I ❤️ AI Q&A: Redefining Human Work with Agentic AI – Building Human-AI Teams

Fingers crossed it remembered all my live streaming information. That would be amazing if it did. So welcome everyone. Oh, it looks good. What? What? What? Okay, it's going. I don't know what's happening right now, but it seems to be going, so I'm going to close it out. So welcome. This is our classic weekly, unless I'm traveling or jet lagged, but our weekly call, the I Love AI community. We invite you to join us every Friday to ask any question that you'd like, but most importantly, to get a chance to meet each other, to get a chance to get an update on me. As I was mentioning at the beginning of this call, we are right now in the beginning of our Agentic AI for Beginners course. And what that is, is it's a Maven course available for you if you would like. Maybe I will— maybe I'm going to check the chat and see. Um, hi everybody. All right, there's an otter account. Uh, there's so many. So let's see if anyone has the link to the Maven course. Maybe you could throw it in the chat for me since I am not immediately available. Um, all right, some, some small kids just came to our door, uh, so they're trying to sell stuff. I love entrepreneurs. Awesome, thank you, Sherilyn. Um, so that is in there if You would like to, um, get a discount on the course. The— it's Maven. You can actually find it pretty easily. Maven/noelle.ai or noelle.ai/agentik. Um, I'm actually— we'll, we'll also put this link. Uh, you can find it on LinkedIn as well. Um, you can ping me if you're watching this on LinkedIn and you're like, what, what is this, this cool class that's happening? You're welcome to, uh, send me a message and I will send you a link. But if you go to Maven and you find our Agentic AI for Beginners course and you want to take it, there is an opportunity to get a 50% discount. And all you have to do is type in the word Agentic in the promo code. So, oh, that's all right, Joe. Good morning to you. It's morning somewhere. It might not be, but that's too funny. But yeah, so please, if you want to join us, it's been really exciting, really fun. We are learning agentic AI. It is for beginners, no code necessary, but will you learn skills you never thought you would learn? Absolutely. But we will do it with joy, excitement. It's really fun. It's a chance to learn some of the agentic AI design patterns and use cases. So I encourage you, the, I mean, you're going to have an opportunity when you join this class to actually get like hands-on experience building agentic frameworks. We partnered with Microsoft on the content, but we are doing hands-on delivery. We also have podcasts with different leaders inside the AI Leadership Institute community talking about the topics and what they've learned, what they're implementing. So it's a really, really cool opportunity. So if you want to join us, you're absolutely— it's not too late. But right now, we are in week 1, and week 1 is all about setting up your environment to run pretty sophisticated agentic workflows. And so lots of cool stuff is happening. You know, lots of people are building GitHub repos, GitHub accounts that never had one, configuring command line Python applications. Like, it's been crazy. Super fun. So if you want to join us, please do that. Hello, Marisol. Good to see you. What's up, Yara? Nice to have you as well. And Joe and Patrick and Julia. So many of you here. So thank you for being here. Welcome to I Love AI. So I also wanted to give you a sense of where, what I've been doing this week. And I mentioned this a little bit in our previous call as well, but I started my week in Chicago. I have an amazing opportunity to speak on a stage in front of 10,000 people in August. And so this was the rehearsal week. So they flew me out to Chicago where I got a chance to rehearse, But I don't know, many of you know me, I don't really do rehearsals cuz I kind of like organically think of what to say whenever I do my presentation. It's different every time I teach it. I teach different stories, different use cases. Um, anyway, so I did my best to do a rehearsal in front of a bunch of people. It was really to give the translators, uh, cuz it will be, uh, in China. It g— it gave the translators a chance to hear the kind of things that I'll say. And so how I use the words, how I use it. And acronyms or analogies. Um, and so it gave them a, a chance to kind of hear my speech, my cadence, the kind of jokes I use and prepare for this event that's gonna happen, uh, at the end of August. So I'm super excited for that. So that's how I started my week rehearsing for this much bigger event that'll happen at the end of summer. And then, um, I went on to Work Human Live, which was really amazing, talking to HR leaders across The, some of the biggest and even smallest companies in the world, anyone who is managing human work today, a lot of them are a little concerned about like, what is happening? How is AI involved? How do we define AI workflows? This is why it dovetails nicely into the work we're doing in the Agentic AI for Beginners, because I, I truly do believe, and I believe this because I'm now seeing it at Anthropic and OpenAI and Meta. I was with some of the executives of that, those companies at RSA a couple weeks ago, maybe a week ago, week and a half ago anyway. Um, but I was at that conference and they were talking about this idea of building out an agentic org chart that complements human work, that every human will have a collection of agents that report to them. Um, and that those agents might be workflow dependent, but they also might be job dependent. So imagine if you will, getting a new job, getting hired, starting in a new company as some of my friends have done. I saw your, your, um, posts on LinkedIn announcing your new positions. Imagine the day you start, you don't just get like, you know, an onboarding buddy, which every company should have, like an onboarding AI system to tell you the best way to get onboarded, but also you get a series of AI agents, maybe 10, 15, 100. They're gonna just help you do your job better. And so when you get hired, you're instantly gonna become a leader, a manager of a bunch of AI processes. But in order for that reality to become true, I feel like the human resources organization needs to first understand what human work is gonna look like and then figure out what AI systems need to be created to complement those humans. And I think we could be pretty specific in the approach. I created a brand new framework. Y'all know me, I'm always thinking in frameworks, created a brand new framework for HR professionals that are gonna be building agentic organizations, and it's called POET, P-O-E-T. So I'm gonna share with you real quick, but I have a presentation, I could send it to you if you want. But it's called POET, and the first P stands for precision and how important it is for us to use the data we have to create customized, personalized, precise, agentic systems to complement human work. I got a chance to talk about, someone asked me a really cool question. They asked me a question about what happens in the world of neurodiversity, right? Like what happens? Like I have a son, many of you know, I have a son who has Down syndrome. And like what happens in a world where AI does all of the easy jobs or easier jobs, right? Will he ever be able to get a job? And that was the question was like, if I have a neurodiverse or cognitively impaired person, Will AI take all those jobs? And I wanted to share with you what I shared with the audience on Wednesday. I wanted to share with you this use case, this case study that exists today. You can go and look it up. But Goodwill is a company in the United States. They're in California. Goodwill is an organization I follow very closely because they employ people that have a condition like my son's condition. They employ people that have Down syndrome. They employ people with cognitive differences. And they talk about how they are Azure customers. So they're with Microsoft. They— Microsoft wrote a case study on them. So you can go and look it up. But in this case study, they talk about what they did. They didn't go in and go, oh, AI can replace this. What they realized was that they already had humans with Down syndrome that were doing this work inside warehouses. Imagine, if you will, some of us in the US have given bags of clothes, bags of, you know, toys to Goodwill. There are people in the warehouses that get these clothes, and what they used to have to do is they used to have to look at it and kind of categorize it. Toy, you know, household good, t-shirt, pants. They'd have to look at it and do this kind of mental categorization, put it in the right place, determine pricing, determine place it goes in the store or which store it goes to. What Goodwill decided to do was leverage Azure OpenAI Service, leverage Azure's computer vision services, and build an app that allowed them— and I get goosebumps just thinking about what I'm about to tell you because it's so cool— allowed these same people, regardless of their cognitive ability, to do the same work. The only difference is, is that they amplified their human ingenuity. The dream of Microsoft, right? Microsoft's mission is to, like, to improve the ingenuity of every person on the planet, to help everyone on the planet achieve more. And Goodwill was an excellent demonstration of that because they created an application that now someone who maybe has Down syndrome or autism or is on the spectrum, like, allows someone with this condition to use an app that allows them to— now they're gonna get all this stuff the same way they always did, but now they can take a picture of the thing that they just got. It's gonna help them categorize where it needs to go, help them identify pricing ranges that it needs to be. It'll say, for example, the pricing range is, you know, depending on condition, but it's the job of the human to look at it and determine what condition it's in, right? Like the human still is required, still is necessary, but now that human is equipped with a tool. And you all have heard me say AI is just a tool. It is equipped— that human is equipped with a tool that allows them to do that job more effectively and most importantly, more quickly. So as a result of doing that and empowering their workforce, which some might label as disabled, it makes— it increases their abilities and now allows them to do more in less time. As a result of this, the revenue shot up, their ability to get more of the items delivered or donated into stores, their time to store completely changed right now. They were able to deliver items from warehouse to store in, uh, I don't remember the exact data, so you'll have to go look it up. But it was like, as I read it, I was like, this is incredible. It was millions of dollars in improvement due to this amplification. And they did not fire their workforce. They did not go, oh, we don't need you anymore. They amplified their workforce. And I think this is what good leaders do. Good leaders look at an opportunity to take the humans we have. And again, that's why I talk about precise in POET. Precise is looking at the humans I have and creating very specific AI systems to complement those humans. The second letter in, in POET is O, optimize, which is another thing that, that Goodwill did. They optimized, right? They went in and they said, how do I optimize the effectiveness of this human doing the work? Not how do I replace them, not how do I make them irrelevant, how do I, you know, alleviate the needs for that person, but how do I amplify what they do by optimizing what they do? And that's what that app did. It allowed them to get optimizations in product identification, product placement, pricing. It didn't do the job completely, but it optimized the workflow. So that's O. E, y'all will know this one. E of course stands for ethics. Like Goodwill, thank goodness, right? They, they were ethical in their approach. They were ethical in their approach to solving this problem. So that means, right, that they had an opportunity. Sure. I guess if they were not the company they are, if they didn't have the core values that they had, I mean, these are their core values of employing people like this. But if they got a new leader who didn't care about that or didn't believe in that, right? It's the ethics that drives. The amplification of the humans that work for you. It's your ethics that decides whether you let a spreadsheet decide the value of a human worker. I'm just gonna say it. Things have happened this week that I am not happy with. I'm watching amazing people that have spent their whole lives at companies get laid off because the spreadsheet said that they were too expensive to keep. Um, anyway, I'm not gonna get into it, but I'm not cool with that. I wanna develop AI leaders that recognize that our opportunity, our opportunity in a poetic way is to create precise AI agentic solutions that match and cooperate and collaborate with the human to make them the most effective and most efficient at their job. So precision, optimization, ethics, right? We do this. That comes down to Jeff Goldblum, one of my favorite people. He said in Jurassic Park, right? Like, he's like, okay, so we can, right, clone dinosaurs, but should we? Right? That becomes that ethical leader's— we can do this, but should we? Is that the direction we should go? What is the right way to do this? What drives our behavior as an organization? And your core values should do that. So T, another really great word for many of you as responsible AI implementers, as AI leaders. The most important thing we can do is develop trust. And I have worked with Stanford. I went there and, and took a bunch of classes from some of their researchers. And in those classes they shared, one of the sessions I went to was all about trust. And they shared that their, their research is showing that today as you implement AI, you're gonna probably take a 30% hit on the trust someone has with your organization when they realize they're, they're interacting with AI. But everyone takes that haircut. Everybody gets that haircut that everyone's gonna be like, oh, you're using AI. I don't know about this. Everyone does that. But here was the uniqueness of that research is that they found that if you do not disclose, if you are not transparent, if you do not explain how you're using it, why you're using it, that you actually will take a 70%, up to a 70%, like a 70% cut on trust with your organization. That is pretty much non-recoverable. Right? Like if somebody doesn't trust you 70% of the time, they're not gonna buy from you. They're not gonna stay employed with you. Right? So I think that trust piece is not only a huge part of what makes us all leaders, AI leaders, is like, how do we create human trust? But then also how do we weave trustworthy behavior into the systems that we're designing? And there's lots of strategies behind this. As a matter of fact, there are strategies in every single one of these letters. But I, I think we now have a chance to change the narrative on how we design agentic systems. And it's gonna require leaders like you to go, I'm gonna build this system to amplify human work, to amplify human ingenuity, to make the humans better, faster, stronger, more profitable, more valuable to the company. As opposed to how do I create, how do I optimize for revenue or productivity. And the goal— I mean, I heard someone tell me this yesterday, that the goal from their board was to reduce headcount. And I, I just encourage organizations that are thinking about this, like, headcount is not the variable upon which you can drive success in your company. You are about to be in the age of extreme prosperity, extreme abundance. But the way that you achieve that is by amplifying more humans, not less. And as a matter of fact, hiring those humans that actually know what they do, what they're doing, that actually have experience, that's gonna get harder and harder over time. So I really think it's an opportunity to think a little bit poetically about our approach to creating organizations that collaborate with AI systems, that we are, we use the data we have to create very precise solutions that amplify humans. That we optimize existing workflows by looking at the human work and building systems that complement that, that we stay true to our ethical foundations, and that we ultimately see through a lens of trust in everything that we do. And so I, of course, came up with that. I woke up one morning 2 days ago and was like, I love this. So I share it with you, but it means something. I don't know. I don't know. I feel it. I feel it. If, if, if anything that I just said, like, resonates with you, I hope you'll let me know in the chat. Because I'm just messing around with it. Like these, I'm just learning as we go. Um, 100%. Uh, yeah. Oh, interesting, Rick. Um, so that's a good question, uh, or not a good question, but a good comment that you make about Waymo. Now I was an early, early, early user of Waymo in Phoenix, Arizona, and I thought the same way that you are commenting, that nobody's gonna use that, nobody's gonna get into that car. I don't know how many of you have seen the new Ford commercial So here's how it happens, right? I see completely full Waymos in San Francisco and Phoenix, and what I'm sure they're in other cities, but those are the two cities I've seen. They're not empty. When I look, when I look, there are people, and most of the time they're in the car doing this with their phone. Like they're taking a video, they're putting it on social. There's some crazy stories out there, but most of them are having a great time. We are in this, like I call it a chemicalization period when we go from the time before we sat in cars that had no drivers and the time where everybody's comfortable with it. That middle ground is like, uh, is this safe? Like, am I gonna die? Like, what's gonna happen? It also is a demonstration for these software systems that are running these cars. They make mistakes. But as Apple says, this is the worst it'll ever be. And it's pretty darn good right now. I think more pe— oh, so one of the things that Ford did, just to reiterate that commercial, Ford started a commercial series of commercials where all they did was get in the car with people who bought Ford cars that had autonomous driving in them. And they said, we're gonna record you. Turn it on. We're here. It's gonna be fine. Turn on autonomous driving. And you watch Jane or Bob or, you know, Steven, you know, Leticia, like you watch these people of all different types. Like all, like this neurodiverse symphony of humans do this activity of turning on autonomous driving and then you watch them like little kids go, oh my gosh, this is pretty cool. Oh my gosh. I want, oh, like they get excited. And this is what adoption looks like when you start. I mean, it was such a good idea when you start demonstrating to people not only that it's not something to be afraid of, but it actually is extremely cool. Talk about Alexa. Like Alexa, when we launched, we just went out and started talking to Alexa devices in public and having it like, I don't know if you remember, but Barnes Noble, um, uh, who was it? Uh, Best Buy, Target. One of the biggest momentum drivers that we did was we put devices on the floor in these spaces so you could just walk up and talk to this device. It didn't matter that it broke or that it wasn't really working, because in the early days it wasn't. What happened was, is people got delighted. They were like, this is so cool. And that is what was happening with these Ford commercials. And I think that's what's going to happen with, with Waymo as well. Oh, awesome. Y'all are amazing. Thank you. Thank you. Yeah, exactly. Microwaves were scary. I mean, imagine the first time someone got in an elevator where it didn't have a human shutting the door. Where there was no other human, it was just you. I mean, it's kind of like how some of us feel now when you pick the, the floor outside the elevator and you get in and you're like, I hope I picked the right floor. Like, there's no buttons inside. It's like completely autonomous. Um, yeah, I mean, this, this fear of technology, but it only happens at the beginning and then it becomes sliced bread. Then it becomes the iPhone. Like, it becomes the thing in everyone's pocket that everyone does. But we have this amazing, unique opportunity to be that generation of people that do the thing. We're the early adopters. It's so fun. I mean, I personally, anytime I try to— anytime I'm in a city with a Waymo, I try to get in it and I record the whole thing. It's super fun. So anyway, all right, cool. Thank you. Thank you for acknowledging my POET framework. I just made it up, but it felt right. You know when you say, I say lots of things that don't sound like that. I end up going, yeah, okay, no. But this one, I was like, it just felt good because it, it's very human, right? Poetry and like being creative. I don't know, it felt really, it felt really good. So really cool. Um, excuse me, I'm still getting over losing my voice. Uh, I keep talking, so it's, it's pretty good. It's like, I'd say 90% there. Um, but it's, it, it's still, I still have to rest over the weekend. Um, but pretty cool stuff. So that is I did that with WorkHuman. We are also members of the AI Leadership Institute. We are, um, a few of us have gotten together. We're working with a couple of clients on what we call the Inclusive Innovation Framework, which is literally this concept of designing for human AI experiences, right? Microsoft, for those of you who don't know, Microsoft has a toolkit called the Hacks Toolkit. And some of you know it, you could maybe put the link in the chat, but The HAX toolkit stands for Human-AI Experience, and it literally is this like overarching concept anytime you build an AI system that you'd want to start with, how are the humans and AI going to interact? And when I think about like back in the day, 1947 or whatever, when iRobot was created and three laws of robotics were defined by Asimov himself, right? Does anyone remember these three laws? Right? Like we, it was fiction, but it defined like, if I'm gonna build a robot, these are the ways that I want it to interact. And they are very human things. Like it's human AI rules. So that was back in a day where we were just imagining. Now we are here, we are building systems. So at least think about what those laws should be. What are the rules that govern the human AI experience? How are you going to design for that? There is what's called the Hacks Toolkit that allows you, and you could just Google or Perplexity, um, Hacks Toolkit for Microsoft, and it'll, it's very robust, but you at least wanna do that design for human and AI to coexist. Now, I, the reason I say that is because so many times, especially if technologists are at the helm, We kind of build first and ask about humans later. Because we're technologists, we love building, we love creating, we love designing. I love writing software that just does a thing. It is critical now when we build AI systems that we collaborate and cooperate and work directly with the humans that are gonna use it. What that also means is that we own the delegation to an AI system. We, meaning as humans, as AI leaders, as responsible AI leaders, You own, when I build an AI system, here's what the AI's gonna do and here's what the human is gonna do. You define that experience. And if you don't define it, it doesn't mean you're not doing it. It just means you're not doing it well. It's not a good, I like, it's probably not gonna be well designed. The more intentional you are in how a human is gonna interact with the AI system that you're building, the easier it will be to focus on amplifying that human's work. As opposed to giving some human an AI system you built completely separate from them. So I have a term that I use called never build— it's actually not mine, I adopted it from the accessibility world because I'm very, you know, I have a son with Down syndrome, so I'm very cognizant of that world. But they always say never build for us without us. And like the blind community, the deaf community, the Down syndrome community, they are often like Don't build me a tool if you don't have someone like me helping you design it. And that at a large scale is true for every AI system. Whoever you're building it for, they better be right next to you going, yeah, that's probably a good idea. Yeah, I'll use that. Or you will either end up having to rebuild the whole thing or it just won't work. It'll never get to market. People will never use it. Uh, let's see here. Oh, Joe. Joe's in the house. Um, oh cool, awesome. Oh yeah, yeah, Arvind Krishna. I love— we are— I'm like one-to-one connected with Arvind. Very cool. Um, I 100%. And, uh, this week, I think it was this week, was Think at IBM. I was supposed to be there, but I ended up being somewhere else instead. Um, but really, really cool. Uh, I also think that they have a strong core value-driven approach to building these systems. To be amplifying human work. People over tech. Absolutely. Some of you might know I have a whole series of what I call mindful leadership principles. It's called the 7 Virtues of Mindful Leadership. If you go to my Instagram, Noelle Russell on Instagram, you'll see it's a pinned post of the 7 virtues, and they're all good, but some of them are like clarity over velocity. People over product, health over wealth. And there's, there's nuances to what I mean by each one. But all of those I learned either by being exposed to a leader that did not share my ideals and being like, wow, that is not the way to do it. And some of them are because I saw while I was at Microsoft or Amazon, leaders that demonstrated so beautifully what it looks like to be an executive leader that cares about their people more than their products, that cares about, you know, instilling mental wellness over, you know, making a buck or productization or, you know, revenue generation. It takes special leaders to do this. But over the— over time, strategically, those products that are built with these types of leaders that embody these principles end up making more money, end up being much broader. Now, there are plenty of products that do very well that that do not do this. But it's definitely— so it's, it's not like— anyway, I won't, I won't mess with the corollary, but it does inspire me that leaders that have these principles build good things. It's not like the nice guy finishes last, that these mindful leaders do win. Um, and it's nice to follow them. Success leaves clues. And so I look at people like Arvind and people like Satya Nadella, and like, I look at them and what they're doing and how they're growing Um, and, uh, even Andy Jassy over at AWS, like there's, they struggle and they grow and some are good and some are bad. I just watch all of it cuz it's really great to follow. Like when it works, I wanna do what they're doing. I wanna follow and model what they're, what they're doing, which is why I follow Microsoft so closely because a lot of the work they're doing in implementing trustworthy AI into the fabric of how AI systems are built. Not just a checklist, not just a team, but like packages that you install into your software to ensure that it's safe, responsible, and trustworthy. Like, I couldn't agree with that more. Oh, what? That's cool. Thank you. Oh, Sherilyn, you're amazing. Um, amazing. Oh yes, of course. Um, so it is about that time. Oh yeah, right about that time. So if you are on the call, One of the benefits of joining us here on Zoom, which means you joined us at the, um, school community. So if you go to school, or you could just type in, uh, into any browser, noelle.ai, uh, as the URL, um, it'll take you to our communities that we have available. If you join us on our Zoom calls, you get to meet these amazing people. We're about to break out and spend some time together, um, contemplating organizational, like agentic AI and organizational, like how do you build an organization that's gonna use this? It's new., but I think it'd be fun to kind of talk about and hear from each other what our perspectives are on this. And so if, yes, if you go to, well, everyone, I don't know, everyone here probably is part of it, but noelle.ai, you can join us. You can be in this call next time. You do have to be approved to join. Not everybody gets in. If you are trying to sell stuff or you're a robot, I likely will not approve your participation in this community, but join us. We'd love to have you. But we spend the last 15 minutes going into a breakout, at which point I will stop the recording of our call because I think I didn't do that last time. I was like, it's just a bunch of dead air. Or maybe I could stay on and talk to you all, but we'll probably stop the recording and let everyone who's in the Zoom community get to know each other. But in light of that, maybe some of you have to leave early. Maybe some of you are shy. Also great. Joe demonstrated it just now. You could throw in your LinkedIn. And I will tell you on these calls, sometimes we get a lot of people just click and open up everyone's LinkedIn, you know, profile and look at them, read them, find out if you have anything in common, reach out to them, send them a message. Of course, connect. Yes, follow. But more importantly, like, is there a way for you to collaborate with that person or help that person? Thank you, Yara. Yeah, so Yara's in there, Joe's in there. Of course, I'm kind of in there. If you go to noelle.ai, I'm, I'm probably in there as well. Eve as well. We have such amazing people in this community. Um, so this is a great opportunity for us to kind of hang out together and get to know each other. Every week we spend a little bit of time together, just breaking out into breakout rooms. I do my best to not have you broken out with a robot. Sometimes it works, sometimes it doesn't, but I will definitely be reassigning you. But I think it's interesting, like my, my question that I am pondering right now, I'm writing a book right now on How to Build an Agentic Workforce. And it's all about the things I learned listening to the teams at Anthropic and Meta and OpenAI during the RSA conference. When I listen to them talk about how they're currently weaving in like this kind of Venn diagram of an org chart, a robotic process and a human process, and bringing those two things together. And I do think human resources is the best equipped to know the humans and how to use the POET framework to create precise solutions that make those humans more valuable to the company. I also think, you know, that part of that, once you know that building an agentic framework is like, how do you treat these agents when you build them? I will give you just a little bit to think about and something that you all can talk about when we break apart into our breakout rooms is when you have an agentic system, like an AI machine participating as a member of the team, how do you want to treat them? One thing, I think it was the— I think it was Anthropic CISO. He said something that really resonated with me where he was like, these agentic systems are not employees. They should not be treated as employees. They should not be treated as trusted at all. As a matter of fact, you should apply a zero trust kind of architecture or implementation framework when you adopt these models, which means that when that model comes into the organization, it starts participating in workflow. It gets assigned an, an email address, like, so that it can now email with you. It can be this agent, this AI system can participate in Slack, it can participate on Teams, it can send messages, it can be asked questions, but it's not gonna be treated as an employee. It's actually gonna be treated more like a, vendor, right, where you kind of trust them, but they're under guardrails. They actually have a different domain, right? So, so these are important things to think about is like, as you start to bring an AI system into your workforce and partner with them, what are things from an IT perspective that you're going to need to think about? And that's one of them is like, how do these agents show up as a trusted, like, resource? Do they show up like as an employee domain? No, I would say no, because all the CISOs that were showing up at RSA were like, don't do that. But you're gonna have to think about that. Do I create an agentic domain like agents.delta.com where all of my, you know, all of my agents have an email that says, you know, roboticprocess1@agents.delta.com, right? It's just really cool to kind of think about, expand your mind. So the, the question I present to you all as we break out into our breakout rooms, I hope you enjoyed today's session. I hope you enjoyed my little peek into the world of how human resources is changing. We're gonna stop the recording in just a few seconds, but the question I will ask you to ponder, even if it's only with yourself or with your team, if you're not in the Zoom, you won't be able to talk with each other, but I'd ask yourself like, what, what does the future of work look like? And in a world where we are definitely gonna have agents, like little AI systems doing work, How do we, how do we combine that? Like, what are your thoughts on how humans and AI systems will collaborate? Is there like a framework you're thinking about? I don't know. I just think it's worth contemplating. What does the future of work look like when you can build an AI system, a set of AI systems, hundreds, thousands of agents that'll complement humans? How do we figure that out? How do we ensure that we don't use this very framework to actually destroy society, destroy humanity, create massive unemployment? Like, how do we avoid that? Um, I think there is an answer to it. I certainly have my own ideas. Um, but would love to hear what you all think. And if you're listening to this and you have some ideas, please throw it into the chat. Um, not necessarily in our Zoom call, but if you are watching on Instagram or on Facebook or on, um, YouTube, throw it into the comments. Let us know what you think about this new world that we are entering into. We are in this moment of literally getting into the elevator and there is no human, or there are no buttons, and we're the first one to do it, and we're like, what is happening right now? So I would love your thoughts on this. I'm gonna go ahead and send us into breakout rooms. I'm going to stop our live streaming. Thank you all for joining us. If you wanna join us live, come join the I Love AI community. Be part of our amazing 1,500-person organization. Um, and you'll get to meet with each other and have really cool conversations and meet some of the most amazing people in the world. So, um, thanks for being here. We'll see you next time. All I'm doing is shutting down the livestream.