I ❤️ AI Q&A: How to Design Responsible AI Systems that Scale

Right, here we go. Welcome everybody to I Love AI, because I do. Welcome in, so nice to see you. It's great to see you all happy. I would say Friday, but it's not Friday, it's Monday. So hopefully you all had an amazing, wonderful weekend. Welcome in. I'm trying to maintain my, you know, it's very well hydrated in South Florida right now for those of you are here, but I am trying to work on that myself. So pardon me. Some of you remember a few months ago when I lost my voice, so I have to constantly battle making sure I drink enough. So thanks for that. Welcome everyone. Good to see you, Marisol. We were just talking about you. I have a In the last session, we were talking about on Thursday, we'll just kick this right off with some announcements. So welcome to the I Love AI call. This is our community call. For those of you who are not aware, you can join us live on Zoom, which means you get to ask questions, unmute your mic, and have fun with all of us. You also get a chance to break out into little breakout rooms and connect with each other, which we will do at the end of today's call. It is such a delight to be here with you. We were— we normally do this call on Fridays, but because I was actually at the International Cyber Risk Summit, an incredible event, I was there on Thursday and Friday. Thursday, I was the keynote, and I also delivered an onstage whiteboard presentation on how to design scalable, safe, and responsible AI solutions. And it was really fun. I love it because, you know, you see that look in people's face like, oh my gosh, I just learned something, one that I did not know I needed to know. And I pushed kind of the edges of their brain. So I always say, if, if your brain hurts a little bit, I've done my job. And I feel like it was a really great session. Lots of people were very, very complimentary of the session. Can't wait for you all to see it if you haven't done so yet. I also did a miniature version of that session. Workshop during our Rise Up AI Challenge. It's actually on day 2. And as a matter of fact, I think day 2 VIP, we ended up— I forgot to record it or something happened with the recording. So I ended up using a prior recording of that session that I'd never published before. So if you are inside the I Love AI community, you can go and check it out. It is there for you. So good to see you all. Thank you for being here. We are in the summer. Um, most, I guess, things in general kind of stop during the summer. I don't, uh, call me Alexander Hamilton. I am nonstop. I do not stop mostly because I truly enjoy this time we get to spend together. I enjoy meeting and getting to know all of you. I enjoy being part of your journey. Hopefully you enjoy also being part of mine. We, as I mentioned, are here every Friday or Monday, depending on travel, uh, allowing us to really have a chance to just realize that we're on this journey together. And there is so, so much for us to learn as we go. We do tend to fight overwhelm with enthusiasm here. And that is kind of the excitement I think there is today. I figured I would start, number one, Marisol, you had asked a question during the challenge, I think, or maybe it was after the challenge about creating or walking everyone through using an AI tool to build out a scorecard. And so rather than use this time, which is kind of public, everyone gets to see. We're actually gonna create a webinar for Thursday, this coming Thursday. We're gonna do it on Zoom. It's free. You just have to sign up, but that'll allow us to, like, do it in a way that I can reuse it. So hopefully you'll be okay with that. But we're gonna walk through a couple of different tools. So the idea is that one of the most interesting and engaging ways to communicate to people as an AI solutions architect, which is one of my favorite roles, or really in general, is often to give them a way to kind of rate or develop a baseline of their current performance. And so scorecards are often used for that. There's a third-party company, I think they're called Scorecard App or something like that, that you can use a SaaS product to build them. But today in the, you know, emergence of artificial intelligence, there are a couple AI tools that you can use. I, in less than 20 minutes, leveraged a tool called Gamma. So on Thursday, we're going to be doing an introduction to asset creation in GAMA. It's not only going to include the development of a GAMA resource, but also publishing of that resource to a website. So I'm going to— for just so you all can see what we're referring to, I'm going to also— let's see here. Oh, okay. Skye's Notetaker sent me a private message, but I'm not going to look at it. But here it is. If you want to go take a look at the outcome of what we're going to talk through, it is my own website. It's called gamma.upskilling.ai/scorecard. I hope it works. You'll have to let me know. Maybe I'll click on it and make sure. Yeah, that'll do it. So this is the scorecard. You can actually download a sample of what the scorecard will do, or you could take the assessment yourself. Um, here's the thing though, is that this was provided as part of our AI, uh, Rise Up AI Challenge. So the intent was not to use this to generate leads, um, or collect people's information or use that data. This data is actually only accessible to you. You'll see that it was used for our participants during the June 30th to, uh, July 4th timeframe. So if you go and take a look at it, you will see it, but it's kind of cool. So if you want to build something similar to this for your customers, if you want to, we're also gonna talk about how do you do this in a way that it actually does become a lead magnet that you can use this data to generate you know, have time, put time on a calendar with a prospect. Those of you who are in this stage of your, you know, entrepreneurial journey, or if you are working for a company that would allow you to do this, I hope you'll join us. It's going to be Thursday, likely at 8 PM, which is when I do most of my Thursday sessions after dinner. It'll be AI After Dark, where I'll show you how to do asset creation in Gamma. So hopefully you'll enjoy that a little bit. So, Marisol, what do you think? Is it what all you hoped it would be?

Yes, it is. Oh my gosh, thank you. I want to say thank you to Skye for passing on the message.

Yes, absolutely.

Yes, yes. No, this is amazing. One, I thought the scorecard was amazing, and you're right, it was so useful for our project that we did, and it just gave me an opportunity to try to assess my team as well. And so I really appreciate this. I look forward to it, and thank you so much for Um, everyone who's on right now, you have to understand, whatever it is that you're asking in this, in this platform, um, you're gonna get a response. So here it is, perfect example. You need to join this, um, if you're thinking about joining like the AI Leadership Institute. I mean, that's amazing. This is also a great portal. I couldn't make it to the 2 PM, um, I just had a conflict, but thank you so much. I'm looking forward to it.

Yes.

Thank you so much. Yes, you're right, exactly that. I always look for questions and then my first question is like, how many people can I help with the answer? So that's why we took it from— I could have just called you and been like, hey, let's talk, um, but I was like, oh, but if we do it in a webinar, we can save it, we can share it with as many people as possible. And I do think it's a really cool— I think it's something that used to be hard that's now easier, uh, but it does still require a little bit of clarity of thought on what you're going to do and how you're going to do it. So that's what we're going to cover. So I'm so glad. Thank you for having the idea. And, uh, similarly, if you all have any questions about tools or resources, or you see something that we do as a company and you want to know how we did it, we hold no secrets. Um, but we do like to create opportunities for us to teach as many people as possible kind of what we're doing. And that is what we do in the AI Leadership Institute, right? So in the institute, literally, it's kind of like the behind the scenes of how we're growing the company, what we do for lead gen, how we, uh, market the company, how we deliver sales calls, how we actually implement and deliver with excellence once we actually get a deal. All of that is like, we, we basically talk about all the details, the nitty-gritty details with the members of the institute. So hopefully you can replicate the same thing. And Nitin is here. Hopefully, I think you were gonna talk to Padmini today. Hopefully you had a chance to do that earlier.

Oh, good.

Yes.

Yep.

So I will join you for the next one.

Um, okay.

I had a conflict unfortunately.

Yep.

But hopefully you enjoyed your time. Um, so awesome.

Yay.

Amazing. So thank you all for being here. Um, alright, so on that note, We always, I always like to try and tee up something that I can share with you. We do have a couple of updates that I have to share that are pretty amazing. I have been posting about it all week. The week started, first of all, with the celebration of our 10th anniversary as the AI Leadership Institute. And I always like to tell a little bit of that backstory that I was at Amazon doing a lot of executive briefings around the concept of artificial intelligence and working for Alexa and, like, I was just constantly talking to people about what the future would hold, the future we're experiencing right now. But this was 11, 12 years ago, right? Where I'm like, hey, it's coming. Voice AI, text to execution. Like, this is the world that we're, we're coming into. And I realized in, you know, I started at Alexa in 2014. By 2015, I was like, this is a thing. Um, and actually more towards, you know, I, I think I joined the team in the early part of the year. By midyear, I had built over 50, 60 apps for Alexa. They were doing very well, and I just realized, man, I need to get out there and start talking about this. So I formed the AI Leadership Institute, and at that time, it was simply to segregate the work that I was doing to advocate for AI use, specifically natural language. Many of you know I have a son with— thank you for that. I have a son with Down syndrome. And so my journey, my reason for getting into this space and starting to advocate for artificial intelligence solutions was driven primarily by accessibility, that I really wanted us all to adopt voice interfaces because that would reduce the amount of things my son needed to learn to participate in the world, right? If we all decided to build a voice UI, a voice user interface, for every application that we built as companies, my son, the only skill he would really need to really get good at would be talking, would be communicating, that he would have this vehicle for executing code, launching applications, building financial systems, creating healthcare, uh, appointments. Like everything would open up if he just had a UI he could use. And his voice was something I was willing to work with him on. And of course now he's extremely verbal as a result of that. Um, but, but that's really what drove me, you know, 10 years ago to kind of start AI Leadership Institute was to encourage companies like, hey, if you're gonna build, build with voice, build with natural language as an interface. And it took a long time, a good 8 years, uh, before people really started to take it seriously. Um, and now we're now, you know, almost 11 years after that, and we're just starting to see companies really implement this at scale. And thankfully, I think due to the work that we started at Alexa that continued at Google Assistant, that was then of course commoditized and made available to everyone through platforms like ChatGPT and Gemini and Claude. So it's, it's exciting. It's an exciting time. What's up, Lucy? Great to have you in the house. Good to see you. Um, so that is kind of why I started the company. But yeah, we just celebrated year 10. We have, uh, over 3.4 million learners. Million people have gone through some level of training, uh, that I've delivered over the years. And, and I think it's, A little bit more than that, but that's like, I feel like that's a conservative number that I could be like, I, I could document exa— 3.4 million. There's many more that I didn't document that I didn't write down the numbers for. Um, but it's pretty exciting cuz I had a goal at one point to, you know, we all write these mission statements, right? I had a mission that I was going to use the, the technology that I uncovered at Amazon Alexa, that I was going to talk about that and I was gonna empower a million people. And now I've empowered 3.4 million. So Noelle Russell has to come up with a new metric. And of course that number goes from a million to, right, the magic, the brick, right? The, the billion. So now I'm on a mission to impact a billion people with this technology. And of course that is an extension through all of you, right? As you learn, as you get excited, as you stay excited, as you see value, you'll hopefully share that with people that you know, people you don't know. Um, and we all become advocates of a technology that literally does make the world a better place. Uh, so, so excited for that. Um, but that was not where it ended. So that happened on like, I think that was Tuesday. On Wednesday I get the coveted email, the coveted moment when every year I have to reapply to get the Microsoft MVP award. I'll share it with you all in case you've never seen one before, but this is what mine looks like, right? So this is our MVP award. You can see I have discs for every year I've been an MVP, which up until this year I was at 4. So this year on Wednesday I got the email that gave me my 5th DISC. So now I will be, uh, my 5th year as MVP starts now. But most importantly, 2 new categories that were not categories when I started. As a matter of fact, AI was barely a category when I started. I was one of the first to be awarded in that category. But more importantly, we've got 2 specialized categories that are specifically Noelle Russell Russell. Like one, I am, uh, I got awarded MVP in the area of Azure AI Foundry, which means I'm going to be pushing the envelope and really like pushing the opportunity that we have to build solutions inside Azure AI Foundry. What that means for you all is a lot of the free education, a lot of the training and the walkthroughs that I do will likely be in this tool because, well, they gave me an award and I like to reward them for that. The second one though was Trustworthy AI, not a category we had in the past. It used to be called Responsible AI, but this is the first year for Trustworthy AI. And of course, many of you know, this is is like my ethos, right? How do you not only be a builder, but how do you build safely and responsibly? And I got awarded in both categories, so I'm so excited for that. I could not be happier. I'm super, you know, grateful and thankful to the Microsoft team. They do make their selections. It is possible to not get selected, and so I recognize that. And I, of course, many of you know, I work very hard to do the work that I do, so it's really cool to be recognized. For all of that work. And then I got to seal last week by presenting the keynote at one of the really one of the strongest represented conferences that I have been at in a very long time, specifically in the area of cybersecurity and risk. It was called the International Cyber Risk Summit, and Katie Arrington was there. She was just an incredible presence. In the US government was there. We had lots of different government contractors, people who had built some of the foundational technology in the government that the government uses today were there. It was very, very cool, very humbling experience. But I got to be one of the keynotes. I then also got to stand on stage and do a whiteboard presentation of how I believe what I think is really important in designing AI solutions that are safe and responsible. And I now have in my keynote that I do, my keynote has a new title. It's basically Scaling Responsible AI, From Enthusiasm to Execution. The name of my book, same, same idea, right? For those of you who haven't gotten it yet, I'm— I shipped more books today. We have a long line of books to ship, but I have a bunch of them stacked up right there ready to go. But this is the book. But inside this book, I have two kind of concepts that I talk about consistently, and I've coined them kind of this concept of poets POETS and JEDI. So POETS as in like poet laureates or people that are poetic, and JEDI, well, you know, like Luke Skywalker and Yoda. So, but what it really means is POET, of course, is an acronym. I come from IBM. I was raised in IBM. My first job was IBM. So that's, you know, I'm just prone to acronyms, but POET stands for Precision, Optimization, ethics, and trust. And it literally is the stair stack of capabilities that I find successful companies are going through, right? Like figuring out how do you use data to create really precise outcomes? How do you optimize what you're already doing with AI as opposed to trying to boil the ocean? How do you make sure that there's ethical foundations? And at the end of the day, if you don't have humans who work for you that trust you, if you don't have customers and partners that trust you, Trust is everything. Jeff Bezos was really strong about that, that you can, you know, it takes a long time to earn trust. It takes a second to lose it. And you have to be just narrowly focused, um, on maintaining trust with everyone in your ecosystem. And I think that's a, we're not seeing it quite yet. We're starting to see it bubble up in some implementations, but it is a critical ingredient to every scalable AI system I've ever been a part of. The other part is JEDI. That's my, one of my favorite things. Renee Cummings, if you don't know who she is, please look her up. She is amazing. Renee Cummings, she is a professor at, she's a professor of data science, I think entrepreneur in residence at the University of West Virginia. She's phenomenal, but she's also a world-renowned speaker, and she talks a lot about the importance of today being an AI activist. And part of her description of that is becoming an AI Jedi. And I do think that at least the people I see here, we would be qualified as this. But those of us who, when we approach a solution, right, we identify a problem, we identify the data we need, we pick a model to solve that problem. Once all that's set up, right, I call it an MRP or minimum remarkable product. Once that's set up, what happens next? Like, what's the next thing to happen? And the next thing that happens is basically we need to figure out, like, how do we make sure that that system is fair? How do we make sure it's accurate? How do we make sure it's trustworthy? And so the, the acronym of JEDI stands for every solution we build, we build through the lens of justice, right? Through the lens of equity, through the lens of inclusion and diversity. We find that it's not just ethnicity and gender. That are important when building these systems, which of course, yes, please do that. But in addition to that, it's the neurodiversity, right? Like when you build an AI system, you have no idea who's going to talk to it. Is it going to be a special needs mom in a moment of need? Is it going to be someone who's struggling with mental health issues? Is it going to be somebody who never went to high school? All of these personas need to be present from the very beginning, all the way through deployment and ongoing maintenance of these systems to ensure that they continue to serve not only the people that those systems were built for, but they actually serve everyone. And so that Poets and Jedis has just kind of caught on. And so now I use it in my keynote to represent very important practices that every organization really needs to start thinking about. Now, I do have one thing that I wanted to share with you all from an educational perspective that I've that I shared with people last week, and it was— it resonated really well. But actually, it became something that also showed up in a— showed up in a conversation that I had. So in addition to the International Cyber Risk Summit, which you can look it up, it actually was live on Zoom, live recorded. So you could probably go back and catch the replay on LinkedIn Live. But the one— one thing that was really interesting about that is that I got to leave the summit on Friday and go and be on a really cool podcast with a good friend of mine, Sima Alexander. She has a podcast called The AI CEO, and she's interviewed some incredible AI CEOs across government, public sector, as well as entrepreneurs, big companies. It's a really cool collection to be a part of. As a matter of fact, some of our leaders from the AI Leadership Institute were also on the podcast earlier that week. I think she did 3 last week. Anyway, But one of the questions she asked me, and I would love— I would be very, very interested in hearing your perspective. Um, my kids taught me that I need to call you all chat, like that's the name of you, you all. So I'd be like, all right, chat, you need to let me know what you think about this. That's like a young person's way of saying it. Um, but chat, I would love your opinion on, or, or even maybe what, how you would have responded to this question. So I'm stuck in, you know, rapid fire questions, uh, that Sima's asking me about AI, about humanity, um, about trust. And one of the rapid-fire questions was, hey, if you were in a room with Satya Nadella, um, if you were in the room with Satya Nadella, uh, Sam Altman, Jensen Huang, um, you know, like a few of the leaders of the biggest AI models in the world, what would you, like, if you had a chance, if you had their ear, what would be the one question you would ask them? And I think this is interesting, um, for a couple reasons. One, and I'll tell you what my one question was, uh, that I would ask, but like, I think it's an interesting question to ask because we do actually have the chance to use our own devices, our own mechanisms for uncovering what that truth might look like. But I think it's important because I do right now believe we are in a bit of a golden age that we have And I don't— you'll, you'll notice I was very specific in the CEOs that I mentioned, but we have lots of pretty good CEOs that are, in my opinion, empathetic. They're good leaders. Um, you know, Satya Nadella, I, I couldn't say more good things about him. I wouldn't have worked for a Microsoft that he didn't build. I mean, that he was the reason that I ended up going there at the end of the day. Um, but I also see this in Jensen and the people that work for him. Like, I know some of his his direct reports as friends. I don't know Jensen Huang at all. I don't know, I've never met him, but I know his direct reports and what they say about him and how he listens when they talk. And some of these are underrepresented women, right? Like, it's just, these are cool leaders that we have doing this work right now. But my question to them, of course, if they're saying in front of me, my question to them is, you know, I actually was laughing with the AI leadership team earlier today. I would kind of quote the King in Hamilton, right? I'd be like, okay, what comes next? Like now that we've kind of got this momentum going and everything's all good and we've got good leaders in place and those leaders are making relatively good decisions, they're at least being thoughtful about climate, they're being thoughtful about ESG, they're being thoughtful about cyber and quantum. Like it's a good energy, but what happens when they go away? Like what is the succession plan? How do we make sure that we don't accidentally get, you know, that one of these systems doesn't get acquired by the Death Star, right? That an evil empire doesn't come in and dismantle all of the good things that these organizations are trying to do with their systems. That's my question. Like, what happens next? Now, here's the good news, is that, you know, in order to uncover maybe what happens next, number one, I'm positive that there's a succession plan that is pretty standard in executive ranks. But that's not really what I'm worried about, right? I'm, I'm more worried about how does the ethos of a personal mission to build good things, how do you carry that on when you don't, you can't really, I mean, I don't know. I don't know how you'd be able to like predict the behavior. I know, for example, I don't know, maybe people knew what they were getting back in the day, but there have been leaders of big companies like Microsoft that were not awesome. And if they were leaders today, we would be worried. There are other leaders today of technology companies that worry us as ethicists, that worry us as activists, like that they might not be looking out for the best interest of everyone. They might be very siloed in their, you know, in their perspective and in their goals and mission as a company. So building systems that serve everyone is a very personal goal, right, of mine. But what happens when I have leaders that do not support even listening to a mission that includes that, right? Even if I was willing to do it for free, would actually dismantle anything that would enable me to have that conversation. This is my concern. It's a little— I mean, I don't know, it is what it is. But here's the, the good news is that I can use AI systems.

How—

I don't know how many of you have thought through this before, but if you think about, you know, in my mind, I, I always say success leaves clues, that we've got lots of big companies that have been growing up in the age of AI, some of them a lot around much longer than others, but all of them have clues, clues in the documents that they write, clues in the GitHub repos that they publish, clues in the leadership. So for example, when I was at Amazon, every single year I printed off the stakeholder letter that Jeff Bezos would write to his stakeholders, and I would read it and highlight it and be like, what? He was so good at crystallizing what he was trying to say in very few words. It was like one of his superpowers. And I really, like, I, I spent time doing that. Another thing today that I spend time doing in order to kind of get a pulse of direction inside these companies that seem to be a black box is I look at the roles that they have open. I meant to mention that earlier today, but I look at the roles they have open. I just, uh, was listening to commentary on OpenAI's, um, move to offer execution as a service, something that I do myself. Many of you on this call do. Right? We offer execution as a service where in a world where anyone can adopt a baby tiger, right? Little Bruiser here, right? Anyone can adopt a baby tiger. In a world where that's true, it's how you use that system, right? How do you execute? How do you deliver results? How do you get an outcome that changes the business in a positive way? How do you take a baby model and turn it into a model that generates hundreds of millions of dollars in new revenue or reduces, right, the amount of time employees take to do a task, allowing them to be hundreds of percent more productive, right? These outcomes are entirely possible, but they are not indicative of the model that you choose. They don't start when you pick a model. They start when you execute on a model, right? When you actually build a model and use it to complete a task or to, what's the word I want to use? Like, I basically, I want to set a, a goal for my business and I want an AI system, an agentic system to help me achieve that goal, whether it's revenue generation or cost optimization. So the future is in the execution. And I'll just say like the next maybe 2 years at least is everyone's adopting little baby models. If you are someone who knows how to implement them to a successful outcome, you're gonna be pretty successful. And that now can be echoed or reinforced by the direction of a company like OpenAI to really move in this direction. So I was looking at their open recs and saw that they had open recs in the area of like account management, sales, uh, go-to-market. I think it's fascinating to see, right? Like you wanna look at these companies, Anthropic, OpenAI, Meta in their AI divisions. What humans are they hiring? I think it's really interesting to look at, right? What humans do they think in AI? Like Salesforce, right? Salesforce, the CEO has already mandated you cannot hire humans, right? You cannot hire humans if you can get an AI system to do the work. So the first thing I'm gonna do is go look at what, what humans are you hiring? If you are new, let's say you are right out of transition, and of course I know that's I've been there. I know it's a hard time to be like, oh no, I thought I was secure and safe and now I'm unemployed. But success leaves clues, right? There are organizations, big organizations that are hiring, not for every role, but the ones they are hiring for is a great clue of the direction to go in. Now, we were meeting with one of our clients and they recently released, um, a really cool report, a jobs report based on a bunch of data that they had partnered with the data organization to build. And I was very happy to find out that in this jobs report, there was a bunch of new roles, AI roles that had created, but number 2 on that list was AI Solutions Architect, that, that is one of the fastest growing roles. And the reason why is because AI Solutions Architecture is the exact step that precedes execution, doing the work, building a model that actually scales and does its job. AI Solutions Architecture is the pre-work to building successful scalable models. So I think it's awesome. AI Solutions Architecture is my jam. That is my favorite job. I've been a solution architect my entire career. They may have named it different things as I went to different roles, but at the end of the day, my job was to understand engineering enough because I'm a builder, understand the business enough because I am a business, you know, I'm empathetic to the side of the business, but who is the glue that's going to hold those two things together? How are we gonna use technology to amplify business results? And who's the person who can tell that story and build at least the initial minimum remarkable product? That's what I do. So as a result of that, we are gonna be launching a brand new course, a certification actually, um, AI certified AI Solutions Architect. It's gonna be launched on Maven. We're gonna be doing it in August, back to school. Um, we have an entire back to school campaign that we're running at the AI Leadership Institute. It's gonna include 3 certifications, one of which is AI Solutions Architecture. Another one is Agentic AI Practitioner, where you get to learn to build an agent from scratch. But then you also have the ability to learn how to take those systems and get them to talk to each other. MCP, A2A, you get the idea. But then we also, of course, have a little bit of a higher level certification, which I also think is critical, which is Building Responsible Systems. So we'll have a Responsible AI Leader certification to round out the month of August. If you wanna learn more, just ping me. But I, the reason I think these courses are important is number one, I speak from direct experience building some of the largest models in the world. What I saw us work, what, what I saw working and what I saw just dismal failing. And I wanna make sure that as we educate people who are going to move into solution architecture, trained or not, because it's a required component of building enterprise systems. That role is gonna be filled by someone. I'd prefer it be filled by someone who at least knows what I know. And for those of you on the call who are consultants or architects or have a lot of domain knowledge or expertise in this area, I'd encourage you also to get into at least some mechanism for letting the industry professionals that are gonna need this skillset letting them buy those skills from you. It's an incredible, incredible time for that. Um, yay, good! I'm so excited. It is going to be a great month. So I am taking, uh, I'm— it's a little slower the last two, um, last two weeks of July for me. One, of course, I want to spend some time with my family before things kick up in August. Um, but I'm also going to be doing two things. Oh, I think I'm con— I just signed this contract, so I can tell you all Do any of you know the organization Mindvalley? I don't know if you would know it. Um, Mindvalley, it's really exciting. You can look them up.

Yay!

Oh, Kim, you would because you're, you're like me, like you're a Mindvalley kind of person. But if you look them up, they're international. Uh, Vishnu is the CEO of this company. It's all about kind of human growth, human potential, which I absolutely love. They do a lot of work in the space of like just personal development. Um, they've decided to move into complementing personal development with AI systems, but specifically, how do I help people really uncover the art of a, a side hustle that can one day become your real hustle, which is my journey exactly. Like, you know, some of us, the, the longer you've been in career, we call it golden handcuffs, right? The longer you've been in career, the more expensive you become. Right? The higher your salary is, the more benefits you get. And so you get these golden handcuffs where you're like, oh my gosh, if I wanted to start something, I'd have to be making 6 figures, like on the high end, in order to replace my current income or, or compensation package. Like, it becomes very hard. So I, of course, spent 10 years kind of build— building that bridge and eventually getting to the point where I could just cut over. I actually teach a little bit of that in the Solution Architect course, but, but that is such a— yes, right. Oh my gosh, exactly. Mindvalley and I, we're like this. I've— I'm a consumer as much as I am, but they hired me now to be the keynote for their AI summit, and I'm also going to be teaching a deep dive session on how to build a 7-figure company, basically how to go from Zero to a million in ARR, or annual recurring revenue, as a single person, which means you're gonna learn a whole bunch of agent AI. So I'm gonna teach the— in that session, you're gonna learn how to build your own agent and then build a bunch of them, tee them together, and maybe even create your own advisory board like I have for myself, right? I have an advisory board where I've trained it on my favorite CMOs, chief marketing officers, my favorite, um, chief revenue officers or growth people, right? People who run sales teams, my favorite sellers. Um, I've also got one on finance. Finance is probably, you know, like spreadsheets and all the things, like all expense reports, not my favorite. Um, so I've created an AI system to help me with that and make it seem easy, which has been nice. Uh, and so all of these different areas of the business to complement me as a single employee and help me generate si— 7 figures, 8 figures, 9-figure business. I do think we are going to see the first billion-dollar business run by a single person in this new agentic AI world. Actually, I believe that company probably is already created. It's just a matter of whether or not that person quits before they get there. Um, but it's possible now. We do have the ability to build an agentic workforce to complement every human. In a large, large company, we're even seeing agentic AI being used to complement directors and above. And this is where what I— the trend I'm seeing is HR meets tech, right? Where the human resources organization— I don't know if you'd have opinions about HR. I certainly had mine as I was climbing the ranks. I didn't really think that they were for me, right, as the employee. But now I actually, you know, now I've had to really rethink, and this is true for every role, but HR, human resources, human capital, the people that, you know, lead and manage the people in the organization, their job becomes fundamentally important because in a world where we're gonna add agents, AI systems to help do the work, we need to understand who our humans are, what they do, what they wanna do, how, how do they wanna grow? What roles do they wanna take on? So that we can build complementary systems. We call it an agentic blueprint, that we build a complementary org chart that matches those humans directly. So for many— for my clients, they're starting at directors and above. So directors, VPs, SVPs, executive staff, every one of them gets at least one agent to start with that they begin to delegate work to. Call it a copilot. But the benefit of that, of course, is that that copilot or that agentic system is trained on the outcomes that that human is being measured by. The OKRs. How many of you know that book, right? The OKRs that you have. So imagine if you had an agent that was trained on your OKRs, and when you said, hey, this is what's happening, it could immediately be like, well, you're, uh, right now not gonna— you're trending in a direction that does not land you where you need to be. Here are 5 or 6 things you can do different today to move that trajectory. Oh man, like this is good stuff, but it hinges on human first, right? First, HR understands the humans that work for them. Second, HR partners with technology, partners with the tech team in order to build agents that complement that human work, right? Reena, oh my gosh, this is right in your wheelhouse. So of course I'm preaching to the choir a little bit in here, but I do think This is the future, right? Like, it is possible. Can I just go in and like take out all of my humans and build all agents and see some level of success? Maybe, but it will be very transactional, very tactical. Strategic success will be those companies that are human first and AI forward. I coined that earlier today. TM, right? But human first, AI forward, meaning that AI is not first. And as a matter of fact, I heard this from the, the leaders. I think I told you all this a couple weeks ago. The leaders at OpenAI and Meta and Anthropic, right? Like, they're not saying AI first unless they're building the model. But even then, they're saying, like, wait, no, we actually wanna make sure that the AI systems, like, in their case, they're the ones talking about building agents that support human work. And maybe we do need less humans to do a certain task, but it's still gonna require human intervention. We call it human in the loop, human on the loop, right? There has to be a human being like, hey, that's not cool, Mr. ChatGPT or Mrs. Claude. Like, I, I don't typically anthropomorphize my robots, but I wanna be able to give feedback to these systems as they scale to ensure their ground truth doesn't change, to ensure that they stay poetic and Jedi, right? Poets and Jedis make sure that they see through the lens of how do I make sure that this has a lens of justice, equity, diversity, and inclusion? How do we make sure that this model, as it scales, continues to serve as many people as possible? So I think it's interesting. We're starting to see this narrative. I definitely encourage you to, to do a little bit of research, maybe ask, you know, Azure OpenAI Service or ChatGPT reasoning models. You know, ask it to do a little bit of this research for you so you can see some of the reports and, and research that has gone into this. Stanford Human-Centered AI, MIT, uh, Business, um, there's a lot of different organizations that are focusing on kind of long-term impact of the decisions we're making now. And the success so far, the clues that are being left by successful organizations, is HR re-engages as the entity that knows humans that work for the company. They partner with technology to build agents that complement that human work, and the whole organization elevates. And I think it's worth looking into if you're in this space. So what I'm gonna ask you to do today, so that's my little learnings for, for a minute. What I'm curious for you all to kind of talk about amongst yourselves is, you know, I think last week we talked a little bit about agents, but I'm very curious about this, this concept, right? Like, what do you think? I actually— who, who asked me this? I think— oh no, I was on a client call earlier today and they asked me very specifically, what are your thoughts about human resources and artificial intelligence? What is the role of HR in the future? And no matter where you sit, I think it's a good thought process I just told you where I sit, so it doesn't really— we can agree, disagree. You might be able to see way further because you know this world better than I do. But I think it's an interesting thing to talk about. Like, what is your opinion on how human resources— what is the future of human resources? It certainly isn't to do what it was doing the last 20 years. It is being reinvented as we speak. Is your vision of that reinvention? So take a few minutes to think about it. I'm going to set up some of our breakout rooms. If you have a question for me live, you're welcome to raise your hand. Otherwise, in the next couple minutes, we're going to break out into groups and talk about this together. I'm going to try and keep an eye out for you if you raise your hand. And if someone— if someone sees a hand raised and I don't, let me know. But I'm going to put us in a couple rooms.

Mm-hmm.

If you get put in a room with a robot, um, please don't worry. I will remove the robot or I will move you, but give it a couple seconds. So if you're in a room with a robot and you're all by yourself, just wait and I'll move you around. Um, but, uh, but I would love this. And then of course my hope is that you're going to come back. I'm going to give you 10 minutes to talk amongst yourselves. We're going to come back and if some of you, not everyone, but if some of you want to share some of your learnings and certainly your perspective with all of those listening today, I would really be interested in seeing what you all think about this topic. But first, I think it's nice to get to know each other. So don't forget, this is your chance to practice your introduction. So you have one sentence. It's called the I help statement. You're going to say, I help whoever you help, your audience, right? So in my case, I help I help, you know, professionals in transition. That's just an example. I help professionals in transition learn the art of responsible AI at scale, and I do it through my really cool community called I Love AI.

What do you do?

Right? So a very succinct statement that says who you care about, like who you have a solution for, what you're solving for them, and maybe a little secret about how you solve it. Um, but no more than a minute apiece for your intro, and then let's get into it. All right, I'm gonna create these rooms. Let's make sure. Oh, cool, cool. Uh-oh, uh, I will move— Sky's no, take her out of that one. I will remove— okay, hold on, let me move to there.

Uh-oh.

All right, give me a second. All right, I got Patrick in the house, William's here, Yvette's here. Awesome. All right, Sandy's here. Oh, I have a, um, I don't think I forgot about you asking me for like my crazy whiteboard. I have a presentation, like a PowerPoint for you. So I will try to do that while we're on break and get it to you. All right, Kim.

All right, cool.

I'm going to move this person to 3. All right, that's 3. 1, 2. Oh, I got to move this person up to— I'm going to say 3. All right, rooms are open. Remember the question. I will also, as the voice of your captain speaking, I will come over the air and let you know when you have 2 minutes., before we break out. All right, try to give everyone a chance to talk. Hey, talk to you later! Go have fun! Bye! Rooms are open. Hit the button. Choose your own adventure. All good. All right, everybody, I just figured out how to get everyone in the room, and I think they're there. So if you are here, that means that you're connected with me live on LinkedIn Live or YouTube or Facebook or any of the other streaming platforms that we are publishing on. So welcome in. I would love to hear your opinions as well. Um, but I thought I'd give you a couple other, uh, questions that have come up, um, that I think are just interesting to consider and that we've used in our conversations, uh, in these breakout sessions as well. If you want to come, don't forget, if you want to come and learn, um, get a chance to meet fellow people on a similar journey as you but from a totally different path It's really cool to just have this experience together. These breakout rooms give us a chance to get to know each other one-on-one and really grow and learn together. Many of us start here having very little understanding of the world of AI, and then over time, we not only learn AI, we learn it in our specific part of the business, in our specific vertical or industry, and then we use that information to get a new job or start a new business, and we get to share all of our successes along the way, and it's so cool. I love watching everyone become more successful, get jobs they never thought they could get, and deliver with excellence in ways that they just never thought they would be able to do. Because sometimes we let the world think that journeys into the world of AI, artificial intelligence specifically, but machine learning, data science, virtual reality, augmented reality, quantum, Right? It— I don't know what it is, but as an industry, we tend to be like, this is hard, you don't belong here. And I'm trying to change all that. And so this is a room full of people, 20 people to 30 or 40 people a week that just come together and say, we're, we're here for it. We're here to help raise and increase the level of awareness for everyone on these really important and sometimes complicated topics. So that being said, another number one question that I often get asked when I am presenting— so I love those keynotes where I get up on stage and I do my thing, and then afterwards they open it up for Q&A. And so this week that also happened. I'm going to see if I can— I think I wrote them down so I could share them with you.

Yes.

So one question which I thought was pretty interesting, and I get it all the time, is, hey, I have kids who are in college or post-secondary, or I have kids that have chosen to go into computer science. Should I be worried about them? And I think it's really important to think about, think about that concept. There is a term that I've used lovingly genderly, caringly called Silver Tsunami, right? Like every company is in this moment where there's a silver tsunami happening. And what I mean is that there are people with silver hair, right, that have, you know, basically become an elder in the organization that know things no one else knows, that have critical tribal knowledge of how the business operates. They are beginning to leave the workforce, some of them intentionally, some of them are getting laid off, which I think is crazy, but no judgment. Um, but they're leaving the workforce like every second, you know, someone, uh, is leaving the workforce in this generation. And those who are new in the workforce, or even those in their first 5, maybe even 10 years of experience, they will never have the experiences that that Silver Tsunami generation has, right? Like, that generation grew up at a time where you could not just swipe left or right to, you know, accept or be rejected. Like, it was— you had to walk up to someone in a library and like pray they wouldn't laugh in your face, right? Like, you had— for your first client meeting, right, or the first time you called someone on the phone, like, you had to just call them. You couldn't like look them up on social and be like, oh, oh, look at their LinkedIn, it looks like they like this, we have this in common, I teeing myself up. It was like blind all the time. And the level of skills that you've learned when you do that, right, when you have to put yourself in a position of vulnerability and ask someone to listen to you, to partner with you, to connect with you, to date you, it's such a different experience. It's why I do a lot, a lot of— that's why I love being on stage. I like human-to-human communication. I like the vulnerability that's required when I get on a stage and I just say, here's who I am. I hope you'll like me. Like, I hope you'll work with me. I hope what I say will be something you realize you need. I mean, could I just send them cold emails via an AI system?

I guess.

But it's a different skill set. And I do think that part of my success is because I've had those hard days and I've learned those hard lessons. And it's taught me to be very persistent. So in a world where we've kind of got this instant gratification brewing, right, with the younger generation, and we've got this, you know, silver tsunami of, you know, deep expertise leaving the workforce, what are we gonna do? Like, what does the future look like? How will a younger generation be able to do the same things with the same level of excellence as a generation that learned the skills differently? I think it's an interesting question. I often am asked, you know, kind of what does that world look like when people are using ChatGPT to kind of help them along instead of using kind of their brain? We saw the research recently that said— what was that research that came out, right?

Who?

I can't remember. McKinsey, was it? Some of you know, you can put it in the chat. But basically, it's like your brain on ChatGPT, right? That you have this cognitive atrophy that begins to happen. And I saw this research years ago when predictive text first came out. I think Meta was the one that released this research, and they showed that— and it was back before they were Meta, they were Facebook back then— but they basically showed that if you got predictive text and you used it for 6 months, and then they took predictive text away, that you by yourself with no predictive text tool would be more likely to answer the messages with the way the machine trained you over the last 6 months, that you would end up with no help talking just like the machine, not reverting back to your pre-predictive text self. And we should think about that, right? Like, if we're gonna use AI to augment what we're doing, which I believe in, but if we use it to help us along, to help us come up with ideas, help us build out, flush out, right, things that we would have done on our own, but now we're going to use an AI to do that. And we take it away, like, do, do our brains have that ability? And that's what that Atrevid research is all about. Now, what I personally do and what I do in my family, we have a family-based— a lot of— another very popular question people ask me about is about fam, like, how I manage tech in my family. We do have a family platform, GPT platform. Everyone has their own account and they can use it to communicate. I also get to monitor everything anyway. I'm that mom. But they can use it to answer questions. But what the rules we have in our house, and I do this in my teams as well, is that you cannot use it to get off the blank page, that there is a cognitive benefit to building the page from blank to something, that you have to come up with something. You can then use it to edit. You can then use it to refine, but to come up with the idea and the dopamine, right? The serotonin that happens when you come up with an idea and then you begin to move forward with it. There's really no replacement for that. Maybe scrolling on TikTok, I guess. But the reality is, is that I support, like, my children, the way that they leverage this technology is to amplify their ideas, meaning the idea comes from them first. They are the producer, not the consumer. It is a philosophy in our house and something to be thinking about. All right, I'm about to send them a message letting them know they have 2 minutes left. So hold on. This is really fun. Come join the Zooms if you haven't done so yet. Hello everyone, this is your captain speaking. Sorry to interrupt. Uh, we have 2 minutes. So if somebody hasn't had a chance to share yet, now is the time. If you're done already, you can join back in the main room. See you soon. Isn't that fun?

Oh my God.

Okay, and then in 1 minute I will close the Zoom room. Normally I just kill the, uh, stream right now, but I got a chance. You and me, we get to just hang out, chat it up. I don't know if you noticed my shirt. It's a Red Hat shirt back in the day. Inclusion inspires innovation. It launched an entire campaign for me when I got this shirt, which I think was just like a, a thing. I created a website, I created a campaign, like I created a class on it. I was super inspired. So now I have what's called an inclusive innovation framework that goes along with it, helping people really manage these things. All right, 30 seconds. I think they're having a lot of fun because no one's come back yet. What is happening? All right, here we go. Close that. All right, I usually like to wait for at least one person to come back voluntarily, but it looks like they're having a good conversation. All right, closing the rooms. 60 seconds till they all come back, and then we get to hear from them, hear what they've come up with. Like, the first person to come back Oh, the note takers are the first ones to come back. Hello, welcome back, welcome back. Hello, hello. Hi, good to see you all. All right, anyone? Well, I guess we'll give everyone a chance to come back. It's a little tiny bit early. I also eject as soon as the timer comes up. I can't really think, I'm like under pressure, so I just leave. My voice of God. 6 seconds and they'll be back. I hope God sounds that enthusiastic when I meet her, right? Exactly, exactly. I saw some movie where— was it Alanis Morissette was God? What movie was that? Oh, I didn't see that.

Very cool.

It was really good though. Yeah, I can't remember what it was. I'll have to look it up. Yeah, I'll have to look it up. Um, but it was funny because I was like, okay, I could see that. Like, Alanis Morissette, this quirky— sure, it was pretty cool. All right, anyone want to share what you all were talking about? Anything interesting? Tell me what you were thinking.

Anything?

Well, first I want to say, Noelle, thank you for putting me in a room with 3 wonderful gentlemen. So that was the first.

Oh, Cool.

I didn't—

like, the universe did that. But that's awesome.

Okay, one of the things that we talked about was, um, you know, part of what HR could bring is a more empathetic view. Um, you know, now a lot of organizations have a lot of chatbots anyway, and so we're wondering, you know, what, what's going to come after that, you know, what's the thing? One of the ideas that was talked about was succession planning, but then there were a few others in terms of, you know, what would be ethical, you know, what's the ethical thing for HR to do and what's going to happen with all these folks that are displaced? How can they even purchase the services that many of these companies used to sell, right? And so just trying to figure out that whole cycle and what that's going to bring.

Oh my gosh, that's so important. Like, that's one of the things a long time ago before ChatGPT, Jeff Bezos would tell everyone is they, they would say at the end of the day, everyone's an Amazon customer. That was the ethos, right? Everyone's a customer. So if you lay them off, you do it in a way that they love you so much that they still buy from you, um, that you, you know, like you think about things and he would say like, we don't layoff. I don't know if you've, you know, seen, but like, it's a cultural thing. Like, you can't— if you want people to buy from you, you can't make them unemployed. And so he was very much against kind of mass layoffs in that way, because he's like, I mean, he's a retail company. But I thought it was an interesting way to think about it, because yeah, like, you— if every company was like, oh, let me just cut 10% of my workforce, it would like societal— it would societal impact. Like, the entire society would begin to crumble. Under the pressure of that many people unemployed. I mean, it would create the Great Depression on the heels of us thinking we were doing something good for, you know, for prosperity, and it actually would generate just the opposite.

And to some extent, that's what's happening right now.

I'm trying not to because someone just gave me an award. I'm trying not to even talk about it.

Okay, sorry.

I know, but I'm with you. I'm like, come on, man, I'm trying to like y'all and you're hurting me. So I'm trying. It's rough. What was this? Yeah, I'll edit this part in post, but okay, thank you.

No, I'm just kidding.

No, like, we should also be willing to be like authentic. Like, come on now. Um, yeah, and that it's— of course, all these organizations that do that, it is a numbers game, and I get it. And they like— it's very complex. It's not like they're just like, we want to get rid of people. Like, it's this shareholder value thing, and like, it's this complex capitalistic thing. Uh, and so I understand the complexity of it. I just— in a world where we're, we're still defining what good looks like, you know, what an AI agentic organization looks like, I think it's super premature. Like, I just feel like it's, you know, short-term leadership.

That was the other thing that we kind of talked about, is that if you wipe out the bottom layer of the pyramid, who's going to advance to those more senior levels? And you know, had they— what's the plan for that? I haven't heard a plan. Yep. So I think—

and this is like, some of you are HR, like you could be either a human resources person or at least adjacent. They need help. Like, this is a huge opportunity. I created a whole campaign for leaders in this space, but specifically those that were called to like DEI, and I called it From DEI to RAI: The Evolution of Human Resources. And it's basically like We did a lot of good work with DEI, but it wasn't for a, a reason. We didn't tie ourselves to revenue in that work. But now we can because that DEI work actually shows up as hardening production AI systems. Like, it's extremely valuable. But for some reason, well, it's because it's human resources. They've distanced themselves from the technology. That's why I said you'll see this pattern. We're already seeing it, like tech and HR. Are partnering together. And so if you're either tech and you like HR, or HR and you like tech, you actually could serve as the catalyst for bringing these two teams together in the future. The agentic future is HR and technology like this. So I think, you know, I don't know, mark my words. Let's talk again in 3 years and see if it works out. But every signal I am seeing is HR being like, what's my future here? And tech being like, What agents do we build? And to me, that, that's— and we're already seeing it, Salesforce consulting organizations, they're, they're bringing these two things together.

Cool.

Anyone else want to share what you talked about, learned, anything like that? I know, just consider it practice on the world stage.

Any—

anyone, anyone? I don't know, this William here, I was wondering if there would just be a push for AI resources. Because you got human resources and you got AI resources.

Interesting.

I love it.

So, you know, maybe there will be a department just called resources.

I don't know.

Interesting. You know, actually, that's a fascinating idea because I always— so there are some very dangerous misunderstandings about agentic, like we're in all of our documentation, we're calling them like teammates and that they will be partners. And the reality is, is that these are AI systems that actually should run. We've talked about this in like in a zero trust environment, like they should be at best untrusted contractors, right? They are not your teammates. They are outsourced systems that have access to data. Like you're going to want to give them like we're in, in security, it's called least privilege, right? You're going to want to give them the least possible privilege, not the most. And so I think there's a bit of, you know, the hype cycle, man. That's what it'll do to you. It'll get you going, we should use agents and they're going to be in our teams and they're going to show up in Slack. So one thing I think I did this on stage yesterday is I was like, one thing Microsoft did a long time ago, and this is for their human segregation, is they created a whole separate domain for people who did not work for Microsoft but worked for Microsoft, meaning W-2 versus 1099. And so Uh, if you're at Microsoft and you're on a 1099, you're V-Microsoft. Like, it's a— it's an email. If you see someone, the V- means vendor. Same thing needs to happen. Like, and this is like, all of us could go out and just help companies with this one thing. As you add agents to your system, you better put them in a separate domain and manage them as such. That domain then has different permissions, had different onboarding, has different exiting. Like, that whole— that, to your point though, William, like, that is an entire human resource-like behavior. Like, how do we manage those entities coming in and out of our, our business? That's a really good idea. We're like, these are million-dollar ideas, people. What are you saying, Kim? I can't hear you.

No, I agree.

Totally agree.

I mean, I think for me, the biggest thing with HR at the moment that I'm seeing anyway within Australia is that they know about AI. But they're not actually educating themselves about AI and they're not really understanding how it fits into their role or could fit into their role. And they're not seeing the, the advantages of actually upskilling their workforce with AI. And I think that to me is a big danger. You know, I think that is probably what's going to see a lot of people lose their jobs. It's through the lack of education personally.

My head.

Oh my gosh, I couldn't agree more. And then I have to be like Kim G versus Kimmy and Kim G. Kimmy, you were gonna say something too, I think. Kim, gasp.

Go.

Oh, I'm sorry, what, what did you—

I just thought you were gonna say something, so I didn't want to cut you off.

Oh, I— when you commented before, I was just saying that, is it going to be a human human that does that AI force onboarding, offboarding, right? Or will be an AI that actually manages the AI? It's going to be even in a year if we talk about this, it's going to be—

I agree.

Yeah, I agree. I agree.

I agree.

It's like a year from now.

It's a huge place right now where AI is going to upend it.

It's—

yeah, right.

Because we're already seeing in the past, so it'll either get bad faster.

Yes.

Or that's what we were talking about. Or it'll improve drastically.

So yeah, I mean, we're seeing HR leverage AI to do things like writing reviews and selecting candidates. And, you know, like, independently, each one of these tier points can go really bad and maybe okay. Like, I don't see it doing really well at either of these things because I was talking to a human resources, like, CHRO, right, the chief human resources officer of a company. And they were like, at the end of the day, like, I'm not really sure we want AI giving performance reviews to humans. And I reminded her of some research that was done recently in human-centered AI at Stanford around how we as humans take feedback. And that if we get negative feedback, not like super bad life-changing I'm getting fired, but more like, we— you could do this a little bit better. We actually do respond to machines more unemotionally, maybe more practically, like pragmatically.

We get—

if we get negative feedback from a machine, we're more likely to be like, okay, I see what you said, all right, I see that, okay, let me see what I could do. But we also, on the other side of that, we respond very well to positive feedback, but not from a machine. We don't actually see value in a positive feedback from a machine. We do though from our boss or our boss's boss, right? That praise, recognition, the hierarchy of needs. So it's really fascinating. Like, if you start really looking at this research and then architecting a new human resources organization that leverages AI to give this real-time feedback, which Amazon, Jeff Bezos was really big fan of, they ended up getting rid of it. But, but I liked it because I would get real-time feedback that says, hey, the decision you made today, the time you spent today took you away or brought you closer to your goal. And that I got from a machine, not from a human, because if it's a human, I'm like, why are you in my business? But if it's a machine, I'm like, yeah, go ahead.

And the ego comes into it as well, doesn't it?

Yeah.

Yeah.

Yeah. So you could— so it takes— and I think this is your point is like, it's going to take an architect to kind of go into a company and say, this is how you'll use these systems and when you will use them. And that's why I think AI solutions architecture ends up being like HR solutions. That's a whole bucket by themselves. Of how are you going to— and I always say, like, you're not— AI doesn't come and take from you, like, it's what you give it. But right now we're giving kind of haphazardly. We're like, hey, write these reviews for me, and we're not really thinking about this.

And yeah, go through the resume for me.

And yeah, yeah, yeah. And so anyway, so for those of us who choose to be intentional in this work, I think there's some real opportunity for us to do some big big things. But if not, at least you know. I mean, these conversations I think are important. I think you'd be surprised that even executives in big conversations aren't having this conversation. Like, they don't— they're not even willing. They're kind of like, this isn't happening. We're not doing this. So I think even just being willing to voice the question, being brave enough to ask questions like this, and maybe not to your executives. So don't do like what I did. I got fired from a very large company because I, you know, I always say I Jerry Maguire'd my way out of that company where I wrote the memo and sent it to my leadership and they escorted me out of the building. I was like, oh yeah, don't do that. Which I get, like they called me insubordinate. Totally I was. Like, I was like, yeah, I went and researched that word. I'm like, what does that even mean? I'm like, oh my God, that's totally who I am. I could not argue. Yeah, right? Exactly. There's like this This is who we are. Um, but they knew that's who I was. It's just they like it until they don't.

Yeah, yeah, yeah. As they say.

Yes, exactly, exactly. Like, it depends on which one, right? If I do one like completely non-important, uncommittal thing, it's fine. Noelle can mess that up all she wants and blow it up. And I call it fruit basket turnover, um, where I could just turn it over and everything gets messed But if it starts like infringing on certain people's ego as an area, or like their perceived likelihood of success, um, yeah, they're like, yeah, you can't play here anymore.

Yeah, I get into trouble for that quite often.

Yes, exactly. But now, like, that's why I do like the world of being an entrepreneur, is they actually do— when I come in as a trusted advisor, as a consultant, they actually like— they don't mind getting that information from me now. But as they're like person under them and multiple, usually multiple levels below them. It's not as appetizing from someone in that. So those of you who are earlier in your career, just recognize that that is the tendency. But eventually it all works out. But man, I've, I've been put in my place so many, many times. Like, and I always called it wing clipping, especially for women. Like, you get to this point and I'm like, you hired me to give you this information., and then you give it to them and they're like, we so appreciate you, but we're gonna like clip your wings and stick you in a little box.

Yeah.

And you're gonna keep doing what you're doing, Noelle, just don't do it to anybody and don't let anyone see you.

Absolutely.

It's very, very common. But I just think it's really cool, the space we're in, these questions that we're talking about. I think there's entire companies that will be built to solve this problem. I know I probably have said this this a few times, but like, I'm watching companies that are now 6 months old solve a problem that was not solvable 6, you know, 2 years ago because of large language models, because of reasoning models, because of research models. Like, being able to take a single problem and solve it deeply and then generate a 3-tiered web application and accompanying mobile app all without any developers, like, I think it's just now like who has the coolest problem they wanna solve. And if you're persistent enough to go after it, you can actually use AI to do the whole thing. And in that, in that sense, I think there's a lot of help we can offer these bigger companies. It's literally Blockbuster and Netflix time, except not new Netflix, old Netflix. I was talking to someone earlier, like yesterday, and they were like, you know, Netflix is now Blockbuster, right? Netflix is now attached attached to their models, attached to the way they do things, and they're watching their business get eaten out from under them. And I'm like, so like, yeah, you're— so it's funny how these things happen. I think the thing that's different now is that like in my dad's generation, like this would happen an entire— like you would go through your whole career and never see that cycle come back. And now we're like halfway through our career and we're watching like that cycle come full circle. That's pretty— I think it's gonna get quicker.

Yeah, it's gonna get quicker and quicker and quicker, isn't it? Those cycles.

Exactly, exactly. And so now we should— that's why I'm like, now is our chance though. Now that we know, if we do know, our responsibility is to say something, right? If we see something, say something. Have a conversation, talk. One thing I did, uh, at a consulting company is I just started a community of interest like this, actually, just inside the company. There's a lot of people that are like, I'm introverted and I don't want to like show my face on YouTube. I'm like, do a Zoom call inside your own company as part of an ERG. Just have the conversation, get people talking about it, because that ripple effect, right, will show up when they're in a meeting. They're going to get this idea and they're going to be like, oh no, I should probably say something. And they hopefully won't Jerry Maguire it. They'll just ask a simple question. Um, who was it? Columbo? I'm dating myself. Do you remember Columbo? He's like, deer in the headlights, like where he would be like, tell me more about that. Even though he knew what he was doing, he'd be like, I don't know what's going on. I'm so dumb. Just explain it to me. And I've used that deer in the headlights, like euphemism in my mind when I'm asking questions to just be like, just ask sincerely from a place of like, are we thinking about this? Like, it's not, not, I know what to do and I have the answer, but just who's having this conversation? Is anybody? Because if they're not, I would love to be there. Um, anyway, yeah, yeah, exactly. Uh, anyway, yeah, I just shared like, uh, TMI on my age and what I do with that reference. But some of y'all know. If you don't, it's worth looking up because he's, uh, yeah, it was like that was his thing. Like, he acted like he didn't know what was happening and everyone gave him more information, just like almost belittling him. And then he ended up— yeah, I like it too. I like Cumbalumbo too. All right. Any final questions, requests, answers, any requests for content you guys want to see? So as I mentioned before, you're going to start to see a lot more live learning labs, live hands-on demos of Microsoft stuff because they just gave me a new license. So I'm going to go crazy. And if you ever want to build— oh yeah, go ahead, Kim.

You talked about the MCP course that you're doing. Did I miss that? I came in a few minutes late. Oh, no.

It's gonna just be part of— so in August, we're calling it Back to Skool, S-K-O-O-L, and we're running 3 courses in August. And so you'll see that. You'll, you'll see more than you probably want, but we'll send an email like once a week with the schedule, and you get— you— they're part of the AI Leadership Institute, but you can also join one by one in the I Love AI community.

Yeah, I just signed up, by the way. For your link as a school starter of the school community. So what?

Oh my gosh.

You have to tell me so I can join.

How to get it, you know, because everybody's been asking. I'm like, yes. Okay. I'll put my membership back. I'll do it on school because school's cool and it's, you know, everything's here.

So, oh my gosh, Kim, if you want to, like, I, you know, I'm now like in year 1.5. So if you want to talk about like what I did to build my school, I'd be happy to share.

Absolutely.

Bought into other, like, another school that taught me how to build my school. So I'm sharing that with you too. And I still use it to this day.

When you have time, I would love that.

Yes.

Gosh, awesome. Okay, I'll email you because, uh, thank you.

Yay.

And then I want to be a part of it.

Okay.

Send me an invite.

I would love that too. Okay.

Yeah, I, I, uh, I don't know if I mentioned to y'all, but I have this, like, 3-step framework that I'm giving, that I use with my clients called ARC, A-R-C. And it starts for— the first A is awareness. Like, everyone in the company, every company has to know what this AI stuff is and how to use it safely. So that means the education, which used to be like this, like stepchild that, you know, it's the worst paid profession in the world. But now when it comes to AI, it's actually like a linchpin moment, right, where everybody needs to understand this in order to use it. So A is awareness, but R is readiness, where you take that awareness and turn it into very specific, like, job training, right? Like, if you're a project manager, if you are an engineer, if you are a procurement lead, if you're a back office administrator, if you're a front office admin, like everyone should know how to use AI for their job. And that is that whole HR piece, right? Like if I know what your role is, my job is to give you 1 to 3 to 5 agents to help you do your job. Um, but companies need that. So that's a whole nother business set. Like you could just go in and help people build out their little agents. Um, but then the C is competitive advantage, which is agentic. Like once you build out the awareness and then you build out readiness pillars. We call it, uh, Padmni called it the T. It's like you build wide and then deep, and then once you build deep, you now start orchestrating across lines of business to build a competitive advantage. And companies, this is like what we're going to end up doing at scale for the next 5 years at least. Well, and you know, when I say 5 years, that means like 18 months, but still, the world goes so fast. Um, but it's definitely now, like, these are things you could help people with right now, and it's not about the tech as much as it is about the business problem you know and can help solve. That T, like, how deep do you know that problem? And then if you know enough AI to help them solve it, the competitive, competitive advantage is very much an agentic thing. So, but that's why I'm teaching exactly what we're teaching, like, solution architecture leads to building an agent leads to connecting agents. And I think that's the future, at least that's—

is that the, is that the way that we'll do the core, the the school through that.

Yeah, through that sequence solution.

Yeah. Okay. Yeah.

And, and of course, I teach my philosophy is that you want to get attention and get like buy-in before you actually build anything where it's often the reverse engineer builds and then we push it on the leadership. We're like, you should buy this. It's awesome.

You're—

everyone should use it. So I believe in the opposite, especially with AI that because we can build so quickly in it and, you know, in an agile way, iteratively. So I, yeah, I start with solution architecture because we can design and the solution architecture starts with problem identification metric. You know, what metric are we going to move? And then we sit with the people that have that problem and help design the solution. And now you go and build your agent and then you go and connect those agents together. But yeah, oftentimes this order is reversed.

Yeah, I find I do both. Both. Like, yeah, there are things— tools I love to build. And I'm not— like, when I say tools, I don't build like you do, but, um, I will build something. It's like, this is— who could use this, right?

Yeah.

But in, in this space, I think it's super important to really understand what the problem is that I can work on, because I'm in the environment right now where I don't have to doubt that no matter what problem I find I can build a solution for it, or I can find someone to help me build a solution for it. And so now I am more concerned with trying to get that problem first and worry about the tool later. But I still love playing around and building, so I'll build things.

I'm the same.

Let me see where I can go use this.

Yeah, we're the same in that way, right? Like, I'm still a builder at heart, so I will build first. But when I'm talking to someone who's on the path for the first time, I'm like, like, don't get caught in that because we end up building stuff out of sheer enthusiasm that we haven't vetted against somebody who actually needs it. I always say never build for them without them. But you and I and many of the— we have lots of builders on this call where we're like, but, but, but, so cool and fun. Yeah, so one of the ways we are— we're actually— so to complement that, um, what you're saying, Kim, is that we are doing in September, September 9th, we're doing, um, at the MidwestCon. For those of you in the United States, in the middle of the country, in Ohio, we're doing, uh, what I'm doing inside companies, which is a vibathon. So the first day I spend with a company is a vibathon, which is basically vibe coding hackathon, um, where they come in and they learn how to build with their words, right? Agentic, or building an agent. So they build with their words. But here's the funny thing, so they a whole day, 8 hours, but now they'll spend like 4 or 5 of those hours designing and thinking through problem determination because it takes them so little time to actually build the thing, right?

Yeah.

Because they can just vibe code it in an hour, um, maybe 2, but the work they spend designing the solution and figuring out what problem they're gonna solve and how do they measure success. So in a day they have a viable, like I call it a minimum remarkable product. But it's interesting because in the olden hackathons, they would think a little bit and build a lot. Like, that was what a hackathon— that's why it was called a hackathon, because you thought a little bit about the problem and then you just hacked for 2 days. But now the burden is on us to think more clearly about what we want, articulate that into words a model can understand. So I think it's kind of cool. And anyone can lead a vibathon, you know, like, it's just— yeah, it's, it's fun. Uh, but it gets— it's high energy, people get excited, and then of course we end up with products that are done at the end. Uh, And we do it in clients. We ask our clients to nominate executives to own different idea buckets. So like the chief revenue officer would say, build me a lead generation tool. The chief risk officer would build, build me an audit AI system, right? So they sponsor these like use case buckets. And then if you build a system in that, they end up donating either a day of your time. So they buy you for a day to to finish building what you built, or they give you $10 grand, or they give you $50 grand. Just depends on the size of the company. But it's kind of cool because it gets everybody—

that sounds cool.

Exciting. Yeah, excited. Um, so once we— we are delivering one in September and then October, and we do this on clients all the time, but we're gonna build a Vibathon in a box so that if you all decide you want to deliver one, you could just borrow from us.

Awesome.

Yeah, well, we gotta do it first, so as soon as we do it though, we'll make it available to So you're going to record it?

You're going to record it?

No. Yes, I try to record everything. Yeah, yeah, it actually— I think it might even be livestreamed, as a matter of fact.

Brilliant.

I don't know how exciting it'll be to livestream a vibathon, but still, for somebody who's never been like me, it would be great to watch. Absolutely. Absolutely. All right. Awesome. Okay, well, I'm always— so we're right on time technically. So I always say we're going to do it for an hour and then I give myself 30 minutes to like bring it home. And so we're 5 minutes shy, but if you have any other questions— did anyone have questions? Let me just check the chat. No, I think we're good. Um, awesome. Yay! Yeah, I agree, it is exciting. Okay, cool. So if you have any questions or topics, you're welcome to send a note to our page. If you go to the school community, in the school community there's a link to fill out a form if you want to present an idea that you have. We're not selling anything, but if you want to present an idea if you do a project and you just want experience presenting back, like, and you don't want to do like a Zoom for everybody or webinar for everyone, you can just fill out that form or just DM me and we'll make space for you. And instead of me talking, you could talk today. It might be terrifying to some, but I think it's a necessary step that all of us need to get to, which is how do we just share with other people what we're thinking? And 100%, I think the biggest challenge with that is confidence. It's not, do you know what you're talking about? It's not, do you have the expertise?

Would it be valuable?

That is not the problem. It is, do you have the confidence to actually just say yes? So I'm inviting you to, you know, an opportunity to share what you know with 1,600 of your newest friends. Wait, I shouldn't have said that. But seriously, think about something you might want to teach and you could just use this as practice. This is how I got started. I started with my little YouTube channel with zero followers and I just posted videos every day of me in my basement. Working through web— IBM WebSphere and what was it, Red Hat JBoss. Like, um, so you go to my YouTube channel, if you scroll down far enough, you can see my earliest videos are me just demoing products. So if you want to demo a tool as just practice, because it's a skill I promise will not let you down over the years. So, um, but awesome, thanks for being here, thanks for coming. I know we're gonna do two this week, so Friday We'll be back. If you have any topics or wanna speak, just let me know. Otherwise, I will continue to share with you. I have 2 model deployments going out this week, so if they are successful, I will be sharing you with you the results on Friday.

So thank you very much.

Yes, you're welcome.

All right.

Thanks.

Have a good day.

I would say have a great weekend, but sadly it's over. So I hope you had a good weekend.

All right. Bye, Noelle.

Bye. Yes.

Bye, everybody.

Have a great one.