, we're gonna do, we hope to hit 20 or maybe 25. But, but when you build this many, like, that's kind of the moral of the story. When you are learning and being curious and you're like, ooh, I see this model, I see this tool. Massive action. Build, build, build. And you don't have to know what you're doing to start. I, at Alexa, I didn't know anything about natural language. I didn't know anything about artificial intelligence. I just went into GitHub and started cloning projects and rebuilding them. And I didn't know what I was doing. I was just following steps, like typing, copying code. But what happens is, I don't know if you're familiar with this term, the reticular activation system. Like, when you look at code and you copy it, your mind starts processing what you're seeing and then looking for similar patterns and other things that you're doing. So as you look at new projects, you start to see patterns. And then over time, I think it took me about 7 projects that I rebuilt on GitHub before I was like, I can build my own thing. And then I started building my own and then I took off. So really, really, I think really exciting, really interesting world we're in right now because being a builder is not a, it's not a, like a skill you need to go and take a technology bootcamp for. All you need to do is have clarity of thought, have an audience you wanna build for, hopefully a collaborative partner that is a representation of that audience that can work with you and provide you user experience insight. And then the persistence, the resilience to be able to keep building until it works. AI Leadership Institute, my company, I started this company in 2016. There were— I always told people I was selling vegetables to kids. Like, nobody really wanted to hear what I was saying. And now I'm coming into my own. But that's literally how it works, is that you start something, no one's listening. It's called the Valley of Death. That's like a valley of death whenever you start something. No one's paying attention, no one's liking your posts, no one's using your models, no one's subscribing to your content. Like, and then all of a sudden you start to gain traction. Through consistency, through persistence, through resilience. And then what's really the reality of it is you actually get good at the thing over time. You get good at it. You can get good at it faster through massive action. But over time, like now, AI leadership, the concept of building a center of excellence inside a company, the concept of building, um, an ethics review board, the concept of building an engineering team to support it, security infrastructure, Uh, you know, middleware that manages latency and caching. Like, these are now very available tools in my toolbox because I've been using them for decades. Like, that is how you end up— but it has to start with, oops, I don't know that. Like, that's how I always say everyone starts at awful before they get to awesome. Some go faster on that trajectory because they put in more reps. And they're willing to work hard to do it. But I also have a philosophy that I personally adhere to where I work hard in silence and I let my success be my noise. Like, I don't, I don't, you know, do too much where I'm like, hey, look at me, I'm doing this thing. I mean, this is a call where I hope I get some of my stuff in my brain. I share that with you. But the reality is, is that I work really hard when no one's watching in hopes that I build something useful. A company invests in it, buys it, has me build it for them, and then the world sees that. And that's been true my entire career. So I used to build enterprise Java code for the largest companies in the world, and people would always ask me what I do, and I'd be like, well, you know, Bank of America? And then they'd be like, yeah, you built the Bank of America website? I'm like, well, not exactly that, but the speed at which you are able to do a transaction. Yeah, that was me, right? And so my success was in the actual application, the usage. And with AI, That would've taken me 3 years to do 20 years ago. That is available to do in a day. I mean, I can build an entire system end to end in a single day at a company. I can't put it into production because there's, that's when all the work comes in of validating it, testing it, right? User experience, all of that. But the work it takes to actually build the scaffolding to set up a project to deliver value for your customers, for your company, for your team. You— there's never been a better time to be able to do that quickly. So it allows us to focus, I think, on bigger and better questions and problems. So hopefully you found that helpful. That's like my AI leadership tip of the day is kind of the process by which I have acquired clients, that I have gotten jobs. I mean, even to get the job at Alexa, like, I didn't get the job and then learn Alexa. I was on GitHub building Alexa apps before I got that interview. And so similarly, now, if you wanna work in AI, be building in AI every day. Build models, post them on GitHub, post them on, uh, create a school of your own. I have a school community, couple of them. Um, create a school, get people, you know, say, I built a model, you can use it if you join my school, I'll teach you how I did it. Like, create a Twitch channel, a YouTube channel. It doesn't actually matter if anyone listens. Like, that's the, the vanity metric of followers and likes and comments. That's not the goal. The goal is to generate enough confidence that you can say out loud, you do this thing and you're good at it and you've tested it. Remember how we started the conversation, right? Like, I wanna be able to say, oh my gosh, I, that problem you're having, I had that same problem. I built 200 of these applications. I've created hun— you, all of us should have at least 50 GPTs under our belt, which means going through the 5 Ps of prompt engineering. So that leads me to some updates. If you have any questions or comments, please don't hesitate. You can throw 'em in the chat. Or hey there, or you can throw them in the Q&A section so I don't miss them. But I think hopefully I'm going to go into a couple updates. And if you have questions on that as well, we have really exciting stuff coming to both the AI Leadership Institute as well as to the I Love AI community. So I'll start with I Love AI because I'm dressed for it. I'm about to head out on a plane. In about 20 minutes, I'll be headed out of my door, hopefully on time. So if you got questions, now's the time to ask them. And you could just raise your hand in the Zoom if you want to. I can unmute you and bring you up and you can ask your questions. But one of the things that we're doing in the I Love AI community is that February is Love Month. And in my case, it's Why I Love AI Month. So the 9th through the 14th, that whole week from 12 to 1:30, we will be doing a special event every single day to help build and qualify your knowledge in the world of AI. We have a day dedicated to building a career in AI. That is gonna be on Thursday. I'm host— I'm gonna be delivering a session inside a Maven course, partnered with 5 other professionals, and it's about how to get a job in AI. So that will be one of our days. And that is always— last year we did the same thing. We had one day dedicated to career, one day dedicated to building a company, because some of us are in this moment, which I was at a year ago, where I was like, do I start my own company or get another job? And today it's easier than ever to kind of make that choice. I'd say 5 years ago I didn't even really think too much about going to my own company. It was easier for me to get a job. But now with the friction associated with getting a job in this market and the like separating the noise out as a hiring manager, knowing who's telling me the truth and who's lying, like it's very difficult. So hiring processes are taking longer. There's more applicants because more people are, you know, laid off. Like, we have a bunch of different economic variables that are impacting kind of getting a, a J-O-B. So I encourage you, like, one of our days will be focused on what if you decide to just go out on your own? How much would it take for you to make a 6-figure income, $200K, $300K, $400K without actually getting a job? And so I will share some of my strategies on that on Tuesday. Hopefully, one of the days, but I think it's gonna be Tuesday. We've been selected— AI Leadership Institute was selected as the Agency of the Month for an organization. So I'm super excited. We're gonna be announcing that. They're going to be collaborating with us on content, and you'll get a chance to build an agentic AI system on that platform. So really excited to do that. You'll get an agentic AI workshop certification if you choose to do the work. So you can attend, everyone can attend, but you, in order to get the certification, you actually have to do the exercises. And then, as you know, you'll have to deliver a video training me on what you learned. And this is a big part of what differentiates us in the AI Leadership Institute is that whenever you take a live learning lab or a certification through the AI Leadership Institute, the way we qualify your experience is not did you watch the videos and did you pass the skills you know, assessments, the knowledge tests at the end. It's more about can you say out loud that you did the thing that you did? Can you describe it? Can you talk about it? Your ability to communicate those soft skills that they say is your superpower in the, like, from now on, like a lot of people are going to say they can do a thing even if they've never done that thing. And your ability to actually talk about what you've really done is going to be incredibly important to your ultimate success. Hopefully that will get you in the habit of actually producing content in the world outside of your certifications. But this is my little push, my little nudge for you to learn how to record your— you don't have to— it doesn't have to be your face, but it has to be like you talking about what you did, demonstrating your product. And this is a skill I found once you learn it, it allows you to get known in the world and it's really, really important. Thanks, Char. Thank you so much. Yeah, exactly. Oh my gosh, you are. Yes, helping people that are either jobless or in transition or have a job they hate. I mean, that's kind of— I feel for them too. Like a lot of us, I have a class that I teach called How to Get a Job in 72 Hours. So if you're jobless, you can get a job in 72 hours. Like I can guarantee it. Some of you are already there like, well, what job is that? Whoa, whoa, whoa, I don't want every job. I don't want any job. I want like the job I want. Um, and so I, I think it's an important realization, right? Like we have a choice. Like we can go get a job that I can show you how to get a job in 72 hours. That's, that's not, not difficult. It's just you won't, you may not want that job. It may not be in a field that you care about. Most of the time when I teach people that course at the end, they're like, but I don't wanna do that work. I'm like, yeah, but you could if you really want to. But that's where the world of AI changes everything is that now I can choose, and I can choose to build my own organization. I can choose not to. I could be a solopreneur and just do the gig economy thing. And there are ways to do this really successfully. So we're gonna take the week. I'm also gonna be partnering with an organization called The Source. I met them at the Startup World Cup. It was called Startup World Cup. I was one of the sessions, uh, at the Startup World Cup. I met them there. Um, some of— yes, The Source, you would know Yara, cuz they're here locally in Miami. So we're gonna start hosting generative AI for professional classes at the source. And again, to your exact point there, Yara, like include, like being able to help people, specifically underrepresented people, like people like me who came from Homestead, Florida, or came from Kendall, or, you know, these cities in Miami where your trajectory is not to go to Harvard or MIT or Stanford, like maybe, but maybe not, maybe in Kendall. Um, but it's also just as easy that someone in your family or someone in your community or at your church or at your school will be like, yeah, you're not, you're not capable, you're not smart enough, you're not into math, you're not good at math. All this nonsense that people tell you when you're 16, 17 years old that shift the trajectory of what you will do forever, potentially. Certainly that was my case until luckily I found technology and was like, wait, wait, wait, none of that is true. None of it. None of it. So I am very passionate about creating that opportunity. We have some sponsors that are going to sponsor those classes so that we we can bring in people who have never been exposed to technology or AI as a career path and be like, or as an entrepreneurial path and get them on their journey. Um, and really create a whole new life for them. So I'm super excited about that. Yeah. So The Source, um, so that's one of the things we'll be doing. Um, back to the week of February 14th. So we have the, uh, agency announcement. So we're gonna do an Agentic AI workshop one day. We're gonna do, um, how to, start an AI career. So more on the professional side. And then we have a consultancy day, how to build a consultancy and grow that consultancy. In our AI Leadership Institute, I just launched what we're calling the AI Leadership Lab. And for some of you who saw, there's like a, a YouTube series called the How to Build an AI Consultancy in 2025. There's also a Solutions Architect series, but the consultancy one, which is how to build like a company so you can go get clients and start doing work. I built this class, but with it I had the 6 Ps. So basically 6 different steps to building a business. And it was like, prepare your business, create a website, build a, you know, create a way for them to pay you, create a way for people to contact you, get an email address, a phone number, a domain, like all that stuff. And so the first P was prepare. The second P was purpose, like define the purpose of your organization, your unique value proposition, your unique, your unique selling proposition. Then define your product, like what actually are you going to sell? And there's lots of things to sell. Then there's a process called Million Dollar Math. This is probably my favorite session that we all did together where you figure out what it's gonna take to make a million dollars this year or next year, like, or in 2 years. It doesn't matter the timeline, you can pick it. I say in a year, we're in January, say I wanna make a million dollars. What are all the different ways to do it? Well, you can get one customer to pay you a million dollars. 2 customers pay you $500K, right? 10 customers pay you $100K. So all of a sudden, like, $1 million, it becomes kind of feasible. Like, $100K. Now, once you figure out, like, these kind of price points, you gotta think to yourself, what can I do that's worth $100,000? What can I do that's worth $10,000? You— it allows you to really start expanding your mind. Like, if I can build something that's worth value-wise $10,000, I need to sell 100 people on that. Let's go. So that I have a, uh, so that's one of the P's is like, what product are you going to create? What? So the next P is pricing, and then positioning and pitching, which is marketing. So sales, marketing, and then finally delivery, or putting your, your practice into practice, right? I called it production. How do you get to production? How do you get what, and that's my technical world, but, but what I did is I developed 5 to 7 models per area, custom models that I created for the AI Leadership Institute members. So you can go in, it's like $500 a month if you are a client of mine. Like I just, it's one of our continuity products, so it's $500 a month, but you get it for free if you're part of the AI Leadership Institute. So I'm giving it to the members now. I just gave it to two. I'm getting their feedback, kind of design partnering. I mean, it's built, so, uh, but I separated it across the 6 different Ps. I have 5 to 7 models in each P, and these models are meant to, in a workflow, right? Like, let's say I, I'm gonna, I need to build a funnel to drive sales for a product I wanna sell. So there's a model that helps you ideate on the product, write the copy, build the funnel, create the domain, set up the website, create the email campaign, set up a CRM to capture the leads. Like, all of that are models that I've provided to truncate the amount of work you'd have to do if you had to go figure it out on your own. And this is meant to also be an example to you of what you could do. Anything you do in your mind that you're like, I have this process, this sequence in which I think about things, you can now train a model and sell access to that model. This week we had in our AI Leadership Institute, we had a live learning lab around digital twins, creating a digital twin. I'm going to change some of your lives right now. I mentioned this on the last call. There is a platform called Pickle, pickle.ai. I don't know if Sherilyn is here and can throw that in the chat, but if not, I'm going to go grab it really quick. It's hilarious. Pickle.ai. I think I still have it. I'm just going to type it in and I'll throw it in the chat. I think it's .ai. I ended up Googling it because I didn't know, but I'm going to try that and see if it works. It's always dangerous. Yeah, I didn't spell that right. So instead I'm gonna like just search for pickle avatar and see what— yeah, there it is. Oh yeah, of course I didn't— it's getpickle.ai. Of course, of course it is. Oh yeah, cool. Thank you, Sherilyn. Awesome. So getpickle.ai. Imagine if you will, you are on a call and just scroll through the sales page. It's so awesome. So you want, you know, you have these calls, these Zoom calls. You create a digital version of yourself, a digital version of yourself, and this digital version of yourself, like this deepfake of you. In the past, there was actually another company called Bueller, and Bueller would allow you to create a deepfake of yourself that would sit on large team meetings cuz it wouldn't say anything. You would just be there like, you know, like just so it would allow you not to actually actively be there, but it would look like you were there. So that would become, your picture. Now though, it's an actual deepfake of you. So you can put this beautiful person, uh, version of you on the Zoom call and you will unmute the line and start talking and the deepfake will match to your words. So you talk, it doesn't look like you. I mean, introverts unite. Like, like we never have to be on another call again. Yay. Um, But it's cool. Like what I, what it reminded me of and why I mentioned it is that imagine again creating, we did, uh, this live learning lab that allowed us to create a digital twin of ourselves. So train it on all the content or articles or, uh, blog posts or anything that we've ever, you know, any podcasts I've done or keynotes. I train this model on that, which I could do today in a text-based model, but then I put it in an avatar and allow someone to actually talk to me and get the advice that I would give them in person, but instead get that advice via avatar. Um, right, I'm an ENFJ, so yeah, and I don't think I am, but I apparently I am. But yes, exactly, Tara. Um, blank NFJs love it, but I'm an ENFJ. Um, but yeah, exactly, INFJs 100%. Um, Oh, exactly, Robert. Oh my gosh. So this is a clarification I also had to make because I have been doing digital twins kind of in the manufacturing space, like, like what you're referring to back in the day when we would actually digital twin a system or an ecosystem or a distribution center or a warehouse. This is actually digital twinning you, which The people who created this platform and called it a digital twin, I'm pretty sure were completely unaware that that word is already used in the industry. But that's why, I mean, you could do anything you want these days. But yeah, absolutely. So, but that's okay. Yeah, yeah, exactly, exactly. Yes. So anyway, but yes, interesting stuff. Like this tech is, it's so fascinating. So I always like to introduce you one, some leadership topics to be thinking about around what we talked about at the beginning, right? Learn and be curious, bias for action, and then empathy. Make sure that you have a user experience expert, somebody who understands. Never build a system for someone without that someone, someone who represents lived experience. You might be that person, but like, even me, I'm passionate about being a caregiver, but I would never build an app as a caregiver for my dad that I'm caring for, I would wanna find out at least maybe from a clinician or something like what happens to people with traumatic brain injuries? Like how does that work? Um, and make sure I'm building very, very closely aligned with the people that actually know, uh, that demographic. Um, yeah, so you can check out the Live Learning Lab. Yeah, we have it in there. Um, oh yeah, for sure, Robert. Yeah, the Notebook LM. Me too. So now I hope you don't— I almost bought Pickle and I stopped myself. Sometimes you gotta stop the crazy. Like, do I need— it was very tempting, but I did not buy it. Maybe I'll figure out a way to get them to give me a copy for free. Um, but it was very tempting, like, and it's got a monthly thing, but I was gonna just buy the year. It was, it, it was cool. Um, so if I can introduce you to new tech that potentially would become a, a shiny button you go click on, you're welcome. Um, but yeah, it's, uh, but NotebookLM is very cool, but it's also a bit dangerous. So I don't know what— I was talking to somebody, maybe it was a client, about this earlier this week that, you know, when you go into NotebookLM, it says very clearly, first you have to log into your Google account. So it's grounded to a degree, right? Like it's in your tenant, if you will. But it says like in the, you know, privacy statement as well as in the terms of service that it is guard-railed, if you will, or, or governed by your Gmail account. But at the bottom of that terms of service, it's like, however, we are in beta and therefore do not guarantee any of this, like any of the terms of service. So basically completely remove themselves from accountability for behavior of, of NotebookLM. Um, and that's the danger, right? These are the types of things that I try to tell organizations that wanna use cool new tools. I'm like, Sure, but read the terms of service. And guess what? We can read the terms of service by just taking them, copy paste into ChatGPT and ask a very simple question. What should I be worried about in here? Like, don't overcomplicate it. Don't think you have to read every EULA, every user agreement on your phone, but take some of the important ones where you maybe were worried about, um, or think you should be worried about, copy and paste them into GPT and just give You know, I think that's a, that's probably an app waiting for someone to write, like, tell me how secure, or, uh, educate me on the terms of service of the apps. Most of us have 75 or more apps on our phone. And I know this because I'll just give you a rundown of my schedule. I did bring it, uh, for this purpose. Um, so obviously let's hang out together for an hour a day during the week of Valentine's Day for the I Love AI week. I hope you'll join us. They are available for you to register, like say you're coming on LinkedIn. There are events there you can go and say hello. But I just want to give you a sense of where I will be. So this Friday, or today, I'm flying to Scottsdale. I'll be teaching and talking to executives in the supply chain industry this week. Next week, or the week after that, I will be at San Francisco. So if anyone's in San Francisco, I'll be in San Francisco at the MAMA event, and this is a mobile app conference from AppsFlyers. It's a huge conference, and I don't know if you know this, but the world of mobile app development is changing fast. So my goal is to give them some advice and guidance on how to navigate when the, the thing you were building is not the thing anymore. Like, how do you create value when you can now completely automate the development of a web app right now? It's gonna be more about Knowing your customer and thank you, Noelle, um, knowing your customer and getting the data. Like, it's going to your, your responsibilities. As with all of us, whatever we do now, as AI comes to take away the mundane tasks, whatever we do now, we're gonna have to reinvent who we are in a world where we don't have to do those things. And the sooner you start that reinvention process and that transformation process, the more successful you will be. So start like now. Now start today. Um, so I will be, uh, there, and then, um, that is in San Francisco the week of the 28th. Um, then I will be, uh, let's see, in February, just to keep you— oh, February 12th. Oh yeah, I forgot to mention, I got an award from, uh, DCA Live, a company in DC. Uh, I got awarded a— one of their awards for AI and cyber leadership. So they're hosting an event. If you're in DC, I hope you'll come. I put It's posted on LinkedIn. There's also a link to grab tickets if you wanna join me there. We'll be having a little party, little soiree to celebrate all of the people who were given this award. Some of my favorite people, if you don't know them, Dia Nguyen from— she's a responsible AI expert over at AWS. Seema Alexander, she runs DC Tech and Startup Week in DC, the largest tech and startup conference in DC that happens every year. So some of my favorite people are on this list, so hopefully you all— yes, thank you. It's so exciting to win something, especially when you don't know it's happening. You know, many times I get like letters that say, pay me $350 and you can be awarded this thing. And I'm like, I didn't know how that's how this worked. I didn't know you could pay to get an award. And, and so I was like, I don't want that kind. So when I get surprised, which is what happened. I saw on LinkedIn they tagged me on the award category with the other nominees, and I was like, this is awesome. So I'm excited. I'll be flying to DC for that event. But I will be in DC likely the day before and the day after, so I will be teaching a couple of classes for local clients in the DC area. So if you're in DC, I hope I'll see you there. Then my daughter's birthday. Yay! And then I will be— oh my gosh, in— did you guys are not not specifically concerned about this, but I will be running the Disney Princess Half Marathon. Disney, uh, RunDisney race weekend is the 21st, um, and so I will be doing that. And I'm actually not just running a half marathon. The half marathon is on Sunday. I will be running a 10K on Saturday and the half marathon on Sunday. They, uh, I used to run a different race at Disney and they called it the Goofy because you're, you're goofy if you do it. They don't do that for princesses, so it's called the Fairy Tale, which is way more appropriate. Like it's a fairy, uh, fairytale to run the 10K, then the, uh, then the, um, 13.1 the next day. So I'm excited for it. I've been running like crazy. I will be, uh, dressed as your fa— my favorite. I don't know what character I'm gonna dress as yet, but whatever that is, it'll be my favorite at the time. Maybe Spider Gwen from the, you know, DC or Marvel Universe, maybe. I don't know. I have to figure it out. Maybe Moana, so I don't have to do anything with my hair. We'll see. We'll see what happens. I was Moana last year, so I can't do it again. So that's happening. And then at the end, I will be speaking here in Miami. Yara, maybe I can get you a free pass. I'll be speaking here in Miami at the Fontainebleau on responsible AI to executives in the local area. And then I will also be in Tennessee talking to Autodesk. So, oh, and I got an invite. In April, which I'm not going all the way out, but just to let you know, I will be the keynote on day 1 of the RSA conference in the— anyone remember the name of the— I always forget it, but it's the, the big conference center I've spoken at so many times in San Francisco. It starts with an M. Moscone. Yeah. So I'll be at the Moscone, Moscone, Moscone Center. Anyway, super excited about it. I haven't spoken there since the J— like my Java days. So I'm really, really excited for that. That too. So thanks for joining me. I'm looking, I don't see any questions in the chat. I mean, I, I answered them kind of as we went, but no Q&A. Thank you all. I do, my, my, my car is here ready to whisk me off to the airport. I am always available on Skool, but you also can get an immediate response from me if I'm not on stage or on a Zoom like this. I'm available on LinkedIn as well. Those are the 2 best ways to connect with me. If you send me an email, I'm doing my best. It's a, it's a, it's a crazy world in that inbox. But if you want to get in touch with me right away, just ping me on school or ping me on LinkedIn. My, whatever's in my brain, I give to you. I hope you will use it in, you know, good health. I truly believe that everyone on this call, like, the world is waiting for us to just step into what we know and help companies deliver value, help people learn this technology. There's so much opportunity. It's just a matter of getting curious and taking massive action. And I am your partner in that. Thank you all for being here. I am so grateful for you. Thank you for being here. I love AI. Don't forget, when we do this week, you're gonna get your own t-shirt if you join us. There's a VIP opportunity for you to get a t-shirt, and it's only given out in this week. So then you have to wait. Um, so, uh, a lot of people ask me, how do I get a t-shirt? I'm like, you either have to take a class from me live, which most people can't do, or you have to show up at this challenge. So now's your chance. All right, we'll see you all later. Thank you, everybody, for joining, and we'll see you next time. Bye.