How to Become an AI Solutions Architect

We did it. I finally— now you'll see it on LinkedIn and Facebook, all of our amazing channels. So welcome. We are here ready to get going with our How to Become an AI Solution Architect. Now, this is actually based on a book I wrote last year, maybe, called The 21 Laws of AI Solution Architecture. So I'm gonna be sharing with you my perspective, but I'm also going to invite you to share your perspective. There are many AI solution architects here because we started this journey a while ago. But there's also some of you who are relatively new to the game. And so, and maybe some of you who are deciding, maybe you've always been an AI solution architect at heart, but you're deciding to move more intentionally into this space. And so that's why I wanted to talk to you all today and share with you kind of, and I do this every year, we go through and I do a couple of these sessions. I actually am gonna be doing this twice. So today we have a longer session. We're gonna talk until about noon. And then at noon, if you have any questions about our program or about anything like that, about what I've said or any of the principles, we will have about 30 minutes from 12 to 12:30 Eastern Standard Time just for Q&A. But we are also next week on Tuesday— oh, maybe I can't remember. I can't remember. Anyway, you could look it up on Maven. Maybe we could throw the link in the chat. But on Maven, we are going to be doing a lightning session. And so on Maven, that means a lightning session is A little bit shorter, but it's on the Maven platform, so it's exposed to all the Maven people. It is a Maven course. If you've never heard of Maven, it is one of my favorite platforms for teaching courses. And so I teach all of my certification workshops are all taught on the Maven platform. And so you'll get a link to that later today as well if you're interested in seeing what we've done and all of our testimonials and all of that. It's been a really fun ride. I also, again, As someone who does the thing, I want to also teach you how I do it. So as a solution architect, my goal always is to teach what I know, right? My job is to sit in— as an AI solution architect, my job is to often sit in between kind of the amazing, brilliant engineers and data scientists building technology and the businesses that need that information. And I am the translator, right? I'm the magical unicorn that sits between the two where I understand business value and selling and marketing, and I'm I also understand the inner workings of AI systems, machine learning, reinforcement learning, supervised learning. Like, I understand how to take an AI solution that someone has built and architect it to match the business value of a company and what they're trying to do. This is the fastest growing role in the United States right now, maybe globally, but I only look at US data. I'm sorry. But, and if some of you are from out of, you know, somewhere else and you know that, like, in Sydney, this is all the rage, please let us know. But I certainly in the United States, this is a very popular role. And the reason why is because there's, there are a collection of people that know how to build AI. There's a bunch of people who can talk AI. There's very few people who can walk the talk, who can actually bridge the gap between the talkers and the doers. And that's the magic of who we are and what we do, or at least what I do. So I'm going to share with you my perspective on, on that and what I have come up with, my— what I love about it. Oh, yeah. Thanks, Sherilyn. Oh, it's on the 28th. Oh, that's right. We're doing it on Friday. So I get to tell you about a bunch of things we're doing on Friday because Friday we have a vibe-a-thon. So one of the core characteristics, one of the laws is that we're doers, not talkers as a solution architect, right? Your job is not to just present slides and be a good talker and convince someone to do something. Your job is to actually demonstrate value, build. One of the things that always would surprise my teams when I would go in and talk to a client is that I not only could tell a good story, be a storyteller about the value that the technology I was presenting provided, but that I could also then in real time build the solution based on what the client was asking. Right there. Now, in the world of generative AI, it's even more accessible. We can vibe code right in front of our client what they're asking for. Now, there is a method to this madness, right? Because you can't vibe code your way to— you can't boil the ocean in front of a client on a 1-hour call. You also have to be very careful about your approach when you do that, because you could end up demonstrating, A, something that they don't care about, or B, something that you can't deliver. And so there are some core values of a solution architect that I'm gonna share with you today, that I really wanna make sure that you understand, but also that I think are critical to the process of solving problems for businesses. And here's the good news is that I've done this. I always say I go from the boardroom to the whiteboard to the keyboard. I try to do it at the executive level, of a business. But that being said, executive in the sense that they are the decision maker. I don't— I have worked for the biggest companies in the world. Okay, now there's a bigger company, like Nvidia is kind of the biggest company, and I haven't worked for them. Actually, I have worked for them. Oh, they're a client of mine, but I didn't like— I wasn't an employee in that company. Um, that's cool. Uh, anyway, so they're one of my clients, but I didn't actually, uh, wasn't an employee But I have been an employee and literally doing solution architecture at scale inside companies like Microsoft, Amazon, IBM, right? Red Hat, where I have facilitated the development of kind of this skill. As a matter of fact, to give you a little history for those of you that don't know, my journey into becoming a solution architect, which I love this role. Some of you have this role today, maybe not specific to AI. But as a solution architect, my journey started actually at Red Hat in like 2008, maybe. Oh my gosh, that dates me a little bit. So in 2008, I got hired there. Actually, I was hired from IBM. I was kind of poached, if you will, or what do they call it, stolen? Anyway, but the reason why is because at that time, it's really ironic because Red Hat and IBM are friends now. I mean, they're family now. But back then, they were kind of like arch nemesis. They were like completely opposite where IBM was like, you know, closed and, and, you know, doing their own thing and, and Red Hat was open source and, and really driving the open source methodology, which is why it's so good that IBM actually bought them, right? And, and brought that open source in and made IBM have a little bit more openness to it. But that being said, I was hired as one of the first global as or global solution architects for basically middleware solutions. I do remember the service-oriented architecture, you know, SOAP, these protocols that we'd use to communicate between services, business process execution language, all of that back in the day. Basically, my job was to architect companies to go from, hey, we've got a bunch of tech over here, we have a business problem we need to solve over here, how do we take this, you know, maybe 70 different tools and assemble them together in a— not in a, uh, in a way that basically I want to say autonomous, but it wasn't really autonomous. It was just, uh, leveraging automations and workflows, uh, all before artificial intelligence is what it is today. So that was, you know, almost, I guess, a long time ago. Oh my God, it's almost 20 years ago. That's ridiculous. Um, so that was a long time ago, but I loved that role. I always used to call it my golden years because I got to constantly learn new technology in order to keep my toolbox full of the latest and greatest tools. But at the same time, I had to stay extremely present to my customers, to what they needed, what they wanted, um, what, what was safe, what was secure, what was responsible. I was always kind of having to bridge the gap, bridge, uh, the solution between the two. And it's my favorite thing to do because without it, the customer doesn't get what they need, right? They never get to use the thing they bought. They never get to implement successfully the investments that they're making. And that brings me to why I focused on AI solution architecture about 4 years ago, because I realized— and this is before ChatGPT launched, because I was really thinking more about traditional AI, right? When you're building traditional AI solutions, how important it is to really be this, you know, to have someone who understands both sides. But as we moved into the world of generative AI in 2020, I realized it was even more important. But the reason I guess what prompted that realization was the fact that every company— I mean, I was at Microsoft in 2017, 2018. My job was to go into the executive boardrooms of Microsoft clients and talk to them about artificial intelligence and encourage them to think differently about it. Not that it's this hard thing that's happening in the academic institutions of the world, but that it's present and real and activated through an API, meaning you could start using it right now. Now, this is in 2017. And I always say it was like trying to feed vegetables to kids, right? Like, eat your broccoli. This is good for you. You should have some. Eat more. As a matter of fact, half your plate should be broccoli. This is me talking about AI, like you need to have this in your business. It's gonna change everything. In 2017, I ended up influencing a little over $2 billion in 2 years, meaning people bought $2 billion of AI from Microsoft and I was in the room influencing those decision makers to make that choice. Awesome. Super. I'm very proud. I was an engineer. I was like, this is awesome. I love this job. Um, I find out later though, over a few years, as I run into those executives that made this investment, I start asking them questions like, hey, remember I was your EBC person? I, I talked to you about this. You ended up buying this huge consumption. Like, how'd that go? And they're like, oh yeah, I didn't— we— I don't think we ever implemented that. And I was like, what? And they're like, yeah, I never used it. And not one company, but dozens of companies. I got very curious and I started hunting down companies. I won't name them, um, because I don't want to, like, you know, put them on the spot. But they're all— of course, they've all turned the corner now. Um, but back then they would buy it and not know what to do with it. And that is the challenge of me being on the product side of organizations, is that my job is only to sell the product. I didn't really have, like, I wasn't involved in, you know, once that invoice is signed and the PO is done, like, I wasn't involved anymore. So I didn't really understand how important it was to not just sell someone something, but also to prescribe them how to use it. And that's why I ended up joining a very large consulting organization, because I was like, okay, their mission was to help people implement what they buy. And I was like, well, that's exactly what I want to do. So I left Microsoft, joined this huge consulting organization, and said, I want to help people implement the AI that they do. And that, I think, is the marriage of the skill sets required to be a good AI solution architect is that you have to, you know, you basically need to understand that first you do need a decision maker, right? Boardroom, whiteboard, keyboard. The decision maker in the company does need to say, yes, I want to do this. But then you have to immediately in the same conversation be talking about what implementation looks like. Be talking about what delivering on that promise that you're making. So one of the laws of AI solution architecture is never write a check in a sales conversation that your engineers can't cash. How many of you are familiar with this concept, right? Like, so many times, I, as an engineer, would get a salesperson, and this happens, you know, my brother is a creative director, so I was happy and sad to find out this happens across industries. But he would be— it would be like on a Tuesday before Thanksgiving, and he would be given some crazy requests from the sales team. And he's like, I can't do that in time for Thanksgiving. They're like, it's crazy, we need to do this. The customer will sign if we do it. You got to do it. Meaning they wrote a check in the sales conversation that now an engineer or creative person has to go and cash. It's just not cool. Like so many times I've sat on that side of What did you say? One time I remember sitting and hearing a sales— an account manager say something to the effect of, we can do it in 2 weeks. And just so you know, absolutely nothing can be done in 2 weeks. Nothing. Nothing good. Right? And so I was like, what did you just say? In the meeting, I'm looking at— I'm giving him the side eye, right? Like, what are you talking about? And so I committed at that moment that I would never be, A, the person in the executive boardroom. I would never be that person that writes a check that my engineering team or my creative team would be like, you know, I can't say the word, but you really didn't help us out with this. This is not helpful. We now have to work at a velocity that is not conducive to operational excellence. Why would I want to do that? And the funny thing is the client doesn't actually care if it's 2 weeks or 2 months. They just wanna know that they're gonna get the valued outcome. So one of the laws of AI solution architecture is never be in the room and make a promise, like write a check that your engineering team or your creative team that they don't feel comfortable with, which means you need to be extremely empathetic to those teams, which means you have to be friends with them. You have to be connected with them, hanging out with them. I don't know, buy 'em hoodies or something like, Get to know what they can do, how they can do it. What I used to do as a solution architect is I would just ask the TPM or the technical program manager or the engineering manager. I just ask, hey, can I sit in on your retrospectives? Can I sit in on your sprint planning? Right? So I could understand these things. Now, as an engineer, it's easier for me to understand. So I do recognize some of you are not coming from an engineering background. But even more so then, sit in there and understand how engineers work so that when you are, right, one foot in engineering, one foot in the sales experience, right, when you are talking to a client, you can speak from, oh my gosh, you know what, I know what that looks like. I know how that works. I understand. So that's one piece. Now, another principle, another law of AI solution architecture, which is probably my favorite, is, I don't know, I guess they're all my favorite, But it's thinking through the concept of like when you walk into a room, you have a choice to make. And this is part of my leadership principles. Actually, I was gonna wear that shirt today and I forgot. But I have a set of leadership principles. It's called the Lamplighter Effect. And the Lamplighter Effect is actually an acronym. I won't give you all of them because we're gonna do lots of webinars on this and you can come and check it out. But the Lamplighter Effect, the first 4 stands for these are leadership principles I embody every day and work on constantly. But I want to be, right, LAMP, L-A-M-P, as— and it's— there's, uh, words for all of them. As a matter of fact, not to get distracted, I just created a whole collectible series of characters that go with each one. Adorable. Um, so I'll share for you all in the AI Leadership Institute. I'm totally giving you the reveal in December. Um, it's fantastic. Uh, but Eve, just so you know, I am not building plushies. So I'm saving the world by not building plushies. I mean, I'm going to try my hardest not to create plushies. But the Lamplighter Effect is a set of leadership principles that I've come to embody in my career. And the first 4, I think, are worthwhile talking about right now because they're attached to this law. And the first one is love, leading with love, not being, you know, not like ushy-gushy love or boyfriend-girlfriend love, right? What I, what, what is, what I've come to understand in my life and in my experience, it's a term called agape love. It's kind of like this just unconditional perspective of caring, just caring about people, caring about their outcomes, caring about your engineers, just ultimately leading with this idea that you care about people. And you'd be surprised what a flex this is, right? Like the opportunities that you get when you lead with just a loving, caring leadership style. The second thing is A, ambition. Now, in my leadership principles, just like the leadership principles at Amazon, if you know them, they live in tension. So it's kind of hard to be, you know, some of these it's very hard to do at the same time. But that's the whole point, is that I still attempt to do them at the same time. But ambition is important, right? I always want to strive to do more than all— I mean, more than I ever wanted, right? Like, I always strive to dream, to build big, hairy, audacious goals always. So this brings me to— I think I have it here— an exercise we're going to be doing in the AI Leadership Institute for people who have joined us for the 2026 cohort. We have a special bonus called Design Your Life, and I do this for myself every year. I got a new Moleskine notebook. But what I like about it is actually I can't, you know, have a conversation with you all without talking tech a little bit. I don't see— oh, yeah, here it is. So this is the Smart Moleskine notebook. It comes with a digital pen. Some of you might remember this. This is not a new pen, but they have a new version. This is a new notebook, though. But in this notebook, basically, as you write it, there's a little, like, envelope symbol, and you can digitize everything you do. So I'm just going to share with you— this is me doing my work for this year. But let me see. Right? This is the plan, right? This is my 2026 plan. Now, I am a writer. I like writing. I have Remarkables. I like just using my handwriting skills all the time. So you could do this electronically. But what I encourage you not to do is plan out your own success with a tool like ChatGPT. Like, that is not what success looks like. You're not gonna ask ChatGPT how to be successful. You're not gonna ask it what success looks like because it doesn't know you. The way you know you. And so I do this work, and then I use ChatGPT to maybe help me get there, deliver results from that perspective. But I start first with me. And so ambition is being willing to set goals for yourself consistently and to consistently prescribe for yourself the activities that it will take to get there. So that's what we are doing actually in December. One of the days in December, 12th, maybe. Sherilyn can throw it in the chat. But we are doing a Design Your Life session. And so what we're gonna do is we're gonna set our own personal goals. So my goals are in the area of personal, professional, financial, my lifestyle goals, my inner circle, who I wanna be around and who I wanna hang out with, my income goals, of course, relationship goals, and health and fitness goals. And so I have different things that I want to do in each one of them. That goal I have for who I'm going to be at the end of 2026, I reverse engineer. So I start last year, like, I mean, I start in December 2026 and I work backwards. A skill I learned at, um, December 12th. Thank you very much, December 12th. Um, so it's a skill. I, I work backwards from who I want to be at the end of 2026, and I work backwards from there. And I did the same thing for 2025, and I exceeded all my goals, which meant to me, right? Have you ever had that experience when you go and, you know, maybe you are negotiating a salary and you give them a price and they're like, great, done? And you're like, whoa, wait, no, I meant more. Um, you agreed too fast, right? Like, you always want them to hesitate. If you say a number, you want people to be like, ooh, that's a lot. Um, maybe, okay, let me go back. Like, that's the reaction. You don't want them to be like, if you say I want $500,000, they're like, great. Um, sign here and you're like, wait, I meant $750,000. So similarly, when you write your goals, right, you, you don't want to get to the end of the year and be like, yeah, I did that in July, right? That means in July you redo this. And that's what I do. Um, so I've mapped out my goals, but here's the kicker is that I start with who I want to be in 2026, December. I work backwards by quarter. So every quarter I know what my goals need to be to get to where I want to be in 20— at the end of 2026. Then each quarter I break down by month, each month I break down by week, each week I break down by day. So I have a day-to-day plan of attack every single day that tells me if I do these things, I will be on track to get the thing I want to do, the, uh, who I want to be, what I want to have. I can achieve that. So that is the exercise we are doing. Of course, it's only available to those people who have joined our, um, our program. You can head over to our AI, actually, it's, I think it's, I'll put the URL in here if you want to like talk to us about doing it. But it's basically our upskilling, like, www. Oopsie, I'm gonna misspell it. www. If you want to go check out what it, what's in it, including the Design Your Life session, I have the URL upskilling.ai. Isn't that cool? I got it like 6 years ago. Who knew it would become so popular? But It's our Essentials program. And of course, this, this course, this masterclass and certification on how to become an AI solution architect, it is included. Today we're just doing like a fun recreation, if you will, a little, a little crash course. But if you want to get certified as an AI solution architect, one of the ways to do that is through our Essentials program. And you can fill out the application. One of our C-suite will get on the phone with you and it'll be really fun. Um, yes, exactly, exactly. Um, yes, uh, Maurice, yes, exactly. That's my problem. It used to be my problem too, is that I would, I would start out strong and then like a month or 2 months or 3 months or worse, 6 months will go by and I'll be like, huh, whatever happened to that thing I was gonna do, right? And especially someone like me, I have ADHD. I'm proud of it. It's the way my brain was built. Uh, it's not a problem. Um, however, because of that, I have to just be so narrowly focused on how I'm going to achieve my goal. Some of you maybe don't need this. Maybe some of you are like, no, no, I set a goal in January and I'm still actively working on it in the middle of October, uh, with no additional prodding or planning. Good, that's amazing. You should probably build a class on that. Um, but for me, this system has worked so well that I've been able to do things that I never thought I would do. For example, and I'll tell you one of the things I'm doing this coming year that I'm really excited excited about. But for example, 4 years ago, maybe 5, I started putting— I wanted to be a best-selling author. I hate writing, um, but I wanted to be a best-selling author. I also said I wanted to do a TED Talk. I also said I wanted to speak on stage. I also said I wanted to make $100,000 in a single month. That was my goal, um, in a month. I mean, now I'm like trying to do that in a day, but in a single month. And so I set these goals when I had No, it was not in my purview. I could not see a way to get there. I set those goals. I did not achieve those goals in the year that I set them, right? It actually took time. However, I started to, like, because every single day I worked on it, things started to change. I started to collect a huge following on social media. People started reaching out to me to start speaking. I, I don't know if you know this, but when you start speaking a lot, publishers notice you. So that's what happened. I started speaking a lot, which was a product of the work I was doing. Then Wiley was like, hey, we saw you do this keynote, we'd like you to write a book on it. 2 years later, I'm writing the book. This was 2 years ago. I write the book this year. Now, 5 years later, I had these dreams during COVID when I was dreaming a lot. 5 years later, I published this book. I get signed a second book. I do a TED Talk that, oh, hit 4,000— 400,000 views this week. What? Right? But none of— I don't know, maybe it would have just happened. I don't think so. I think it's directly correlated to my ambition and my, my interest in staying focused on what I want and how I want it over day by day, month by month, year by year. Um, so, oh, thank you. Yes, join the party. If you haven't seen my TED Talk, please take a look at it. Um, but yes, and some— and I will tell you a fun fact. It's as slow or as fast as you want to go, right? Like, I look back now and go, I could have done that faster. My mindset wasn't there. I, I, for me, in my head, I'm like, that's hard. And as soon as I say it's hard, that means it's going to take me longer. Could I have said it was easy? Probably. But I did it. That was just my mindset. So whether it's slow or fast is completely up to you. So this Lamplighter's Leadership Principle The first one being love, right? Lead with love. Be ambitious. Don't be afraid to be ambitious. The last two go together— mindfulness and purpose. Being intentional, working on purpose, like having a reason for doing what you do. My reason for being is my family. The reason that I push so hard to let everyone know what responsible AI looks like is because I have 6 kids, and the world is— I'm worried about the world in the future. They're worried about the world, right? And I listen to them. I don't like, shoo, shoo, like, oh, you're kids, what do you know? I listen to the things that they're concerned about. And they're 8, 9, 10, 18, 19, and 20, and they've got very interesting concerns about what AI is doing. Like, it was so cool. We just went to Great Wolf Lodge and they said— they intentionally, they themselves were like, we're not using devices on this trip. I was like, I know, you're right. Um, but Uh, but it was so cool that they, they wanted an experience where it was just us looking face to face, that we weren't at a dinner table on vacation all on our phones. I mean, we're not that family anyway, but like that they were like communicating that. And so living on purpose, living with intention, that's my purpose, is to ensure that everyone realizes there is a time and a place for technology, but it isn't everywhere and it isn't everything. Um, and that human connection is actually going to become extremely valuable as we move forward. Live events, meeting face to face, right? Doing business, shaking hands. Like, this is all something that we're seeing an increase of as technology removes the mundane, right? As we get rid of things that would have kept us tied to our desk, it gives us an opportunity now to do much more collaboration, innovation in person with each other. So I think that is interesting. So all those four They tie to the law in AI Solution Architecture, one of the laws of always be the most positive person in the room. And I say that because if you have a purpose and you are able to be present and you've got an ambition, like you are ambitious, you've set a goal, you know where you're going, it is so easy to be like, this is the most exciting moment in my life right now. Today is the most exciting day because I am taking the steps to achieve my dreams. And once you do it once, once you set these goals and you do the work and you— a dream is achieved, it's extremely inspiring, like, to yourself. Now, I want to give you a little tip, uh, that I used in the early days of me kind of building the muscle of delivering with excellence on my own promises to myself. The way they started, um, some of you know this because I, I have water bottles everywhere, but the way they started was First, I would set— how many of you are familiar with habit trackers, right? I would use a habit tracker. And the most important thing you could do is make a promise to yourself and keep it and do it consistently. Because when you do that, no one is looking, only you. But when you keep that promise to yourself, a little part of you is like, I believe what you say. When you set a goal that says I'm going to make $100,000 in a single day, it's going to be— your brain is going to be like, yeah, right. OK, sure. But the more of these little micro-commitments you make to yourself and keep, right? And then you celebrate and you're like, good job, Noelle, you did 7 days of water. For example, I tried— I have a certain amount of water I drink every day and, um, and I celebrate every 7 days when I do. And I don't do it every— like, I'm not consistent about doing it, but when I do, I celebrate. I'm like, good for you, Noelle, you committed to drinking this amount of water every single day for 7 days and you did it. Another one is working out, uh, infrared sauna, um, running, because I like running. Um, I like it, but it's time-consuming. And so, you know, anyway, but all these things I set a habit tracker for. I track those habits. I set a goal for a time frame, short and sweet. A week is good. But the most important thing is to literally kind of in your, in your mind or out loud or on a piece of paper I commit to doing this. I commit to running 3 times this week. And then at the end of the week, when you do your weekly review, which hopefully you'll get in the habit of doing, you'll be like, I did that, check, good for me. And that part of your brain is now going to believe a little bit more that this big, hairy, audacious goal, that you actually might do it. If you ran 3 times this week, drank all the water you said, meditated like you said, I actually— if you say you're gonna do this I believe you. But sometimes— well, I use a word, uh, this is another one of my principles: congruence. Sometimes we don't operate in congruence. Congruence is the idea that everything is aligned— what we think, what we say, and what we do are in alignment. And I try to do that all the time. I try— I mean, I honestly have very little filter between what I think and what I say, so that makes it easy. But what I do, that's different. Right? When I say something, I need to then follow it up with doing that thing, or my actions being in alignment with that, right? So for example, that's why I write down my plan and I review it every single day, so that I can state that this is my thoughts written on paper. I'm now going to speak it. I'm not going to be like, okay, this is what I want to do. I'm telling you all, holding myself accountable on LinkedIn Live. And then most importantly though, I do the work. And maybe nobody sees that work, they only see the results, but I have to be the one that does the work. And that congruence is where success sits. And the more positive you can be in that experience— and this is why I say every time I walk into a room, no matter what room it is, but specifically in a room where I'm trying to, you know, create a, um, a relationship, a business relationship, or sell something, right? Every time I make that, like, mentally I'm like I'm going to be the most positive person in the room. And here's the cool thing, sometimes you won't be, and you'll be trying, and there's someone else who knows what we're doing and is like, they're positive. But there is zero, like, disadvantage to having everyone in the room trying to be their best self, right? Trying to be them on their best day. I think it's amazing. So that attitude— and here's the other value of that— is that when you are communicating to someone and you are positive and exciting and, and like enthusiastic, right? People always comment on my energy. I'm not always energetic, but I choose. It's one of my— if you go and look at my Instagram, noelle.ai, you will see a pinned post for the 7 Virtues of Mindful Leadership. And one of them is just to choose to be happy. It is a choice in every moment. And I will tell you, I've had some horrible things happen in my life, like really bad, tear-jerking bad, like awful to myself, to my family, like Awful. But I choose, I choose the story that I operate from. I choose to not let that be my story, to let this be my story, to define my story, to create my own goals, to set my own success, right? And to share my excitement with everyone because I am excited about life. I am excited about the opportunity we have in AI. And so that is a, a law in my opinion, in order to be successful as an AI solution architect, you lead with that enthusiastic, happy, um, positive outlook. I'm not saying that if something bad happens to you, you can't process it and you can't take a moment and you can't cry your eyes out over your dishes like I have done. Like, that might happen, but it is a choice. I choose to cry over my dishes. I choose to wallow in a moment where I feel betrayed. But then I always say, feel the feels, And then make a plan. Then I'm like, all right, now what? How do I use this story to my benefit? And some people don't think I process enough, but I mean, if you get good at it, I can clock how long it takes me to get over someone betraying me. And it just happened recently. I was like, like, what? And but then I was like, okay, I know this feeling. It's fine. I get it. I'm going to process it. I sat in a little corner in my office. I let the tears flow. And then I got up and I was like, all right, now what do I do? On to the next. Where is my plan of attack? So it's up to you how this works. But as a solution architect, the benefit of this is that every meeting I show up in, I am excited to be there. I'm happy and I am ultimately enthusiastic about the outcome I can generate for my client. And genuinely, intentionally, mindfully, I am present in that moment. No matter what just happened to me. You know, earlier that day or the day before or years before. Um, oh, thank you. Um, right, thank you. Okay, awesome. Um, thank you. Okay, so we've covered a few of these, um, of these laws so far. Uh, one of the things that we covered was, um, of course, you know, or one of the things we haven't covered that I wanted to talk about, which I think is a big part of being a solution architect, is the importance of actually, and we mentioned it earlier, but I want to dive into it a little bit more, which is being, you know, a doer and not a talker, is that I, I do not want to give you the wrong impression that you can, you know, smile your way into a positive outcome with a client without actually knowing what you're talking about. So half of my job as a solution architect is to understand the business, to understand what value is to them, to understand what good looks like, what what, what outcome they want. But the other half, which is equally as important, is to actually have my fingers on keyboard, on keyboard, building stuff to generate that outcome. Now, I like to be as close to that implementation as possible, so much so that I encourage you, as you know, a solution architect, your job is to actually be thinking, right? This is the technology side. Even if you're not, if you consider yourself not to be technical, it is your responsibility to learn the architectures of these systems. And here's the good news, is that they are available for you to learn. So one of the things I do— I'm gonna actually, um, yeah, I think I'm gonna share my screen. Hold on, let me see if I can pull it up. One of the things I want to share with you, um, is the mechanisms by which I educate myself on solutions that are— I can't be everywhere at once. I'm not working for— I work for my own company, so I'm limited by the number of clients I get to see because I only have I have my clients and my bandwidth, but I can exponentially grow my understanding of how these systems work and how they're architected by connecting to other companies that are doing this work. And those companies are nice enough to share it on platforms like GitHub. So I'm going to show you what I do, and this is just again for your own benefit. Let me— I'm going to minimize my screen here. Um, there we go. Let's go here. Uh, all right, let's hope I'm signed in. Uh, of course I'm not, but it shouldn't take too long. And then I will share my screen and show you what I do. Um, and hopefully— of course, multi-factor authentication, no worries, almost there. Um, do you do— hold that thought. 405. All right, here we go. I'm in, I'm in. All right, I'm gonna share my screen really quick. I think this is it. Share. Alright, let me know if you could see this in the chat. Give me a thumbs up, or you could thumbs up me. I can see your faces too. So that's great. Okay, here we go. So let me close this. Do, do, do, do. Just orientate. Okay, so here we are. So I have a ton of repos here, but one of the things, and I'm just gonna show you a few and I'll throw the links into the chat. As well. But these are some of my favorites. So first things first, as a solution architect, you should be armed— oops, sorry— you should be armed with a bunch of different ways that you can talk about, teach, and demonstrate the value of what you're doing, right? Whether— whatever architecture you're selling. And so I'm gonna show you, I'm gonna go into AI agents for beginners. This is a course built by Microsoft. It's not a— I think there are videos in here now, but that's not why I'm showing you. If you scroll down the README all the way at the bottom, you will see a collection. First, these are— anyway, I won't get distracted. But you'll see a bunch of courses built by Microsoft for people like us, for solution architects. The benefit of this is that many of these have code examples built in. So let's say you're like, but I've never built that before. You can build it. This is exactly what I did at Amazon Alexa. I wanted to become— I wanted to join the Amazon Alexa team. And then when I joined, I was like, I want to be the number one builder. I want to build as many applications as possible. I built over 100 in my first year there. The way that I did it is I went into GitHub and I just looked for people building natural language applications and I just started rebuilding their apps. Now, in the beginning, there were quite a few people that were building Alexa apps. As a matter of fact, my focus ended up being on building, how many, I don't know if any of you would know this, but in the beginning there was a bunch of open source projects building Alexa into Raspberry Pis. So you could, rather than buy a device, you would buy a little Raspberry Pi, put in your headphones, and then you would use it. And, and you could basically, it was push to talk. You could press a little button on your headphones and you could talk to Alexa and the Alexa voice service would reply back to you. And it was a, I was like, ma, it was magic to me.. And so I would build hundreds of these, like, oh, build, build, build, build, build. So I was building this, um, like basically muscle memory, right? And how to develop these solutions that served me so well. I mean, I knew, but when I would talk to a client, they'd be like, well, this happened, or this problem occurred, or this, I ran into this challenge. I'd be like, oh, I know exactly what that is. And the amount of credibility that I got in just being able to recognize their problems and even guide them to, oh, well, this is what I did to fix it. When you can say that most people that are having these conversations with clients have never done the thing ever, not even in practice. They've only ever talked about it. They've only ever watched YouTube. The distinction between an AI solution architect and everyone else is that we have the courage to build and we have the courage to do it on our own time, on the weekends for fun, right? So that when we show up in front of a client and we actually demonstrate something to them and they ask us a question, we can be like, oh my gosh, yeah, you know what, the first time I built this, this is what happened, and I realized what I had done wrong. And then you can explain to them the most common problems that happen because you will have experienced them yourself. Is it hard? Um, yes, maybe. Is it a lot of work? Yeah, but it is an investment that you make in being able to solve, like, I will give you an example. Way back in the day, in the Y2K time frame, I worked at, uh, IBM, and I was one of the very few leaders who understand— who understood WebSphere. I wrote the book on WebSphere. Any of you remember IBM WebSphere? Anyway, it was like my first child, right? So IBM WebSphere, I knew it like the back of my hand. So if I go into a client and they have a stack trace of some error that they're having in their system, you know, sysadmin world, I could tell what it was. It was like The Matrix. I could see immediately. I knew exactly what it was when I saw that stuff, and it didn't matter, but only because I had seen hundreds of thousands of stack traces and had managed to fix them all, right? So over time, there's a finite set of problems that your customers will face and want to solve. A finite set, meaning that it's not infinite. They're not gonna, you know, it's not like every company is imagining completely net new problems. Like, Most companies have the same set of problems. And once you learn— now granted, that problem set might be 1,000. For, um, WebSphere, there was like 3,000 different problems. But once you know all 3,000, then that's it. Like, everything you've seen before, everything you've managed and done before. So it's a really— like, these kind of practice, the practice you can get, um, I think is really important. So this is one thing. Oh yeah. Thank you. One thing, I will throw this into the chat if I can find my chat window. Let's find it. Hold on. Oh, there you are. OK, cool. So here you go. So that's just an example and you— oh, this is mine. Oopsie, hold on, let me— I forked it because I was like messing around with the repos. But let me send you to the Microsoft one so that you can then see all of their originals. So yeah, let me do this. Sorry about that. I mean, you're welcome to use mine. Oh, and I only sent it to host, so there you go. All right. Oh, copy link address, not the words. There you go. So you can go and check it out. And like I said, the benefit of this one, this is the agent one. These are classes. They're not facilitated. It's not like what I do, but this is all— I think, I mean, as an architect, this is so valuable to you because if you look at the license, it is You can use this content commercially. You could distribute it. You could use it private. Like, it means that you can use all of this information without having to pay it or attribute it or anything like that. Granted, there's no liability or warranty on its behavior, and it could break at any time. But this is gold for a solution architect, right? Like, these are tools that you can stick in your toolbox and say, hey, I mean, one of the things I often will lead with, with an organization, by the way, My goal at the end of every conversation with a company is to end with an action we can take together. And now I can be like, by the way, I teach an Agentic AI for Beginners course. Would you all be interested in doing that? And now you have the content, the slides, the labs. The only thing you have to do is— the only thing you have to do is have done the work, right? To have done the work to know what you're doing, right? You will have gone through the material. You will understand it. But again, this is— This is finite. Like, once you learn this, it's in your toolbox. But that is the important part, is not just be good at talking the talk and telling good stories and getting people to lean in and be excited. The second part is actually having, like, the time in seat, fingers on keyboard experience building these solutions. And my hope is that you see some opportunity here because as a solution architect, you don't have to wait for a client.. You don't have to wait for someone to come to you and be like, hey, I want you to build this to get experience. This is what I did at Alexa. I built all of these apps with no clients at all. I made the client up in my head and went, all right, if you're a nonprofit in Washington, DC, I built a, an, uh, a model called JusticeGPT. JusticeGPT. I built that model. I grabbed the URL. I didn't have a client. I had an idea. And I was like, oh my gosh, if I had a nonprofit who was interested in creating a fine-tuned model on how to provide advocacy coaching to people who are trying to get justice for their, you know, incarcerated spouse or child. How could I help them? And I built that. No, I never sold it. I didn't even want to sell it. I just built it to create the experience, right? To, to, uh, create the muscle memory of how I might solve that problem. I learned in that exercise how to fine-tune a model. I learned in that exercise how to make sure I designed with people. So I went and reached out to— I connected with a company called Dream.org, right? So I used a lot of information as if I was getting paid to do it, but I got that experience on my own. I didn't need to wait for anyone to say yes. And that, I think, is a core value of a solution architect, is that your job is to get practice building solutions without having to wait. You don't have to wait. And that, I think, is the most important maybe message is that you can start your journey into AI solution architecture right now. Like today, right now. Okay, the last repo I wanna share with you before we end it and go into Q&A, the last repo I wanna share with you is what I call or what is known as AI solution accelerators. And there's lots of organizations that do this. What is happening? Right now. I can't see. Oh, there we go. So AI solution accelerator. So I'm gonna go back in, and these solution accelerators represent organizations like Microsoft, Amazon, Google. They've created solutions for their clients and then anonymized them and made them available to you. So I'm gonna just type in and see if it pops up. Yay, there we go. So this is an example. These are Jupyter Notebooks, but I mean, just look, Airport code detection, like just rebuild all of these, right? Analyze meeting audio, build an avatar, use cognitive search, which is now AI search, use computer vision. These are all just solutions that were built for customers that if you go in and this is what I did, notice the time, it was 2 years ago, right? But you can go in and just build all of these things. Okay. Yeah. Thank you. Let me throw this into the chat. So this is where, right, someone who is a talker turns into a doer. If you practice what you preach, if you put your fingers on a keyboard and you do the thing and you build it, here's the first thing that's gonna happen is it's gonna be broken. Just to tell you from experience, the code won't work. But guess what we have now that we did not have 5 years ago? You can go in and you could say, hey, ChatGPT, or hey, Copilot, I'm building this thing and here's what it's doing. Help me fix this. And it will coach you. And you could even say, don't fix it for me. Coach me on the skills I would need to learn in order to fix this myself. Oh, yeah, yeah. Hold on. Oh, yeah. And I also want to give you the original repo that I used for this. So let me grab that link. Thank you very much. Thank you for that, Tiana. There we go. All right, cool. Chandra, thank you for putting that in there for me. Thank you very much. Oh yeah, there it is. Okay, Tiana, there you go. So that is— oh, and then of course you can follow me. I'm just Unity Girl, uh, and that says something about my history. Uh, I'm Unity Girl on GitHub. Um, yeah, of course, no problem. Thank you for being here. So we're gonna go into, um, Q&A now. I hope you got some insight, uh, into my, you know, philosophy of being an AI solution architect, some tools, right? I gave you a couple different, uh, things that I've personally used Then most importantly, this is only the beginning. This is a crash course in the philosophy of being an AI solution architect. There are 21 laws. I do want to send you— I'm going to go and take a look at our Maven course and throw in our book, The 21 Laws of AI Solution Architecture, in case you haven't seen it. Unless, Sherylyn, you have it handy, you could throw that link in, but I'll pull it up just in case. So Maven is where we're hosting our class next week on December 4th. It's a 5-day class. It runs from Thursday, Friday. You have the weekend to do some building, which I will assign to you, and then Monday, Tuesday, Wednesday. Then you have 2 weeks right before Christmas that you'll have an opportunity to do your capstone project and get your certification. So I'm going to go into my courses, which you will— oh, there we go, taking a second, and I will share with you Uh, this is our AI Solution Architect course. We've done this before. We've had about 200 people take the course. It's got 4.9 out of 5 stars. It's been extremely successful. So I hope you'll consider joining us. If you join us, we do have a discount code. You can type in webinar. I'll put it in the chat and it'll give you a discount code. I can't remember how much, but I think it's pretty good. So you can go and check it out. Um, but let me go into the lead magnets and share with you the book. So that you have an opportunity to actually just— oh, copy link. There we go. So you can grab the book on your own. There you go. Awesome. Yay. Oh gosh. Close. What is that? Close, close. All right, there we go. So I'm just gonna go to that page so you can see what it looks like. So it's the AI Solution Architecture book. It's literally, this is one of those things where I got an idea on how to bottle what I do which people thought I, I'm special and I have special skills and superpowers. And I was like, actually, no, I can teach this. And so this is my favorite course to teach. We teach it 3 times a year. This is the last time we're doing it in 2025. So hopefully you'll, um, you can grab the book, you'll get invited to join us. Uh, you can also just join the class itself, um, directly here. Like I said, there is a, uh, uh, promo code you can use, WEBINAR, if you want to. Um, but otherwise, I'm gonna take a look and see if anyone has any questions about any of the things. But there's quite— I mean, we didn't talk about all the things. Um, I also have a— I think it's a 7— 7, yeah, 7 series, uh, webinar series that I did on how to be a solution architect where I go through every single law. It's— I mean, in an hour, there's only so many we could do. We covered 3 of them. Um, but I do 3 times 7. So all 21 are covered in that, and that is free. It's a YouTube class, but you do have to send me a message and let me know you want to take it so I can give it to you. As a matter of fact, every one of you registered, I'll be sending you all a message, a thank you message, as a result of registering for this webinar, and I will give you the link to that playlist. It is a private playlist, so don't share with anyone. I always like to make sure you're my people before you see all my inside secret stuff. And so you'll be getting a link to that private playlist in the thank you email later today. So thank you for that. All right, welcome in. Any questions? All right, if you have questions, you can jot them in the chat. OpenShift recording. Oh, yeah, Chandra, that's right. I do have— that's also on YouTube. That's also on YouTube. And then great webinar. Okay, great. Thank you. Oh, I did share my repository. I'm just going through the Q&A really quick. Oh, yeah. All right, hold on. Juliana asked a question. Oh, how is it— how is AI solution architecture different than an IT architect? So AI solution architect, it is basically— I would consider it a higher level of abstraction from IT architect. So an IT architect typically is going to be looking at infrastructure like VPCs or virtual private clouds and DNS, right? And again, IT is a pretty broad term, but typically, like maybe cloud architect is another term. Uh, so each one of these types of architects tends to focus on a specific toolset. When you're brought in as an AI solution architect, typically what they're looking for is someone who's going to help them, uh, design an AI-driven solution. It might include IT components, but typically they're not looking for like, how, how do we, you know, connect, um, the IT ops systems and more how do I maybe create agents, how do I architect those agents, how do I design like MCP, A2A using platforms like Red Hat OpenShift AI to orchestrate, connect, N8N, Make.com, any other ones that I'm missing? I mean, there's tons of them, but the toolset is different. So I think that's the only difference between the two is the kind of what your— what solution you're solving for. If they're asking for an AI solution architect, it might include IT architecture, but typically they're asking for like these, how, how do I use all these AI tools to actually deliver a business outcome? So the, the experience that I would focus on is building AI solutions specifically as opposed to building like IT solutions, meaning email and passwords and things like that. Oh, you're a Chandra. You don't have to do that. You don't have to worry about that. I will be sending it to you in a thank you email right after this session. So yes, but I will, I will have to send you and I will give you my email though if you all want it. It's Noelle at Noelle. Just in case you don't see it for some reason, if you gave me a bad email, that'll teach you. All right, cool. Good, good. Thank you for that. Great question. I answered that question live. Awesome. All right, let's see what else we got here. I'm just going to keep scrolling. I'm currently in a lot of trouble with AI product development. What do I need to do today to move my product forward? Story of my life. For real. Yeah, I mean, and honestly, I will say every time I run into people who are in a product development challenge, it's usually because their scope is too big. So shrink the scope and develop. It's another principle that I have. Another law is to always focus on a minimum remarkable product. And many of you know, some of you know what that means, but minimum remarkable product, it's different than an MVP, which is, you know, like, anyone can build viability right now in the age of AI. Like, that's not special. It's not exciting. It's not even that cool. But what is cool is if you can look at your customer and find out what's one thing you could do that they would be like, this is amazing, right? But what's the smallest version of that that still generates that excitement? That's like, oh my God, this is so cool, but it's small enough that you can deliver it with excellence. And I'll give you an example. Back in the day at Amazon Alexa, we built a feature for a bank, and we went in and we were looking for a minimum remarkable product. It's where I coined the term. We were looking for a minimum remarkable product. And what we found was we actually just looked at the click trails on their website. What were the hardest things for people to do that they did the most often? So literally, we'd first look, what's the thing? What is the top 10 things that people try to do on the website? And then the second lens we looked at was how long does it— how many clicks does it take for them to do that thing? And what we uncovered was that every single day, people were looking for routing numbers. You remember, I mean, you know, bank routing numbers. Today there, some banks make it super easy to find, but back in the day, this was 10 years ago, it was very hard. It was 5 to 7 clicks in before you could get the routing number. So we decided as a minimum remarkable product, which is the first of many things you're gonna do, the first thing we did was said, why don't we create a top-level intent on Alexa? Meaning you could just put on your headphones on a little Alexa Dot, which I have around here somewhere.. And I could just say, Alexa, what's the routing number for this bank? And it would just tell you like that. And what it did is when people realize, like, they were tired of going click, click, click, click, click, click every time they needed it. Right? Now they could just be like, what's the bank? What's the routing number for Chase? What's the routing number for Bread Financial? And it would give it to them in a second. They were like, this is amazing. It wasn't boil the ocean. It wasn't the most critical thing they needed. It was just delightful enough to get us to the next use case. We ended up deploying dozens of use cases after that. I might even say hundreds, but dozens of use cases after that. But it started with that remarkability. So as a product developer, I always say shrink the scope. And then your job also as a product owner, and Reina knows this too, you could break things up and organize them. And that organization is like, that is also an important skill of a solution architect, is that the thing we sell them is the minimum remarkable product. But in our minds, we've already architected the next 19 use cases and that they are all in increasing levels of remarkableness to the customer, right? I always say I might make $50 million on an AI project with a company, but I'm gonna do it 100 grand at a time. Or if it's a small business, right? I might, you know, uh, enable a small business and it might turn into a $100,000 contract over 5 years, but it's gonna start $5,000 at a time. Like depending on the scope, you're starting with a minimum remarkable product, a small investment. They get delighted, they invest a little bit more and then a little bit more. And then over time you increment to a product that is full of features. But it's very hard to be disciplined enough to reduce the scope and be disciplined enough to learn from your customer what remarkable looks like in order to see the next day. And most, most organizations never get there. Awesome, awesome, awesome. How many hours would you estimate it takes to work through Microsoft's GitHub Materials? 5 maybe. Tilly, Tilly, you should tell me how to pronounce your name. But yes, it takes about— the way we teach it is we teach it in 5 days and it's about an hour per day, hour and a half per day. So you could do it in 1 day, like 8 hours probably, or you could do it across 5 days, or you could do it 1 hour a week for 5 weeks. Yeah. So that's for each GitHub class. That's about right. Now some of them have— so for example, the way I did it in 5 days for Agents, Agents has 10 sessions. So I do 2 sessions a day, but even then I still spend about an hour, hour and a half on, on both those topics. Your AI Leadership Institute members will have access to the architecture course. Yes, Marisol, you definitely do. Absolutely. You'll be given an invite at the end of this week to join the Maven class for next week. Absolutely, Sherry. Yay! Awesome. Yes, go do the capstone. We're absolutely— and if you don't know, we are doing a Vibathon. I mentioned it at the beginning, but if you don't remember, mark your calendars. We are going to be for— I think it's a dollar, so you have to join for a dollar. That's just so you show up. But for a dollar, you can come and vibe code for free. We are going to do a 4-hour session to teach you how to build a custom assistant that can help you achieve your goals in 2026. See what I did there, right? With the, with the thing we talked about earlier. So that's the idea is that you're going to build a custom copilot that's going to be— and it's not a Microsoft Copilot, but a custom assistant that's going to be facilitating your desire to achieve certain goals in 2026. And that's what I meant. I don't use an AI system to help me figure out what I want, but once I know what I want, I do use AI systems to help me get there, to prescribe to me the best, most efficient way to do what I want to do. And it's pretty fancy. Yay! So there's a bunch of content there at the end. Let me go up. Okay, cool. Lots of people are connecting with each other. Let's see. Oh, Chandra was curious about my NVIDIA consulting. I was just there to speak to their— they had a collection of frontier model developers and product owners. So I was with— so NVIDIA hosted Cohere, Hugging Face, XAI, Anthropic, and my job was to help them like facilitate a conversation with those leaders. So yes, cool. Aqua hire. Okay, I don't know what that means. Some of these are out of context. Oh yeah, cool, cool. Thank you. Thank you. Yeah, I mean, Joe, you had mentioned IBM sales is notorious for selling tech without grounding. I will tell you it's not— I mean, sure, IBM, but absolutely every single tech organization does this. Absolutely every— I mean, I've worked in 4 of them, and I've yet to find a sales organization that doesn't either intentionally or accidentally overpromise. And I'm of the mindset of overpromising and overdelivering. Ruth wants to help. Okay, let's go. Let's see. Yes, yes, yes. Okay, cool. I think I've answered all the questions that are in here today. What? I was Microsoft certified too. That's cool. We have that in common. Oh, what? Look at us. Look at all of us. Microsoft— I mean, WebSphere certifications back in the day. Those were good. I mean, and I will tell you, that is my goal. So one of the benefits of the AI Leadership Essentials program that I mentioned is that we are doing a certification cohort next year, which we've never done before. But you basically are gonna be able to achieve 3 AI certifications, not 3 for me, which is AI Solution Architecture, Responsible AI Leader, and Agentic AI Professional Practitioner. And maybe I just changed the name. Those 3 for me from AI Leadership Institute. But then we also are going to be doing 3 industry certifications. So we're gonna be doing certification prep for Azure AI Fundamentals, which is AI-900. We're also going to be doing, which I'm getting next week, the AWS certification for AWS has an AI Practitioner certification. So we will be— I will be getting that next week. I will be doing lots of live sessions from re:Invent. So follow me on Instagram for the play-by-play. But we'll be doing that one, and then we'll also be doing Generative AI Leader from Google. So at the end of 90 days, again, only if you join the Essentials program, but if you join the Essentials program, we have a 90-day authority cohort where you're gonna get 3 industry certifications in 90 days. Like, Let's go. That's a huge flex, like huge. I don't know that many people who have done it. And it's just a huge opportunity to share with the world, with LinkedIn, with algorithms that you have been very validated by 3 different cloud providers that you know what you're talking about. And that I think is a really big opportunity. So don't forget, you can go to the Essentials link that I shared before in order to find it. There it is. Sherilyn just shared it as well. Let's see. Yes, follow me on Instagram for the fun. Red Hat Go-To-Market. What? Oh, that's awesome. Maybe, you know, I know that team very, very well, but maybe, you know, Frank, what's his last name? I can't remember his last name. Anyway, look for Frank. He's, he's on the Go-To-Market team. Let's see. Oh, yeah. Well, hopefully you're working with Red Hat Go-To-Market on their OpenShift for AI product, because that is the bomb. Basically, it's OpenShift but allows you to do LLM Ops, but it's a totally different product run by Steven. Again, I don't know these people's last names, but you can look them up. Really, really cool. What? Oh, Marisol, I wanna be an MCSE. I never did do that. Okay. Sent you a question on school. Oh, oh, okay. I will do that. Oh, yes. Oh, yes. Okay. I could definitely do that. So this is called, uh, Marisol, really quickly, this is called ejecting. So I have to just eject your account, um, or you have to build an account. I don't know which side you're on, so I'll go to school and find out, um, that. Marcus, it's good to see you! We haven't seen you in so long. Um, I'm going— so, oh, we were just in Atlanta and we were going to invite you to hang out with us anyway. Maybe we did, I hope we did. Uh, but great to see you, Marcus, that's awesome. Um, I feel like I haven't seen you in a long time, so thanks for being here. All right, I'm just going through the rest, going through the rest of our, our Q&A. All right, uh, oh Chandra, I wish I did too. I do not control school. School is not my, my, not my platform. I'm a— I hate to say this word, no, I'm not gonna say it that way, but I am, um, I am forced to adhere to the pricing changes of school. I'm actually considering maybe moving to a new platform, um, as a result, because you're right, like It's cool, but it's not what I did. It's not how I built my school community. So anyway, so now there's a new pricing model. It's unfortunate, but that is, yeah, that's school's job, not me. So unfortunately, Circle is good. You're right. If Eve was here, she would echo you. Yeah, Circle is good. I also, there's a place called Colab, which is much more anyway engineering focused. So I'm thinking about pushing to Colab. We'll see. We'll see. I love your, your opinion though. Thank you for that. But you're right. I'm very— I'm like going with the flow because I don't have any choice. But it caused some huge ruckus when they changed the pricing model at school. I'm like, what? But anyway, but we decided to simplify it. So we've actually taken the pricing model off of school. So please, if you have not had a conversation with one of our C-suite members on what it takes to become part of our Essentials program, please feel free to do that. Because we have lots of different ways for that to happen and that to work. Let's see, we have, we have lots of different options. So lots of stuff going on. My last thing, I'm just gonna ask all of you, if you're not part of the I Love AI community, please join. Today we are launching our Thanksgiving challenge. So we're gonna ask for you to either create a video or a thoughtful post on what you are grateful for in the world of AI. And on Thanksgiving and Black Friday, we will be sharing them on social and amplifying you, your ideas, and your gratitude. So, so please stay tuned for that. That's inside the I Love AI community. Thank you all for joining me. It's so fun. I love talking about this with you all. I love hearing your perspective, hearing your lessons, your journey. I'm so grateful for all of you. If you are interested again in joining us next week, if you are part of the AI Leadership Essentials program, you get next week complimentary. If you join next week and you decide to join the AI Leadership Program afterwards for 2026, anything you spend on Maven will get automatically included in, you know, basically deducted from your balance. So huge opportunity. 2026 is the year. Solution architects are desperately needed in companies. If you want to level up, if you want to get, you know, 3 certifications from me, 3 certifications from the industry's leading cloud providers, as well as 12 masterclasses and, you know, 6 certifications. Like, this is the way to cement yourself as a leader in this space. And I'm here for it. I'm here for you. I'm here to help. And I'm just so grateful that you all were here. Yes. Happy Thanksgiving. I will see you all on Black Friday. Don't go out and shop. Come hang out with me. Build something awesome that'll save you 10 hours a week. That's the best way I can think to spend my Black Friday. I hope you'll join us. Thank you so much for being here. Thanks to all of you. And good luck and godspeed and go build something awesome. All right, we'll see y'all later. Thanks, everybody.