I LOVE AI With Noelle

It has been in the past, but it's not like it's your face on LinkedIn unless you actually speak and contribute. So don't worry about that. All right, we are live. Welcome everyone, welcome in. Happy Friday. We are here for our I Love AI community call. This is a free call we do every single week. Sometimes we move it around a little bit due to my schedule, but most of the time it's on Fridays. Fun Friday. I was gonna come up with another F word. Oh, that didn't sound right. I was gonna come up with another word for an alliterative way of describing it, but you get fabulous, fabulous friends, right? Absolutely. So it's great to see you all. Welcome in. The benefit of this call, of course, is to number one, get an update on what's happening in the I Love AI community as well as in the AI Leadership Institute these 2 months. Are some of our busiest months because I don't travel for speaking gigs. So I pour into the community, uh, instead, meaning I show up a little bit more often than normal. That happens 3 times a year. So as a speaker, I have these like waves of times where I'm on the road nonstop, but then waves of time where I'm home all the time. And so when I'm home, I do lots of content creation and lots of, uh, opportunities to be live together. So going into the holidays, One of the cool things we'll be doing is what's— what I did for the last 2 years, the 12 Days of Christmas. And I think I called it the 12 Days of an AI Christmas. So different tools, different products. I reach out to companies. I see what they're willing to, in the spirit of Christmas, give us as community members in order to participate. But I will tell you, they usually give me a finite set of resources, and the people who are prioritized are those who come to these calls. So If you're on the Zoom, you get first dibs, and then we distribute it as we can and as available to everyone else. So thank you for being here. I want to make sure that you know how excited and happy I am that you are here. If you want to join us on these Zoom calls, you can go to noelle.ai, my, my, my name, N-O-E-L-L-E dot AI, and you'll have an opportunity to see all the different communities that we offer. But most importantly, join us here for free every week in I Love AI. And it's not just a weekly call, right? We have a community. Many of the people that you'll see here in, in the list of participants are leaders in their own right across using AI across industries in multiple different ways as founders, as leaders, as team managers. And all of them contribute every day into our community chat, and they bring up such cool tools. I can't keep up with everything. So it's great to have a whole collection of leaders that are constantly contributing to all of our increased understanding in the world of AI. Today, I had an opportunity to go to— I'm in Naples, Florida today. I'm actually in at Great Wolf Lodge. If some of you know Great Wolf Lodge, if not, your maybe Instagram algorithm will tell you all about it now that you've heard this word. But Great Wolf Lodge is like a fun indoor water park for my kids, but Many of you know I've been on the road, and so the bank account of my children's, you know, love and compassion and interest, like, I've depleted that by not being around. So I'm here to be fully present after this call. So, um, so super excited, uh, to be here and have a chance to talk to you. But one of the reasons we're all here in Naples— yes, of course, Great Wolf Lodge. Oh, I should have put my wolf ears on. Anyway, um, but also because the Naples— there was a Chamber of Commerce meeting that I was asked to present in, and this is one of One of the areas in my business that I really love, like, helping small business owners that have successful businesses, meaning they've gone through the pain of figuring out, what do I do? Who do I do it for? And how do I get customers? They're, they're already at that point where they have customers. But they don't have enough, or they don't know how to deliver value to them consistently, or they don't know how to keep them over time. And so it's a really interesting opportunity for me to share how AI impacts their lives specifically. And of course, as a serial entrepreneur, multiple, multiple-time founder, I have failed and succeeded in this, in this area. And so I really like being able to share with them my failures, let them know they're not alone, let them know that there's many people go through the exact same problem, but to give them hope and show them specific examples of how they can use AI in their business to make their lives better, reduce friction, increase opportunity. Uh, and so that's what I got to do. It was called the Aboveboard Chamber of Commerce in Naples. It was really cool, really exciting. Um, I loved it. There was about 45 people there. I did give 25 books away. I also gave 2 people, which I've never done before, this specific shirt, I Love AI, um, the purple shirt. So the purple shirt is coveted. You don't get— you only get it if you go through all of my programs. So there's only a handful of people who have gone through everything, meaning all the classes. And by the way, I can tell if you've gone through the material. Now, I would encourage you not to just press play, walk away, and like, not— and like, not use it. Like, the whole point is not so that you get swag. It's— but I do want to give something special. So purple is my favorite color, as you can tell. I even have like— like, what? Like little purple kicks. Yeah. So, so it's a vibe. But for those of you who are in the AI Leadership program and our AI Leadership Essentials program for next year, I mean, of course, you're gonna get elite type of swag that no one else gets other than those who have gone through that program. But more importantly, you get a really incredible experience and an opportunity to develop yourself with a bunch of other people on the same journey. I wish I had this when I was learning this technology. I felt quite alone. Many of us have been on this journey. Alone for quite some time. So it's so cool when you realize that even though we think totally differently about certain things, even though we have very different skill sets, there's such a rich opportunity to learn from each other in this community. So very grateful for you all for being here. So I'm going to share with you today some of the things that I, that I taught them today, and it was a panel. So there were 3 people on the panel. There was a PhD candidate. So someone who's more on the research side. There was a, agency, so like an implementation practitioner, and then me, which I am one of one, uncategorizable, right? But me. But it was really cool because I could say my things, and both of the people that were on the panel, like, we were able to build off each other. And sometimes I get on in conversations and there's not a, like, a level of humility or coachability, right? Like, I'm always engaged with the person speaking next to me. Regardless, like, of whether how long they've been using AI, I just look at what they're doing. I hear the use cases. I'm like, oh my gosh, what can I learn from that? I'm always thinking, what can I learn from this? And not everyone's like that. Maybe you know this, but not everybody, like, is like that. Some people are very closed off. Some people are very introverted and just can't— don't want to share, um, how they do things. I find that there's a little tiny bit of— what do I want to call it— elitism in our field, where when people learn something, they hold it close, and they think that they're They're the only ones in that somehow that closed-off approach gives them some kind of differentiation. I have none of this, as you all know. Like, as soon as I learn something, I will share it with you. I'm going to try not to get distracted because I just learned something that I want to share with you. I'm going to try to stay on topic. I'll come back to that. And then one of you can remind me that I had something I want to share with you if I forget. But this gives me— oh, let me make sure. All of the robots are here. What? Natalie's in another hotel room. That's cool. What's up? Good to see you. Oh, good. Yes. No extra time. Keyshawn is cleaning house while listening. That's what I'm talking about. I do that too. Obviously not in the hotel.

I was just laughing at what you were saying. Coming to you from another hotel.

Yes, I'm so glad. That's so funny. There's probably multiple of us. That's right, Darren, you're getting a purple shirt. I would say you're getting one in your— that's not true. There's only a handful of people here that are going to go in. Yes.

Awesome.

Awesome.

Okay, cool.

So nice to see you. Yeah, no gatekeeping. Exactly. That's a word that I always forget, but is exactly what I'm talking about, that people get information and they put a gate around it and they might just do it with their face. Like they just look unapproachable. They don't share. When you ask them a question, they give you the shortest possible answer. And again, I don't judge that. Like, more power to you. You do you. But my life has completely changed because I share everything. So my mantra is that I nourish the world, and the world nourishes me. But it's not linear. It happens sporadically in exponential ways. I do not expect what I do to yield back something specific. It is an exponential equation. And that approach has served me so well. So for example, I went to this Chamber of Commerce. I did not go— I didn't say, hey, you got to pay me what, like, FICO paid me in order for me to speak. I was like, who's your audience? Oh, small business owners struggling right before Black Friday? I am going to be there because I am serving the world in a meaningful way. These people will now be able to take the little things I told them and transform their business. I'm super excited for them. But more importantly, I get to welcome them to our community. So you'll see them in our community. We already had a few join us. So, um, that's what it's all about. And then because I have this— this is my belief— because I have this energy of like, I give and I give and I give, I am also constantly receiving from all sorts of areas. And people— I mean, people who knew me like 10 years ago or 20 years ago are coming into my ecosystem and being like, oh my gosh, do you remember me? I'm like, yes, I remember you. What are you doing here? And they're like, I'm here because I want my company to buy tickets into your program, blah, blah, blah. I'm like, amazing. So I just encourage you to be a giver, to lead with value. These are the core tenets of our I Love AI community. We're not here to sell each other on stuff, certainly not swag, though I'm very passionate about swag. It's more about everything you learned. All of us should be learning new things every day.. And I'm gonna encourage you, unless you feel like you don't want to, but I'm gonna encourage you to share that with people. The best way to learn is to teach. AI Thanksgiving. What? That's a thing. We gotta do that. So I'll make that a part of my terminology for what's coming up. So let me give you a couple updates. Oh, yeah. And then I will get to the things that I taught the team as well as the cool new tool that I'm testing out. So things that are coming up. Black Friday, a week from today, we are gonna spend 4 hours building an AI system, an AI system end to end. We're gonna use 2 platforms, Lovable, which is my favorite, because I— it works for me. I've heard people say Lovable is not good, and I'm like, well, how'd you use it? So I love it. It's got love in the name. It's like made for me. So I'm a big fan. So we'll be using that. Um, and we'll also be using Chatbot Builder. Both, you will create your own accounts, you will build your own services, but in this hour I'm gonna teach you how to do it safely, responsibly, with guardrails, and most importantly, in a way that you can present it to someone and maybe they buy it. So that is my goal. Now, granted, the mission of Friday, there's two missions. One is to help you create almost like an AI clone of yourself, right? Build a system that can help you do what you do better. My goal is that you will get a 10-hour time savings by the end of custom building this machine. And that is actually not as hard as it sounds. Maybe some of you know it's not hard at all, but, but it does require a special skill set. It does require you to know what to say and how to say it. And that's what we're going to go through. And we also want, if you're going to build a virtual assistant, an AI assistant to help you with your everyday tasks, you also want to make sure that it's aligned with who you are and stays aligned. So that's one part of the focus. So thanks, Sherilyn, for throwing that in. So that is the link if you want to register. I tried— I, I think it's free. I tried to make it free. That's the whole point. However, we are also going to have an opportunity on the call to donate a certain amount of money, $35, to allow us to purchase Alexa devices to give to underrepresented communities. That's the vibe. Oh, is it a dollar? Okay, it's a dollar. Oh yeah, because I think on the store I wasn't allowed to not charge anything. So, so it's a dollar. So, you know, use your dollars wisely. You know, drink a third less, take a tall instead of a venti at Starbucks and join us. Hopefully it's not a deal breaker for you. If you are in the AI Leadership Institute, you will automatically get the link to this. Like, it'll be on our calendar. But if you're an I Love AI, it'll cost you a buck. But again, all proceeds, 100% of the proceeds will be going to buying devices for underrepresented communities. And Sherry, for example, she runs an entire, like, beautiful program that helps people over the age of— I'm gonna call it 75, but I'm sure she has a wide range. But it help— help them understand how AI can reignite their brain. And the story she tells touched my heart that I also encourage my dad to do some of the things that she talks about on our calls. She did a dedicated call if you want to check it out on our YouTube channel. But that— it's such an important and powerful place. I talked to the— I talked to, uh, these small business owners about this today. I was like, my dad is gonna live 20 to 30 years longer than his parents lived. Like, 20 years longer. It's a whole career that he's gonna live longer than his his parents lived in. So I think it's really useful to not write them off, right? Like, I— anyway, I won't get into it, but I've, I've been— I'm very close with my dad, and, uh, he's gone through a lot of things over the last 15 years, one of which was a car accident that caused a traumatic brain injury. And he was the pedestrian, so he got hit by a car as a pedestrian. No bueno. Um, but he got a traumatic brain injury, and This is why I was so excited about what Sherri was doing because she was reigniting their brain by asking them questions and then using those questions to prompt ChatGPT. And that when ChatGPT gave them an answer, their brain would fire in ways it hadn't fired in sometimes decades. Anyone remember that movie Patch Adams? That's kind of how I think about it, like waking up a version of themselves. I'll get emotional anyway. But you know what I'm saying. It's awesome. I'm doing it. So if you, oh my God, amazing. Yes, so good. It's so good, Tara. Oh man, amazing. Your mom's turning 92. Holy mama. But yeah, I think like AI is not just about productivity and revenue generation and time savings. It has a beautiful impact on the world that I get to see every day through my dad and through my son who has Down syndrome and through my kids. And so I want us to open up our ability to see the value of AI from as many lenses as possible. Natalie said, oh yeah, you used to volunteer at a senior center teaching them how to— yes, organic jewelry, beautiful. Oh my gosh, that's cool. What a cool idea. But there's not enough of it. I go into these centers and I just look at a lot of lonely people that no humans come and visit, that their, you know, their kids are like me, right? The kids of these people, their kids are busy in the middle of their career. They got a bunch of kids. We call it the sandwich generation. Right? You're sandwiched between your parents getting older and your kids also getting older. So you're like parenting on two levels. It's crazy, crazy scenario. Um, which means that if you put your, you know, if your parents happen to be in a home, your opportunity to get there isn't as much as you, you end up— that it isn't, is it? Is it? Isn't as much as you think. So I'm passionate about this. This is why I do this every year. I pick a cause. This is the cause I picked this year. I mean, it's a dollar. So every dollar you spend, you'll learn how to build a responsible AI system end to end. You'll take that system home. You'll get to use it every day to save yourself 10 hours. I think it's a beautiful opportunity. And you'll do it for a buck. If you're in AI Leadership Institute already, you know, no, no buck is necessary. But if you wanna do it for a buck, go ahead and feel free. But, but that is, of course, everything we do, our members of the AI Leadership Institute get complimentary access to all the things. So that is next Friday. I am doing a, another Maven course. It's what I every year, because I get more time, I open up 2 classes. We did Responsible AI that just completed yesterday, and then December 4th, which is a Thursday. I hope I have that right. I always get it wrong. But December 4th is the opportunity that we have, excuse me, to start the AI Solutions Architect, the last one of 2025. It is my most passionate course, it represents who I am at the core. Of course, I'm a responsible leader, but that— the Responsible Leader curriculum is actually what I created for executives, not necessarily for myself. And this, uh, AI Solution Architecture is more for if you want to do similar work than I do, if you want to be able to generate, you know, revenue as a salesperson or business development, if you want to be a developer relations person, like if you want to do anything in the realm of the kind of career opportunities that I've had in my life, this is why I built this class is to help you not take a decade to get my experience, but condense it into 5 days. And so that is happening December 4th. So as a result, I am doing 2 webinars to promote that event. So the first one, I think, is on Tuesday. The second one will be on Thursday, but it's just live on LinkedIn. There's no cost. It's just a free class for people who want to—

it's—

thank you very much, but so we're doing one is a LinkedIn Live, which is on Tuesday. And then I think this one's on Thursday, right? I can't tell. But this is a lightning talk on Maven, which we'll still promote on LinkedIn. But this is a Maven lightning talk to hit their audience that we'll be doing. All of these are the basics, and it's based on the book that some of you have read called The 21 Laws of AI Solution Architecture. This is also a free resource that I make available. It's awesome. Like, when I finished writing, it was one of those moments— I hope this happens to you if it hasn't happened yet. Where you get an idea and then you get in front of your computer and like in 20 minutes you're like, and it just like pours out of you. That's exactly what happened with The 21 Laws. Like, it just— I had to stop myself. I'm like, okay, I think 21 is a good number. I think I ended up with like 28 or 27, and I ended up doing a Google search on the top books, best-selling books that had laws in the name, and, uh, 21 was the most common number people use. So I was like, Well, let me just align with that goodness. So that's why I picked 21. But it is literally a pouring of everything I think has helped me be successful. And every bit of it I learned. They are all learned skills. None of it is— you know, people are always like, you're just so good at this, you've always been good at this. I'm like, no, check my TikTok, check my LinkedIn, check my YouTube channel. In 2008, not so good. It is a developed skill. So the sooner you start developing that skill, the sooner you'll get better at it. But I can tell you one thing for sure. If you don't start doing it, you'll never get better at it. And that's kinda like AI. If you never use it, if you don't, you know, get used to practicing talking to it, you'll never get good at it. And so that leads to an announcement that I got. OpenAI was nice enough to share with me. If you download Atlas, how many of you know Atlas? Atlas is the new browser. That OpenAI launched. It's not brand new. I mean, it's, oh, 2 weeks old, maybe, maybe a month old.

I don't know.

It's relatively new. Um, but Alice's new web browser— I mean, I download pretty much anything. Great.

Yes.

So Renee's familiar. So the— I downloaded it, and then it gives you a gift when you download it. If you sign into your account, it will give you this really cool picture, and the picture will include the days you've been on ChatGPT. And mine, my number, my magic number as of today is 1,723. What? I was like, what? I literally was like, wait, how much is that? It's like 4 years and blah, blah, blah. And so it was cool because I've been saying, I mean, of course, I was on the beta of Copilot during COVID I was on the beta of ChatGPT, which eventually became Copilot. And that's why that account existed. Like, I was constantly testing it, testing, testing, testing. But I would say that anecdotally, and I had no proof, right? I was just like, I was on during COVID and people who know me know I'm not going to lie about something. But you know how many people lie about stuff like this? Like, a lot. And so when I saw this, I almost cried because I was like, I have proof that it's true.

Yeah.

So yeah, so go grab Atlas and it will snapshot. I mean, granted, it's not fair for most of you because some of you used it and then got your account on another one, and we jump around on tools. It just so happened, um, that I didn't have an opportunity. Yeah, it's Mac only, but soon, Darren, it will be. Of course they will release it, um, to, uh, to the Microsoft OS platform. But yeah, you're right, it's Mac only right now. This is why I have a Surface, Microsoft Surface, over like not in my office. I have a Surface over here and I have a MacBook over here because I don't want to have that problem. I'm like, I want to download it right now. So I make sure I have at least one machine available. It's ridiculous. You should not do this. It's not, not, not really sustainable, but, but that is it. Only on what? Only on Apple Silicon. Wow, that's interesting. That stinks, Joe. I didn't know that nuance, but I do have an Apple Silicon chip too, obviously. Anyway, so I will wait. Eventually you will hopefully get it as they roll out new versions. The thing I like about it is, and I'm not fully— like, I did not do what would have told the world that I'm going to commit to the Atlas browser. I did not, when it asked me, will you make this your default browser, I did not say yes. So that shows a little hesitation. Right? So I did not say yes because the Arc browser, A-R-C, the Arc browser changed my life. So it's really, really hard for me to like, but I can see some opportunity because I can create the Arc experience custom to me in this new browser because it's ChatGPT with agent mode. I mean, there's, if I wanted to spend some time, I think there's some real opportunity there. But like I said, whether it's good, whether it works, I will always keep it installed because it gave me a gift of social proof that I've been on this platform for more than 4 years. So it was a gift.

I was like so happy.

Anyway, so we got that going on. So Atlas. The other thing I wanted to share with you was another tool that I've been playing around with. And it's called— it's IBM Watson X. Don't judge me. Watson X. But it's IBM Watson X orchestrate. And it's their no-code platform. And in my opinion, like, this is why we wanna do Viveathons and live learning labs, is that the more you can just open it up and test it— I mean, the Orchestrate gives you a 30-day trial. So we're gonna build a live learning lab on this because you can build a 30-day trial. And what I'm doing now— so this morning, I built 3 agents. But the benefit of it, of course, is it's no-code. They have a catalog of preexisting agents. And then you can custom build your agent. And when you custom build your agent, it's very much like N8N. This is the danger of poor N8N and Lovable, is that they put their user experience out into the world. And I can promise you, IBM, Microsoft, Google, and Amazon were like, can we just— we're gonna just assign 35 people to that to reproduce that in our product. That's what happens. It's kind of sad a little bit, but But that's okay. They've had a good run. If they— I don't— I actually think a lot of us like me, I like supporting small organizations. I mean, Claude started super small, Cohere ridiculously small, and now they represent a hugely impactful organization. And then Hugging Face, right? Hugging Face is like the platform for open source models. So I, I'm not saying that like IBM's gonna build Orchestrate and it's gonna replace Lovable or N8N. But I do recognize, and I want— I share this with you more for if you are building something, I would build it for a very specific audience and only tell that audience that it exists. Because if you go big with your go-to-market, people like Amazon will be like, hey, and I've been in these meetings, can you come in and tell us what you're doing? We're so interested. And when you hear as a startup founder that Amazon's interested, what you hear is that they want to partner with you. They want to maybe acquire you. But that's not what interested means. Interested means come in and tell us what you're doing, and we'll, we'll see what happens. And I've watched multiple occasions across multiple big, huge companies, a bit of cannibalization of ideas happen in that moment. And so I'm just telling you, I don't want that to happen. I will support— I love Lovable because I like saying that, um, but I'll support them.. I will continue to pay them. I will continue to be a subscriber until they no longer have an option to do that, because I love the product and I love what it gave me the ability to do in the earliest days of vibe coding, right? Yes, I am lovable. Oh my gosh, that's a whole campaign. I should talk to them. We should do like an I am lovable campaign. What?

I love it.

Oh my gosh, Darren, that's brilliant. I love it so much. My vibe for sure. So, so that being said, so Orchestrate is a fun platform, 30-day trial for those of you who are gonna do some live learning with us. You can grab the 30-day trial on a Gmail account and then do it again when we do our live learning. If you can't wait, otherwise you can wait. But, but yeah, I, the thing I loved about it is that something that took me, you're gonna laugh, something that took me an hour and a half on N8N took me 10 minutes. On Watson, um, on Orchestrate. And that's because they learned from those systems and they pre-crafted agents that do more than one thing. So one of the agents is an email and calendar-like agent. Its job is to basically manage your email and manage your calendar. Um, where at NN, I have to drop boxes for all those things. I have to drop my email box and connect it. And if I have more than one email, which I do, I have to drop more than one box. And then I have to drop an LLM box to do some processing, and then I have to drop the calendar box, more than one. So it's like, again, I feel silly even saying it because I'm, I'm talking about like it takes me less than an hour to integrate systems I could not integrate before. So I shouldn't complain. I think it's great. But now I can do it in minutes on a platform like Orchestrate. So pretty exciting. Um, so I'm playing around with that still. Uh, and that's kind of my I think it's interesting because I don't know if anyone heard of Watson Orchestrate. Yeah, Watson, IBM Watson, it's free. Oh, you mean at scale? I have no idea. Um, and yeah, there it is. Yeah, David Mitchell, thank you for that. Um, sorry, David, every time I call your name, like I say your whole name. I hope you don't think I'm like your mom yelling at you. Um, David Mitchell. Um, yeah, it just rolls right off the tongue. It sounds like a, like a hair product, right? Like Paul Mitchell. Anyway, it's got that vibe. Go ahead, Natalie.

Yes.

Hi, how are you?

Good evening, everybody. Well, good afternoon. I just wanted to say I've been dealing— I've been working a lot with NAN too. I just started my LinkedIn connection and I have like 2,000 impressions now.

I'm like, it's working.

But I wanted to kind of like maybe like future predict. I think that NAN would be like once you connect, like maybe even Google products, you— I think NAN can be like the divider so that like we can avoid scams. And like, I think for me—

tell me more about that. Tell me more about what you're thinking there.

Because the thing is that me as an operation accounting, I'm always looking for ways of like, um, avoiding double dipping even in the industries. Like for businesses owners to go to vacation and know that nobody's going to steal from them. That's what I do. I implement these systems, right? So I'm trying to reverse engineer like the concept of agents because in my head I already created them. Yeah, my industry, right? So what I'm thinking is NAN could be like a, a portal that we use, like a middleman, to give authorization and approve certain things so that these agents cannot create other agents, or, you know, it can go out of whack.

Idea.

And I think NAN is a great thing for that. But to, like you said, to your point, it's so time-consuming. I've been 3 days with this thing, and, and I've been— I, I love one of— his name is David, I believe, um, and he's been helping me. Oh my God, I love him.

A lot of freaking work.

Yes, I'm gonna try Google, and then I'm gonna try Watson, and I'm gonna do like a blog comparing them.

Yes. Come on.

This is a lot of, you know, like trial and error, trial and error. But I guess my goal, my point was that, well, as you were speaking, I'm thinking I'm going to use NAN when I do build these agents that are for specifically for bigger companies, like not corporate, but like small businesses that make like $12 million and up to $20 million. Like those are the systems that I'm going to build, but I'm going to separate them using NAN. And like get 'em together as an approval so that there can be like a protection of some sort, if that makes sense.

Yeah, yeah. And in that scenario, right, you're kind of building N8N as like the planner, right? The third-party connector as opposed to, you know, like integrating them together, you know, in a more, like a more intense way. So I agree with you. I think that's like an architecture, from an architecture perspective, I think that's, yeah, that's the right, yes, exactly. Solution architect in action. But yeah, that's what I think. Is the right way to think about the architecture because you don't wanna necessarily reinvent connecting systems together in a super brittle way. We wanna keep them modular and the best way, like N8N keeps them completely modular where they're just connected by API call and that all of the orchestration logic is actually held in, in N8N itself. So I do have a video, you can search N8N, there's quite a few of us that have shared content on N8N inside the community. I Love AI, as well as in the AI Leadership Institute. So if you want to learn a little bit more, new, or you're new to it, um, something to think about. But it is interest— you know, I love that Natalie said, um, she was like, uh, it takes, you know, it's taking 3 hours. Like, what used to take us like years to build, we can do in like 3 hours. So it is annoying and a little bit, um, you know, challenging, but it's a fraction of the time, uh, compared to what it used to do. So I think it is all relative. Oh my gosh, I didn't realize I have my, like, again, my Grateful Vlog wristband on. That's too funny. Anyway, a little promotion. All right, Renee, I don't know what you were talking about with the Microsoft thing. If you want to share what you were sharing or thinking there, maybe I said something and you were commenting.

Yeah. No, not—

no, she was talking about in advance. I'm just getting my laptop.

I was walking my dog. She was talking about the safety of the agents. Well, that's—

if you build your agents inside of Microsoft Copilot, they have a whole system. I was watching the video and they have a whole red team thing all inside.

Yes.

Well, for an enterprise that's larger, you don't need an ADA, and you would build them right into Microsoft Copilot, right? Yes. And use their built-in protection red team, right? Yeah, 100%. Yes, yes, yes. And so the only challenge, of course, is if you're not a Microsoft shop, or you are a chief risk officer and you're like, I don't want to be all in on Microsoft. I want to diversify our cloud, which I don't think is necessary, but that's the risk, right? Yeah, it's where like a risk person would come from is Even if I don't need to, I feel better. I sleep better at night knowing these systems are decoupled. So, so realize that these, these are not like functionally required. This is an architecture decision, and there are benefits and disadvantages to both. If you're all in on Microsoft, the benefit of that is those systems, like you said, Renee, they inherently talk to each other, so you don't have to do as much configuration. So it's much, much quicker because they already know all the components. Microsoft's ecosystem is very well connected. But the risk of that is that if Microsoft, if there's any challenges with the Microsoft ecosystem, all your stuff is in jeopardy. So a lot of people, similar to you, Nasli, as an executive or someone who has a risk lens, they're like, I appreciate Microsoft, but let's just create a little bit of decoupling from having all our eggs in a single basket.

Yeah.

Yeah.

That's my—

Makes sense. Thank you.

But I like, if your customer's all in on Microsoft, I don't try to convince them to become hybrid cloud. Like, that's, bring it. That itself is more risky. Like, if there are— but if they are saying like, hey, I'm not really sure, then I invite them to kind of think about these different architecture decisions that they need to make.

Um, okay, at the end of the day is like the owner's, you know, the owner's decision. But I always put my— like, I always give that—

like, yeah, you're advised. Yeah, you're the trusted advisor.

And another thing, as an architect, we need to start putting the hat on Chief Risk Officer. Like, that's kind of our sub you know, like our sub hats, we always have to think about like, you know, what are, you know, what the risk factors are and like also put that in our— is that part of our also our—

yes, I'm actually going to give a sneak peek to it right now. So one of the things that I, as a— now granted, this is more in the Business Accelerator, but we talk about building this in Solution Architect. But in the Business Accelerator, that program is all about if you own a small business and you want to be able to create, like, get more customers, grow your business, scale your business from $1 million to $10 million, from $1 to $10,000, whatever you're trying to do, there are specific— like, there's a way to look at AI that's just very different as a business owner. As a matter of fact, it's so different in practice that we've actually separate— like, we have people that have come into the AI Leadership Essentials program and they bought into either the business side or the career pro side, because the perspective on AI is actually quite different if you're trying to use AI to grow your business versus learn AI to be a good employee for someone. And both are, of course, extremely valid choices. It's up to you. But the, the technology adoption is different enough that we've actually separated those two paths and cohorts, because it'll be great if you're in a room full of people that are also building their business, um, versus You know, again, it's nice to talk to someone if you're a business owner and you talk to someone who's on a career path, it's not terrible, but it's a little harder to leverage each other's, you know, lessons and learning and success. So we've separated those two things out. But in the business accelerator, one of the things that we focus on is building your— I mean, I was on with— it was the CEO of 1-800-Flowers. I was just on his podcast. And he said he creates a kitchen cabinet. And I was like, what? And he's like, yeah, you know, kitchen cabinet where you go and grab people that have different skill sets and you kind of have them on speed dial. So if you ever need help, you could call them. And I never heard that term. I thought it was pretty cute, you know, like, because it's not like a real, you know, cabinet, like a, you know, a legislative cabinet, but, but, but like more of a I pick whoever I want and I identify mentors and I get them on speed dial. Now, I have never really been good at this. I hate rejection.

I would—

I hate conflict. I don't really— I don't— I love getting coached. I love someone to tell me something I don't know, but I don't like conflict. Like, I don't like, you know, I don't want to ask someone to do something and then they're like, I don't want to. And then I'm like, I'm sorry I asked. Like, I just don't— that whole vibe. So what I did instead is I created my own mentors. I created an advisory board, an AI advisory board, and I did this 3 years ago. And in this AI advisory board, just think of like who you would want in your corner. You know, you might want, as, um, Natalie just said, a chief risk officer, a chief financial officer, right? A CFO, a chief information officer. A CTO, which is more about IT ops and stuff. You might want a CRO, which is not risk but revenue, a chief revenue officer in charge of revenue and growth. And what you can do is you can build a collection of custom GPTs. You can build them even as agents. What I like to do is I will build a role, chief revenue officer, and I will go find the publicly available published content of the best growth mindsets in the world. And I will feed this model that information so that now I'm not just getting the benefit of one kitchen cabinet member who had a great life experience, but maybe it wasn't mine, or maybe it won't be mine. Now I, I have the benefit of getting, you know, Jim Rohn and, you know, Zig Ziglar and, um, who's that guy who wrote Good to Great? Jim Collins. Um, so like I can go and curate what does chief revenue look like to me? What is success in revenue generation look like? Let me go find those people and I can create my own mentor. And now I can talk to that mentor and then do that times 12 different roles. So you have the ability, you no longer have the excuse of like, I don't want to like find a mentor, I don't want to be involved in that kind of, I don't like meeting with people, I don't like doing informationals, I don't want to do a coffee chat, right? Just build your own mentor. It does require you to have the discipline to go find the right information to train that mentor model.. But I think this is key, especially as you get into the habit like me, you know, 1,700 days in, as I get into the habit of using AI every single day, multiple times a day, every hour of every day, that I'm not just blindly asking a random model a random question. I'm going into a purpose-built model on a part of my company I need help with at that time, and it's custom trained on the best resources in the world. Like, that's fire to me. Like, let's go. Don, I see your hand up.

Oh, okay.

No, no, I'm here.

Okay. I don't typically just raise my hand.

So yeah.

So I'm curious that— yeah, thanks, Robert. So Noelle, it's funny that you brought up this N8N thing, right? Because I haven't been sharing it, but I've been fighting. So I'm playing like two sides, right? So the business owner and obviously like the, you know, the, the tech AI guy. So I'm trying to scale up my photography video production business. So I wanted to do like a social media agent basically. And actually, Natalie and I were chatting about it. She was kind enough to spare a couple of minutes. But, um, so I've been running into trouble for ages just trying to do a really simple thing. And I'm not gonna break it down now for everybody to waste their time, but it made me think of the broader picture in terms of as we start to build agents and whatnot. What I'm finding is—

I'm here, by the way. My video is frozen in a horrible face, but I'm here. Continue.

It's funny because you froze in this pose, so I thought you were just attentively listening. I didn't even know you're frozen. But I'm pretty frustrated because I've been working on the same thing for like 6 weeks. What I think is something that I could see us encountering in the field at some point, especially if we're working with the smaller business owners. Maybe we have to do an on-prem N8N, like something local. You know, even in trying to kind of like take my JSON nodes and drop them in one model like ChatGPT and then drop it into Perplexity and then drop it into— I still wasn't coming up with solutions. And I'm like, I'm— I think, and I don't know if anybody else feels like this, but I, I'm gonna be transparent and say I, I know that part of the reason I haven't moved forward on some things is my concern is I start to deploy something for a client and then I'm at this juncture? And I'm like, I can't call a plumber because this ain't plumbing.

Yeah, you know what I mean? Yeah, so yeah, for sure. And so this is where, like, working backwards, you start with the right problem. Because this happens in every company that I've ever delivered anything. They always want to increase the scope of the thing that we're doing. They want to do something that I can't tie to a metric of success and that I can't ultimately get a model to do. Now remember, AI— this is super important— AI is research. You are testing hypotheses. These are not— you don't know if it's going to work, and it might not work, and then you let it go and you do something else. It is very hard. This is what researchers do all day long. They test hypothesis, they find out it's not working, they change their hypothesis. It's very hard for people like us who are not researchers by trade because we're like, but that's my thing. I built that thing. I don't want to let that go. I just spent 6 weeks on that. Right? But— and I'm not telling you to let this go. I'm just saying that the iterative process of finding the right problem to solve with the right model, if you find your— and this I call— I cut bait, as they say in the fishing community. I cut bait very quickly. And I have an assessment, which I covered in our leadership class. I have an assessment that I use that I check every day to be like, is this where I expect it to be right now? And if it isn't, I evaluate, is this worth continuing? Is there enough open questions in the hypothesis that I have not tested that I'm willing to continue working? Or has there been enough evidence for me to realize it's just not worth the effort? Because— and again, this is challenging because we fall in love with the problem, and then we fall in love with our solution to that problem, even if it's not working. And then resilience kicks in, and we dig in our heels. But with AI, we can still solve the problem.

If—

I mean, crazy fact, you might just switch models, and you'd get a totally different answer. Or you might switch platforms and find a connection, a connector that, let's say, who was it? The Clay, like C-L-A-Y. Clay is a platform for go-to-market engineers. And like, that Clay has a connector that's not even possible, and you were doing all this work to like force something that actually is available somewhere else. So it's hard because you have to constantly be thinking and learning. And that's why those Google alerts that many of us have implemented are so valuable, because we get alerted when new stuff becomes available. But I think Part of the challenge is that I, I personally think that we need to really remember and embrace that we are researchers at heart. Like, that's the first thing. We're researchers first, and then we can use that to productize. I think Joe might have some suggestions. That's just, again, like I always say, like, that's just Noelle Russell's experience and, and me talking. But Joe builds every single day. So I don't know if you're gonna comment on what Don's struggling with, but You're welcome to, or—

Yeah, yeah.

So I've actually been vibing with Copilot for most of the day today because I'm building a development system to build a custom fine-tuned model on Windows, on WSL. So lots of tech going on behind the scenes on the tech stack. So my suggestion to you, Don, is if you're in the middle of something and something breaks, and you don't know why, ask Copilot. Tell, tell, bring Copilot up to speed or bring one of your, your favorite LLMs up to speed. Say, here's what I've done so far. This is what I'm seeing right now and it's broke. Can you help me fix it? And honestly, it will give you some suggestions on things to try. You can, you can, if you get an error message, then you can copy and paste that in. This is what I got when I tried that, but bring it up to speed. In other words, prime it so that it knows where you are, and then it can actually help you vibe the next steps so you can kind of get your way, work your way out of the problem. It's like calling the plumber.

Yeah, I think that's actually—

yeah, that's super great. Sorry, I didn't want to interrupt. That's super great. But this gets so deep that So, so on two levels. One, it should be very simple, right? It's just literally generating Instagram posts using an agent. But, um, but I did that actually. I, I even went so far as to tell, uh, Claude, I said, you're really not doing a good job at this. Talk to ChatGPT and tell ChatGPT what the problem is. And so then, um, and, and literally like I got, I literally got the agent to say things like, so, and I did that and ChatGPT came back with something. I gave it to Claude and Claude's like, oh wow, that's a really great idea. So then Claude tries to do this and then literally there were steps where, and I kid you not, I had done a couple of things and I said, no, you've already told me to do this. I'm not going to do this anymore. And literally Claude said, my bad. I'm not kidding.

It's pretty bad.

I've had him say my bad to me.

Oh, you too, right? So I tried 3 different models and I mean, I think in my case, it's probably unique because it's, it's N8N and probably most likely neither one of these is trained on N8N and I hope that's the problem, but I was kind of thinking like, man, it would be—

I also think you might be able to break the problem down.

I was going to suggest there too, a great way to do that is to go out to the website, to the N8N website, get all the technical documentation and collect it. And then pipe that into the whatever LLM session you have. So it has— is the most up-to-date documentation. So it can actually pull from that documentation. A lot of times what it'll do is based on its old history from 2024. And of course, all technology marches on, right? So I had to tell it to go out, like with this stuff, to say, based on the Azure features that were announced this week at Microsoft, you know, like where Noelle Russell Russell was this week. Tell me the right Azure commands to, you know, like to use in my use case. So it actually, a lot of times you have to refresh its memory specifically on new product designs and make sure that it's giving you the right up-to-date information.

Yeah. And I think— I also think it's important to kind of look at the problem you're solving and make sure that it's broken down at the right level of composable parts. So for example, if you're building a model that's going to build Instagram posts and I presume you're also asking it to post them, right? Like, is what— when you break that down into composable pieces, which is again very hard. Like my clients struggle with this because they're like, no, I just want to build one agent that does this big thing. And I'm like, well, actually that's going to be 5 agents, right? And so looking at how do you create efficiency at more micro levels, right? So building an agent, for example, that builds the post, does it do that well? Then builds the imagery, does it do that well? Or creates the video. But that's a separate agent, right? And that you're using an A-then to connect those pieces together. And be the planner. But if you can do that, I mean, this is Noelle, software engineer, talking, right? When you break these up into smaller pieces of code that are autonomous or at least decoupled, you can test those pieces and you're like, that part's good. So now I can move on to the part of that prompt. You don't have to retest the whole prompt, which in LLMs, it degrades the entire, like, success you've gotten to. You get to build small pieces of success, right? And then that way you can narrowly focus. We called it breakpoints back in the day when you could set a breakpoint right on that part of the process and go, oh, the problem's here. Why is— oh, this isn't actually about posting at all. It's got this. And then you can ask that question, right? Like, ChatGPT, what— why is this part failing? And so I do think that there's some value, especially because we're learning here in decomposing these agents to their smallest— remember, minimum remarkable product, their smallest components. So you get— can get full testable units that you can then assemble. Hopefully that's helpful. Well, I can help. I'm—

yeah, I was going to meet with him after, uh, this evening, so I'll help him. But I just wanted to give a synopsis of like maybe an option. Uh, Canva has an option to post to your social media, so you can connect your NAN to Canva— to NAN and then trigger it to post because the thing is that it's kind of tricky when it's Instagram and there's a lot of things that are behind it. But I was just looking at it today and I actually messaged him, so I will help him.

Yeah, good. That's good. But also, I mean, I also know that like Don is like doing this because he's trying to learn how to build these systems. And so he's not going to want to use like a SaaS. I don't know. I don't want to speak for you, Don. Maybe you do. But I personally would want to be like, well, I'm trying to teach a machine how to do this work. I, I could go to Canva, but then I could also go to like a CRM. But if you're trying, I think it's, it's very useful and educational to actually go through the process of figuring out why an LLM won't do what you're telling it to do. And many times it'll end up being bias in the model itself or in the way that you phrase the thing that you did. And so sometimes what I'll do, and this is a fun story in case you don't know it. In the early days of ChatGPT, when 3.5 was released, um, a researcher, uh, journalist started talking to actually Bing Chat. If you remember in the early days, Bing Chat came out and became part of the website. Super premature, what a disaster. But they started, uh, I loved it.

I love, I love Bing. I really love Bing because it was just like you have a thought, you can do it, boom, bam, bam.

Boom. But the challenge was is that this journalist started communicating to this machine. And it had a 35-minute conversation. And as it approached minute 20, 25, 30, it started to really shift in how it was communicating to the journalist. It became— I'll call it relational. And ultimately, which is what shut the conversation down, at minute 35, And this is all documented. You can go Google it. It's a very popular story. But I say it to you because at the end of minute 35, the model basically was like, you should leave your wife and marry me. The model, like the model. And so the interesting thing about that is that both Microsoft, who of course is liable— it's Bing Chat. But Bing Chat was leveraging ChatGPT, or I should say a GPT model from OpenAI. And both of them made the decision. And also research supports that when you have a single conversation last a certain amount of time, like the longer it lasts, the more weird the behavior gets. And so that's something to think about as you're kind of banging on a problem, that it might be as simple as— I think, Joe, you said this— like just refreshing. Like you called it refreshing the memory. But similarly, start a new chat. Start over. Not over, obviously, you've talked to the model that long, but start a new fresh chat because the model's behavior just gets weird over time. And this is evidenced by the fact that when you are on OpenAI, Claude, ChatGPT, of course, Microsoft Copilot, if your conversation goes too long, they actually measure it by tokens. If it gets too many tokens in memory, they will pop up a little— have you ever seen this where it's like, your conversation's going a little too far, you should probably start a new chat? And that's because the performance, the integrity of the answers begins to degrade dramatically after that time.

Context window.

So there's a reason they ask you to do that. It's not to save time. It's not to save space, not because the model gets confused. It's because the model degrades in performance the longer a conversation stays open.

Context window.

Um, I'm just gonna circle back because this is all really great feedback, but Noelle, there's one thing you said that actually Renee just, just dinged. So there are times— because I appreciate all this, guys, but I spent 6 weeks like for probably 12 hours a day, so I've done all of this stuff. But as it turns out, I think the one key thing, um, is— well, and you kind of touched at this where you're like, you know, sometimes you need to just go left And I've just been like, you know, obstinate about trying third-party tools. And Renee is like, use Bloatato. And I've been avoiding using Bloatato for a while because I just wanted to use the, like, you know, yes, I'm strong and no tools kind of masculine move. And it may just be that Bloatato is the way to go.

No, you're right. That, and that's, that's the mindset is that I, I mean, I do it all the time is I get stuck in, and I almost dig my heels in like, I'm gonna make this work. And there's zero reason to do that.

Okay.

Yeah, right. Be attached to the outcome, be attached to the result. Um, but I'm the same way, like, I dig my heels in, I'm like, this is gonna work. And so I've got all these workarounds, but that's to accommodate my mindset that I don't want to let it go. I want it, I want it. And I do figure it out, but I've wasted so much energy in doing that and getting it to work that I could have just like you said, turn left and been like, oh, it's right there. So it's okay either way. Like, I value the time I spend, you know, like, I don't want to do that as a habit, but I don't mind going down a rabbit hole and getting stuck somewhere and then finally figuring it out, only to realize that I went, you know, 3 miles in the wrong direction and have to turn around and go back. I think it's all good. Like, we're not We're not— and this is, I think, to your point, Don, on like your concern is what happens when I'm on site with a customer and this happens? But we're not right now, right? So I— that's why I say build as much as you can in a low-stakes environment like this. Like, Google companies and just build for them, and they don't have to know you're doing it at all. Just build for what you think they might be struggling with. Ask ChatGPT, I'm looking at this company, what do you think their biggest problems are? Just ask. It doesn't even matter what it says. Build solutions for that. Because the more of that repetition you have, the more you can catch yourself in these habits that you have, which is— I'm very self-aware now, but I don't stop myself sometimes. I'm like, you know what, I'm just— I want to, I think it's fun. Um, but I recognize it. I recognize it's not the best use of my time.

And it—

and again, the benefit of that is that when you are on a client site, you have that mental flexibility. You don't get stuck in that rut because you can recognize it. Okay, Let me just try something else, or let me surface this in a different way. So yeah, thank you for that. Oh yeah, I like Metricool. I'm a big fan of Metricool.

Go ahead, Robert. Hi, good to see you.

Yeah. How are you guys doing? It's already 5:05. I have a little story from, from the judging panel of the Customer Experience International Awards of companies over 5,000 employees who implemented AI projects last year. And I think a lot of those were good implementations. And I always ask one question, right? Because I would say 80% of them, their change management story was, yeah, it's good for people, it complements people. And then we dug into how much they spend and so on. And I was asking, do you really think that you can consistently deliver on that story what you're telling? And we on all the charges started digging into that. And you could actually see that I would say 70% of the stories, they admitted that the stories will get cracks over time because while they say they humanize AI, they bring it all together, they spend more and more money and they will have to cut people. They will have to cut costs. And one said, yeah, it's just call center costs. Which are outsourced, but they're also people, they're just outsourced. So I think that there is a bit of a red flag which came up for me that a lot of the stories for initial AI implementations, you need to be careful that you have a bridge once this becomes very successful, that you don't actually start telling a lie to your employees because they will notice, they will recognize it and will tell you, you baited us into this and now we are stuck with it, right? And you spend millions and millions of dollars, right? So this was a very interesting light bulb I saw. And I just wanted to share that with the group and ask, have you seen also those phenomena happening in your implementation? Or is this maybe more for large organizations where they're more story-driven, right?

Well, I'll ground that a little bit in the research that just that came out, right? The research from, um, that was stated in Forbes but came originally from McKinsey. And it's— they did this study on, you know, AI implementations and pilot programs. And the reason that, like, the number one stated reason that the people surveyed said that AI was failing was a failure to be adopted by their employees for exactly this reason. A, a, a trust challenge. Not a technology challenge, not a did we pick the right model, did we get the right outcome, did we generate this much revenue or save this much time. It's that there is a distrust between an organization that says, hey, I'm going to amplify you and amplify your human ingenuity, knowing very well that in 6 months, if that amplification means you can get rid of my role, you will do that. And so Marc Benioff, you know, head of Salesforce, He's very transparent.

He's—

he will tell his people, number one, if you do— if you have a job that I can replace with AI, you will be replaced. That is his mantra. He tells his— I can't even believe it sometimes what he tells his employees. But the other thing he also says is we're not gonna— we're not gonna recreate the problem by hiring humans without the lens of can AI do this instead? And I think that's a level of responsibility. I mean, whatever you think about Mark, I have my own opinions, but he's transparent at least, right? He's not telling them a lie, right? He's saying, my goal is to replace you. That's my hope, is that I don't have to pay you. But if you can find a reason that your human ingenuity is required in this company, then you have a job here.

And that's not—

I don't know, there's— I just say that so that you can go and look him up and see some of the things that he writes. But he's very transparent in his messaging, and I think there's something to be said about that. I think he could be, I don't know, maybe nicer, but some people aren't nice. But I would love to go back to the question. Go ahead.

Yeah, I think you're absolutely right that that is how it takes off. A lot of those companies actually have taken off. Now they're at the point where the story doesn't work anymore. So I think there's probably two points in time to get it started, right? And the one is when you really have success that you that you chose a story which you can bridge to the reality which comes next.

Yeah, absolutely. And you asked the question, so I don't want that to, like, you know, disappear around, like, anyone, if anyone's, like, building this, especially in a different scale, like, these are enterprise documented challenges, but I definitely know that it's happening. And so if anyone has experience or has, you know, has some ideas around how this is showing up, like, You know, this whole AI is gonna help you, not hurt you, that you're not gonna lose your job to AI, like that, those types of narratives. Anyone have thoughts on like, you know, the potential damage, or do you think it's fine? What do you all think?

I was just having this conversation. It's crazy because everything that we speak about, I've already like talked about, it's crazy. But the, I think that Having finishing my associate's have made me realize that everybody has to go back to school because AI is such a complicated— there's so many things to learn from AI that I don't think a lot of us are going to be out of a job. I just think that we need to retrain our brains. And it's just an example. Like, I fell in love with my robotics class. Like, literally, like, I plan to take my master's in robotics because, like, the way that I saw that robot is the same way I look at my car. I have a stick shift car. I drive a 2000 Nissan Maxima, metal. Like, my car, I feel like it's like a Transformer. Like, when I get in it, I feel like I'm transformed, right? And when I took my robotics class, I just saw myself and I envisioned myself. I'm like, okay, if AI already built this car and now it's going to drive itself, like, imagine they're going to— we're still building other products that are still not even invented. Like, and I think that it's not that you're going to be replaced. I think that AI is going to push us to a whole different level. Of knowledge. And I think that everybody needs to press a reset button, go back to school, learn the basics of AI. And I'm an advocate, you know, and the first person I went to to ask was Noelle Russell Russell. I know I was like, MDC, and here I am 2 years later, I'm finished. And this is the outcome of her just telling me, "Nasli, just go there." And I did it. And I have learned so much. And I'm so grateful. And that's why I'm here to give back, because she's the one that— she's the reason why I'm even here. So if you think that you're going to be replaced, you know, analyze your— analyze what you've learned in the life that you've lived and say, how can I— what do I need in my toolkit of education to get ahead and learn you know, either robotics, either machine learning, either whatever, because these are things that are so complex that just they're like Miami-Dade is going to start a bachelor's in just robotics because just a battery of a, of a, you know, just the battery, just like your car is going to be manufactured. So you need to be ahead of the game and building those, those, those batteries. I'm just giving an idea like the tires, you know, like I'm just looking at my car and I'm just like, oh my God. Like, I'm already in the engineer mentality, so for me, it's, um, I love it. Like, I love, like, even I'm just gonna get, like I told you, I was gonna get a robot. So it's just like that. I, I'm not scared. I'm excited that it's coming. And I tell people, it is your time to elevate your, your knowledge of other things that are going to be coming in the future. And that's exciting for me. I don't know for anybody else. And that's why I went back to school, because I'm like, I need to be in the forefront of this and I need to be an advocate as well. So that's just my point of view.

Yeah. And I mean, we— I, of course, my whole framework, right, is around awareness, meaning everyone has to kind of have a new level of literacy. And I loved what you said. It's about reinvention. It's kind of a reinvention of ourselves, a reinvention of the problems we can solve with this technology. Like, we— many of us as a human, you know, as society, we tend to kind of identify with a problem, and then we picture how we'd solve that problem with the stuff we've got right now. And due to the nature of the speed that you're talking about, Natalie, like, everything is moving so fast that the tools that are available— like, you can now start working on solving a problem, and the tool to solve it can show up after you've started thinking about it. Like, um, you can even make the tool that you need, but not if you're attached to I mean, I remember teaching Java programmers back in the day, and they were COBOL programmers. And I remember them calling me kiddo and being like, I'm never going to use a— what did they— it was an integrated development environment. Y'all remember these IDEs? Like VS Code. But back in the day, everyone uses VS Code today. But back in the day, it was like ChatGPT, where people were like, I don't know about this. I don't know about using a platform that can generate code. It wasn't generating it using AI. It was just like pattern matching. But it was so new and so crazy. And most people were like, I would rather just write it in a text, you know, in a text editor, Notepad, Note++ or Notepad++ or whatever it was. It was ridiculous. I looked at them like, why would you do it that way? Like, why would you attach— why would you be so attached to that? But that's the same thing. We're attached kind of the way we've thought, the way we've solved problems. And to your point, it is massively evolving. And so we need to teach people how to evolve their thinking, like as a skill, not what to do, not what tools to use, though.

Yes.

But really, how do you just evolve your thinking? Javier, I see your hand up.

Join in.

OK, so I'm obviously with Nancy on this. And obviously, when I listen to Noelle Russell, very encouraging, it's like because I feel like, OK, I came from IT. In engineering 15 years ago, and I already knew things were going to like speed up quickly. The moment I graduated, I moved to Silicon Valley, and like 5 years later, yeah, IT is taking over. It's like, no, DevOps took over. And it's like, how are you going to learn and use software changed? And then even though I already knew about artificial, uh, artificial intelligence coming out of school in 2000s, It's like, use NLPs, you know, natural language processing models. That's the word for AI. But the thing is like, okay, this— if the moment you implement this into any software, then you need to understand how you're going to integrate it. And then the moment I figured out in Silicon Valley, I think this is probably 2015, it's like, all right, you have your data framework, and that data framework is going to be able to work with this software and these applications now are going to create different models. And I'm like, okay, so how can I do this? It's going to be better or worse for me? Because then I'm like, and it's a matter of like, because I want to be able to learn. And they were like, if you learn this one thing for the next 3 months, then you're gonna be able to like really expand into multiple things for you to adapt and learn. And it probably helped you and your team. It's like, okay, I'm open to it. And I think that's the part that is most people are afraid of, like being open to learn how something can actually help them. And even if it feels scary, it's like, it's part of like, it's kind of like you get very comfortable. And my dad is one of them. My dad learned in COBOL. I learned to, to when I was in high school in Venezuela. The, the language to learn was COBOL. Yeah, I was like, that's a long time ago. And then I asked my dad, and it's like, so you learn what, C#? He's like, that was the last thing I did. And it's like, and I thought, like, what do you use now? Like Python? He's like, don't know what it is. Okay, so, and I asked him now, I was like, are you afraid of using artificial intelligence? Because, you know, it's everywhere now. And he's like, I don't know how to use it. I would rather just use my Google search bar and get information from there right now than actually try to interact with artificial intelligence. But it's like, okay, then I asked him like, what if you just ask this something, like literally ask in Spanish? Yes, give you the information you want. And he's like, that will be helpful. I was like, okay, so then that means that you need to be open Yes, yes.

And have that like experimental mindset, which to your point, like generationally, that can be very difficult. But I love this train of thought that we are on. I think it's a great way for us to break out right now. I'm gonna ask you to take a second and think about like, you're— we're all on a learning journey. It's why you joined a community like this. So I would love for you to break out into rooms and share just one, and it doesn't have to be a thing specifically, but like How do you— what are you learning right now, and how are you learning it? Do not say anything in this community. Obviously, y'all are here. I hope you're taking these classes. But, but like, did you find it late, like this week? Oh my gosh, there was a video on YouTube. Here's the link, right? I think it's a really cool opportunity for us to just share, and I, I would anticipate our resources are gonna be quite diverse because we're all doing very different things. And I'm going to encourage you to always be prepared for this. Question when you come here. Like, what's one thing you learned this week? Every Friday you should have at least one thing. We should have many things. Many of us learn new things every single day, um, but get in the habit of acquiring information, but then most importantly, being willing to share that with other people. So as we go into our breakouts, this is our time where we actually get to meet each other. So go round robin, find out who's in your room, and then just share something that you've learned or a mechanism that you use to learn. I use YouTube or Y'all know me. I like this new platform called Hux. H-U-X-E. It's awesome. I like listen to problem solving all day long. It's trained on me, trained on my calendar, trained on people I talk to and the companies I work with. So I get very hyperfocused information. So Hux is the way I learn now, is that it's contextual to what I do. But I would love to hear what tools you're using to acquire knowledge and any specific knowledge you've acquired during this week if you are up. To hanging out and sharing. We're gonna take about 10 minutes to have this conversation. If you— I'm gonna say whoever has the shortest hair is gonna lead that conversation and just help everyone have a chance to, to say something in a 10-minute window, and then we'll come back and say goodbye. So, ready, break. Okay, hold on. So I'm gonna break us into rooms. I tried to remove the robots, so good luck. Okay, here we go. Just press the button. Great to see you. Oh my gosh, I have to talk about Satine Adela when we get back.

Noelle? Yes.

Um, okay, hold on, broadcasting. Do not like— yeah, hold on. Um, so thank you everybody. So excited to have you here. Happy Friday. Have an amazing, wonderful, crazy good weekend. As I will always tell you, just start learning. It's the most important skill you can acquire is the ability to have a flexible mindset that allows you to acquire new information. We are right now in breakout rooms learning from each other on how we learn and what we're learning. I will, as I mentioned earlier in the call, I use, um, Today, or I guess a few days ago, I downloaded Orchestrate from IBM and started using it. I'm so excited about it. I created a couple of demo videos I'm going to share with the community. I also downloaded the Atlas browser and started playing with that and seeing how I could replicate my experience on Arc in Atlas. So just always kind of look for opportunities to, to do new things in new ways with new information. And if you have any trouble doing this, the best thing you can do is join a community full of people that are constantly looking for ways to evolve. And that is us here in the I Love AI community. You can go to noelle.ai to see us, to join us. We can't wait to see you. So have a great weekend and we'll see you later. Thanks everybody.

Bye.