Future Proofing Business Success with Generative AI

Speaker A: Foreign. Welcome to the Everyday PM podcast. The podcast where we discuss project management principles for your everyday life. My name is Anne Campia and I'm the host and founder of the Everyday pm. And I'm so excited to welcome our very special guest, Leslie Grande, who is here to speak about future proofing business success with Generative AI. I, I love that because as everybody knows, AI is everywhere. Everyone's trying to learn about it, catch up on it, and Leslie is here to break it down for us in that space. So Leslie, for those who have not met you yet, please take a brief moment to introduce yourself to our audience.

Speaker B: Sure. Thanks for having me, Anna. I'm happy to be here. Um, I've had over a, uh, two decade career in product management dating back to early streaming media days, in the early days of the Internet. And I've led product teams that have included designers, program managers, product managers, managers and engineers for companies like Apple, Amazon, T Mobile, Best Buy and Discovery. And uh, after I retired from full time work, I wrote a book called Creative Propelling Breakthrough Ideas in the Age of Generative AI. And uh, the platform is really to help people as AI is sort of taking on more mundane tasks to explore their creativity, to understand what they bring to that partnership, and to actually create space, space with a thanks to AI for that kind of strategic and creative thinking.

Speaker A: That's, uh, incredible. Your background is, is truly amazing and I'm sure from all of those companies, big and small, that you've been able to work with, you've learned a lot about how Generative AI might fit into that business model. So I'm curious, even before I get into my first question for you, what was that moment for you where you decided, you know what, let me write this into something that can be useful for others to learn from. And so as you had mentioned, you wrote the book. Was there something that happened in your professional journey that you said, I got to go down this path, I got to share my thoughts on this topic?

Speaker B: It's a really interesting question because the answer is a little bit, uh, of a bunch of things as opposed to one real aha, uh, moment. Uh, one of them is one of the main drivers for the topic, um, before I get into sort of writing the book and delivering the book is over the years of coaching people as a leader of teams, um, I see people more than I'd like to hold back, um, because they don't think it's their role to contribute a creative idea or that in their job they're expected to be executional. And so therefore they don't leave space to solve problems creatively. And, and it's frustrating because some of the most talented people that I have, and when I say that in their job they're talented, are the least comfortable in that space of expressing themselves creatively. Um, and so when I would hire people, I started to really look for signals that they might not be that type of person, that they might actually be the type of person that sees the world from multiple perspectives or has great, uh, empathy to be able to adapt a new perspective. And so those skills started to become more important in the teams that I hired. So that's kind of the topic for me area. And I have a lot of, uh, passion, uh, about it because people get judged on performance as to whether they can think big when they want to move up in their career. But a lot of people don't feel they have permission in their job to think big. And so I want to help people sort of own that, take agency over it. The second part and the second kind of factor here is my fear that AI takes that away from people, that they feel that AI is more creative, more capable of generating ideas quickly, more useful in that way. And so not just outsourcing for productivity tasks, but outsourcing thinking. That's a real concern for me because these people are already vulnerable to not thinking they're creative, are probably the first class of people that will flock to AI to generate ideas for them. And it's not that AI shouldn't do that, but you should have agency over it. And the only way you have agency is to believe you can be creative and take that output and mold it into something purposeful and meaningful and valuable. So I think those are the two kind of factors in why the topic, the book, uh, why the book, and why how did that all convert into a book? When I, uh, you know, when I left full time work, I wasn't really sure what I was going to do with my time. And my husband kept saying, oh, you should write a book and you should write a book. And I kept thinking, I don't need to do it for myself. But if there's value in doing it, if the, if there's an audience for it, maybe then I will. And part of my product training was to actually look at the construct of writing a book. Like I was launching a product and putting, putting the sort of topics in, into a book proposal that I gave to a bunch of people who were not family but who would give me tough love, who would tell me, oh, this is Cute. It's a blog post, not a book. You know, who do you think's going to read this? Why would somebody care? And so I kept looking for that kind of negative feedback and this kind of play into our discussion, which is why I felt it's important to kind of go down this journey. I wanted somebody to tell me it was a bad idea, and I wanted to understand why it was a bad idea and I wanted to understand what, what I missed. Right. And so looking for the negative feedback was actually the most positive thing because everybody made it better and everybody told me where I could strengthen it or how can. So six months in, uh, I gave the proposal to someone who was an author with Wiley, very successful author. And I knew that person wouldn't like, want me to do it, embarrass myself, but. And so he would tell me, this is a bad idea.

Speaker A: Yeah.

Speaker B: And he said, how are you going to sell the book? And I said, well, I figured I'll do it the way they say on the website. He said, that'll never happen. He said, if I like the book, I'll pitch it to my editor and if she's interested in reading the proposal, I'll introduce you to her. And so by the time I got to that point, the product had sort of gone through all that user testing and all of the things that would help me. See, I, I asked professors at the University of Washington, I asked all sorts of people to read the book to see if it had value. And by the time I got to this person, it was very easy for him to introduce me to his publisher because it had already been formulated and I had already taken all of the risk out of it, if you will, in how it, how it showed up. And within a week she, uh, they bought the book. So I realized I was never going to do it just to self publish, to fulfill some personal need or ego need. I really wanted to actually get it to people, to help people. And so getting the publisher validation was. That was the real final moment of saying, okay, this is a thing. I should probably go, right?

Speaker A: That was brilliant, insightful, and I love the connective tissue between what you have done professionally for over two decades and how you're able to apply kind of that same framework into getting to this place with the book. That's incredible, Leslie. I love that. So, I mean, why don't we dive into creative velocity? Now, obviously you've launched all kinds of projects for these multibillion dollar companies. Um, you've seen these be either successes or failures. Now in Your book, you argue that one of your, our biggest mistakes, uh, strategically is planning failures, um, and how psychologically unwilling we are as humans to admit weakness and plan for those failure type scenarios. Right. We always want to just say this is going to be successful. We hardly ever have those conversations around what if it fails? And what does that mean? I don't know what that is about the human being in our nature to do that. But typically the conversations I've even sat in are always about this is going to be successful. No one's in the room saying, well, what's the, what's the flip side of that coin? So can you share a story maybe from one of those companies? Or it can just be kind of a trend or an overview of what you've seen throughout your professional journey where you saw this play out and um, you know, where a team's inability to imagine failure led to something that probably could have been preventable.

Speaker B: Yeah, there's a couple of uh, ah, nuggets in there. So the first thing I'll say is, uh, I think there is um, a predisposition to avoid the negative. That's just in general and failure being negative. So when we present an idea in a meeting to stakeholders or executives, um, if we get the objection, sometimes we get defensive and so we don't actually get at the root of what the objection is. And even if the objection may be flawed, the fact that there's someone there that could create a reason for us to fail is something we also navigate around like, oh, John is just a negatron and he doesn't like anything we do that isn't his idea. So we're just going to avoid talking to John. Right. That's a very common behavior. We kind of cut the people out who might create the friction because we really feel the pressure to deliver. And so we, within an organization there's a pattern that develops where uh, we don't take the objection as an opportunity to improve the idea or to strengthen the idea. We don't look at the objection as something that's meant to be supportive of the idea innately. And so we're move into a position where we deal with that objection in one of three ways. Maybe we go deeper and maybe we learn what is the source of that objective objection and address it either in our uh, delivery plan or in our feature prioritization. Right. Maybe that's one thing that we could do, but maybe there's a cultural propensity to just avoid uh, conflict. And so in a lot of consensus driven organizations People will navigate around the conflict.

Speaker A: Yeah.

Speaker B: And that's, that's so that's number two. Right. You can, you can see where I'm not going to be able to have a healthy conversation with somebody about their objectives. So I'll just navigate around it. And then the third thing that we do when we see this, in this kind of organizational tendency is that we look at the um, reason for failure as potentially, um, not worthy of our time. Like we don't dive into what that failure case would be or what would have caused it. And so we're more willing to look at that in retrospective, in a post mortem. Right. And so we spend the time evaluating what went wrong after it went wrong. But we rarely do the pre mortems to think if we failed like this, what would have happened to make us fail? And that's a behavioral, um, miss for most product teams. Right. We don't see it as an agile ceremony, uh, like postmortems are and retrospectives are. We don't go in front expecting to fail. We want to show our confidence to our teams, to our leaders. And so we don't really spend the time exploring, exploring the failure cases sometimes. And this is again another risk to not doing that. The failure case, you might decide is one in a million. But if it happens, your business shuts down.

Speaker A: Yeah.

Speaker B: M. Right. So when we think about things that have happened over the last year where certain, uh, data systems and network security systems aren't available to regular everyday businesses, they counted on those companies to deliver that. What did they plan for if they didn't? M. Maybe it's once in a blue moon that will happen, but now your business isn't operating online anymore for, until they figured out what happened. And so you are so in failure mode that you don't actually have anything you can do to recover. There is no backstop. So I think those are the reasons and the trends that, that I think that describe what you see around the, you know, the negativity in particular. I think there's also um, a reticence for people at a company to um, object in any way to something that maybe a higher authority has, has proposed. But you're closer to the ground, you're clearer about what could go wrong. And it's hard in a meeting to tell Steve Jobs that's a dumb idea. Right. Or that idea will fail for this reason. Even if you don't say it in a silly critical way like it's a dumb idea, you say here's reasons. I don't think that will work. It's hard to be the one that speaks up in that meeting. Right. And so authority, um, and I saw that happen when I was at Apple during the Steve Jobs era. Steve wanted to launch an ipod speaker that looked like a lunchbox cooler. It was big and looked nothing. The only thing about it that looked Apple like was that it was white. And there wasn't a single person in a meeting without Steve who would say it was going to sell. But nobody in a meeting with Steve would tell him, huh, Uh-huh. And he wouldn't have heard anyway. He wouldn't have listened. So they just all shut down. And sure enough, not many people remember that product ever released. Right. It failed. But it was in his case something he could just pull out of distribution quickly and it faded from memory because of the number of successes. But nobody in the room wanted to say to that authority, this is not a good idea. This is not going to sell. It's going to take up shelf space because of the size, it's going to be hard to carry because it's so cumbersome. Like, like all the reasons it might not have worked because he had more hits than misses. So people were like, maybe he does know better. And so sometimes failure happens because of a case where the authority of the idea and the person that delivered it feels like it's irrefutable.

Speaker A: Mhm, yeah, understood. And in those situations, Leslie, where I, I, I, there's kind of a subtle trend in what you've discussed, um, so far around somebody kind of losing that agency or that permission to have a say. And when we're looking at the failure, potential failures, obviously you called out the human behaviors to immediately try to justify the successes. Before you even think about that, have you, how have you navigated that in terms of, um, being a leader in the room, knowing, let's say in this speaker conversation that we're talking about, this speaker that never launched, uh, this product at Apple, um, that it probably wasn't the best decision. How do you, how do you provide that feedback? I guess I'm, um, speaking on behalf of the project managers who are probably listening to this, saying, I've been in the room, I've used the data, I've tried to talk about what this looks like from a failure standpoint, yet it didn't feel like anyone was listening to me. Is there anything at that point you would advise product managers, project managers, in terms of what you've seen, seen be effective in that type of situation?

Speaker B: Yeah, so there's uh, there's a, a couple of different techniques, but one really simple one is to take it out of the personal and the judgmental and to say, what if this doesn't happen the way you imagine it would? What could be the things that would go wrong that prevents it? Is it customer behavior? Is it distribution? Uh, problems? Like what are the things? So let's think about if one of those things doesn't go as we expect. And then it's not so much you were wrong or your predictions are as possible maybe as mine are. But what happens if both of us aren't right? What's that scenario? It's not so much about being the right person in the room or the critical person in the room, but asking a what if question that takes it out of the personal and creates that sort of what if we're all wrong about how customers are going to react to this?

Speaker A: Mhm.

Speaker B: What would that look like? What could be the, what could be the trigger of that? Have we thought about what might be something we have to plan for since nobody's ever seen this kind of speaker before? What might be the questions or problems. Right. That it raises in distribution? Or what might be the shipping issues? Or, you know, what have we not asked about as a place where we could be vulnerable? Even if what we're right is that there's a need for this and we think it will fit the market need. There are circumstances that are not always in our control and that's the way you help preach the conversation. The circumstances that you can't control are things like customer behavior.

Speaker A: Right.

Speaker B: You cannot, you know, you don't know also what could happen the day you launch in terms of some, uh, tragic event that the whole world is focused on. There could be some other scenario where what you planned isn't in your control and what happens therefore isn't what you planned. And so there's a great saying that says, um, by not, uh, planning to fail, you will fail. Right. Because the, the, the idea that, you know, failing to plan creates the case for failure.

Speaker A: Yeah.

Speaker B: And so I think it's the notion that there are things that you can't control that are beyond your, know, your knowledge. Especially, especially if you're an innovator like Steve Jobs. There are things you won't know that people will do because they won't tell you in advance because they've not seen that before.

Speaker A: Yeah.

Speaker B: And so that's the most important time to say, well, what if we were wrong about what customers will do? Or what if our assumptions are wrong? Which assumptions would hurt us the most if we are wrong. And by asking it that way you're sort of putting it on the table and letting anybody comment about it without it being a personal thing. And you do it in the light of fortifying the plan. Because if we think about these things in advance, we'll have contingencies for them. We won't be unprepared when they happen to activate the contingency.

Speaker A: Yeah, yeah, absolutely. Thank you for that insight by the way. I think uh, it gives us a little bit of a deeper layer insight into how you would navigate that situation. And now I want to take that similar scenario and pile on their. Leslie Generative AI. Right. In ah, terms of your insights into generative AI, I know right now a lot of organizations are looking at it from an operational efficiency standpoint. You know, how do we draft emails faster, how do we generate reports with automation? Um, I know in your book you coined the phrase strategic imagination in terms of repositioning how folks are looking at generative AI and the usage of that more as like a creative partner rather than just kind of doing the thinking for us in many ways. So could you walk us through what that looks like in practice and how is that differentiating from kind of at a basic level what I've seen organizations looking at AI for right now to do, which is like those basic automated tasks that operational efficiency that I described.

Speaker B: Yeah. So the thing that's so great about AI is it can do pattern recognition faster than the human brain. So if this circumstance looks like any other circumstance in any other domain, it can use that to fuel possible places where there are vulnerabilities in your plan. People who've tried to do something like this before in other fields have done, have seen this happen. Right. So there's the ability to look uh, quickly across similar but not related domain, similar situations. So a good example of this is I create a disruptive check in process. Now let me look at what happens when people try to disrupt the check in process across all the places people check in, in restaurants, in hotels, in airports. Right. The notion that there's a different kind of experience every place you go that's unique to that experience might tell you something. Right. Like what are they solving for in that unique experience. The experience is similar, it's a check in, but there are consequences that are different. Right. And so you want that assistance in terms of seeing what people have done where there isn't necessarily data about what you're doing and, but the domain may be serviced by knowledge from other Places. A really great example of this is, um, you're getting into the defense segment and one of the things that defense has really done great is at looking at nature and bioscience for how things actually work in nature. So drone swarming is by what happens when insects swarm to attack. Right. And if you look at certain things, you can actually see what happens and what goes wrong when that happens. And so now you can say, all right, I can see why it has benefit, but I also see where it has vulnerability. So let me go fix that in this sort of re evolution of nature and what I'm going to build. So that ability to look in places you're not uniquely familiar with, you don't know yourself, that's a really great way to sort of offset some potential risk. The other great way that AI works is that it can quickly look at second and third level consequences of a miss. Or what if this assumption is wrong? What are the ripple effects of that assumption being wrong? In places I might not look, I might be focused more on operational, but there could be brand ramifications for this miss. And, uh, I might focus only on the operational ones. The idea that it can look at the second and third level consequences quickly to help make sure that sometimes the first one isn't the biggest hit, it's what happens when the second and third get activated. And then in m totality it's, it's a crash, right? It's a problem. And so you want to have that ability to get to that level of thinking quickly as well. And I think that's a really useful way that generative AI can bring you back the kinds of questions, well, have you thought about this? Or what about this? Or where are the other areas? Lastly, I think it's hard, it's hard to know what uh, the opposite of an assumption could create. We assume people will do this, we assume the market will be like that. We assume, uh, the tolerance for prices in this range. And we make a lot of assumptions in, especially in innovation without a lot of data. Um, and even when we have data, data isn't always predictive of what happens in a new environment. And so being able to provide a list of assumptions and look at the opposite of those assumptions being true and what they do to the plan. Here's my plan, here are the assumptions underlying that plan. Now, what if any of these assumptions was wrong? What would be the consequence of that on my plan?

Speaker A: Right.

Speaker B: And so now you're able to sort of take all that insight quickly, right. And establish where you with the agency that you have want to focus, go deeper, understand how to build a contingency plan. So it's going to come back with all this perspective. But the human has to sort of put value on what's the most important thing to focus on, what's the one to explore and what risk you want to tolerate.

Speaker A: Yeah, I'm smiling because all these, you know, little light bulbs are going off in my head as you're speaking because we just talked about a few minutes earlier how just the human nature, the human behavior around being, uh, uh, not in the position to want to discuss failure. Then now you've laid out the layer of this is what you would do situationally if you were in the room. Then now we've added in the layer of how do you then make generative AI, um, your creative partner in this journey. Then now I'm thinking, I wonder if, Leslie, you would imagine a space or maybe you've already seen it, where folks are in a room using the data from the prompts that they've fed into the generative AI tool and are now leveraging that to placate the adverse, um, nature that humans have to talk about the negative. Have you seen anyone surface gen as if they were another stakeholder in the room and saying they are the ones talking about failure?

Speaker B: No. It's really a great question. I haven't seen it. But what I have talked to several product managers about is using that as a talking points, uh, talking points sort of memo for the conversation. So I hear your objection and I've explored it with AI and here's some thoughts that I have now in thinking about that objection. So it does two things. One is it gives the person I've been seen and heard, which from a stakeholder perspective or leader perspective is valuable. Right. To do. It shows you took them seriously. It also shows that you did it dispassionately and not just defensively because the psychological distance that Generative AI brings is really helpful in that conversation. Right. It's not saying bad idea. It's saying here's some flaws, here's some risks, here's some assumptions that aren't strong. Right. And so it takes that human dialogue from I think this is not the way to go to let's explore the reasons this could go wrong and see how realistic we think they are together. And by the way, I have contingency plans for three out of the five of them.

Speaker A: Mhm. It's brilliant.

Speaker B: And now you're, now as a product person, you're, you're Again, you're showing a level of insight that isn't just your personal knowledge, because maybe you're a more junior employer. You don't have the years of experience of the person who's provided the objection.

Speaker A: Yeah, yeah, absolutely. Gosh, Leslie, I'm going to try to prevent myself from rabbit holing down this trend, but I'm absolutely enjoying this conversation. But to kind of put the bow on this conversation around, um, uh, your book Creative Velocity, as well as, uh, the insights that you bring within, uh, the context of that, um, let's talk a little bit about big picture. So building that organizational resilience, making sure that it's not just, for example, individual project managers, who are usually the audience of the everyday pm, but you know, product managers, whomever that it goes from individual to organizational practice. Um, so you talk about, I think the term is premeditation of evils with gen AI, um, which can help in terms of organizational, cultural change and that sort of thing. So can you elaborate more on what you mean by that? And then as well as what do you think it's going to take to build that type of resilience at scale?

Speaker B: The premeditation of evils is a stoic philosophy. And one of the reasons that stoicism factors in here, and I talk about this in the book as well, is because the stoics are really about emotional regulation and not having the highs and lows that come from failures and wins and taking them all in stride and then being able to process them all with equanimity. And in an organization that accepts failure, that equanimity is part of how they do it. Right. People don't get punished for it and any more than they get rewarded only when they celebrate. And I was talking to an executive yesterday who was telling me that in his, uh, all Hands meetings, he starts with all the failures and what we've learned from them so that people doesn't. It's not that he's celebrating failure, it's that he's acknowledging it.

Speaker A: Yeah.

Speaker B: As a part of the journey. Yeah. And so that acceptance of the learning from it comes from being regulated, um, in how you react to it. So that's part of why the stoics are really good for this advice. Right. Because we all fear failure as a performance judgment and we all feel, feel fear failure as a final statement as opposed to a learning journey. So that's, that's, that's one element of it. The premeditation of evils is also based on the stoic belief that things that you don't think about or don't plan for, hit you harder if you not so much expect the worst. Uh, worried is just to worry. But if you imagine these things could happen, you build more robust and resilient plans because you expect the things that are out of your control could go wrong. And so you think about the ideas in advance of what it would take if they did. And so there's kind of three components to, to this in the book that, that I use to sort of bring it to life. The first is paradoxical thinking. What if one of your assumptions is true, but the opposite is also true?

Speaker A: Mhm.

Speaker B: Both things can be true. Creates a different dynamic than if only yours is true. Right, Right. There's a tension in both things being true, which isn't bad. Always look at bombas as profitable and, you know, charitable. Right. Those typically don't exist, so it's not bad. But if you understand what it creates when both of those exist, the uh, the assumption that you have and the its opposite can coexist, you're a little more prepared for what that dynamic will be when you enter the market or you execute the plan. Right. Because then it doesn't torpedo you that someone said, well, see, the opposite is true. Yeah, but I'm true too. And in that scenario, this is how we have to navigate that tension. Right. So it's a proactive thought about that. The second one is opposite thinking. And I love to recall the Seinfeld episode with George Costanza where he spent the whole day doing the opposite of every single thing he thought about doing.

Speaker A: I take all and any Seinfeld references. Thank you, Leslie.

Speaker B: Because that episode was so fantastic. And when they interviewed the actor who played him, uh, Jason Alexander said that people have walked up to him on the street telling them that they took that advice and, and it worked out for the better.

Speaker A: Wow.

Speaker B: And the whole concept of this is imagining every assumption is wrong. That everything that you assume to be true, um, isn't in the plan, isn't what's going to be true. And by taking the opposite of your assumptions, not that yours is true, but only the opposite is true, now you recognize how weak, how it weakens the plan. Can the plan go forward if one of these assumptions isn't true? Which assumption not being true will hurt the plan the most? Right. And so by looking at the opposite of your assumptions, you're looking at the ways that things along the way could decrement your success. Maybe it'll be successful, but maybe not as successful. Or maybe it can't be successful if this assumption is wrong. And so you kind of rank your assumptions and you see the risk in your assumptions more clearly that way. And then the last version of this is called inversion thinking. And this is where you actually imagine the worst thing that could happen is the opposite of what you want to happen. And I'll tell a personal story on this. My first career was in the film industry. I was a film major at Northwestern and I grew up in Philadelphia and I wanted to move to LA right away after college and start working in the film industry. I had no friends, no relatives, no connections, no idea how to do it. And my parents, who were educated professionals, told me it was a dumb idea and that I would fail. They were 100% sure they didn't support this idea. And when I left, they're like, good luck. Right? Like, we're not helping you because we think this is a bad idea. You made this choice. Go, go live with it.

Speaker A: Right.

Speaker B: The entire time I was in la, I thought, they can't be right. I can't let them be right. Because if they're right, then everything I want is wrong. And m, I can't believe that. So what is it going to take for me not to fail? How do I look at their scenario and what would put prove them right? Well, I couldn't pay my rent would prove them right. I couldn't afford my car because LA is a car city. You have to have a car. Right. I couldn't sustain long enough to build a career economically, not that I couldn't find a job in the film industry. And if I reset that failure state at that abstract level, which is maybe it takes a year or two to get into the film industry and I just have to buy my time and make smart choices along the way, then they won't be right because I'll have survived long enough to do that. And that actually was the biggest motivation. And within three years, I became a member of the Directors Guild of America. I ended up working with James Cameron and Brian De Palma. And I literally had no prior connections. I was not a Nepal baby. I didn't know anyone. But I navigated my way there with a different point of view because I didn't set out thinking that was the job I had to have. I just thought I needed money. And in la, if you work on a, you know, as a cater waiter or a nanny, you're probably working for people in the industry.

Speaker A: Right?

Speaker B: Right. And so putting myself out there to get jobs, even if they weren't the job Helped me make my network. And then in building my network, I was able then m. Right, to navigate to an entry level job where someone knew me and trusted my basic intelligence and skills to give me that entry level production assistant job. And then once I got that door open, it was up to me to keep working. But I started to appreciate that the effort to get in there was all mine. Not to get the final job right, but to put myself in a position to get hired.

Speaker A: Yeah.

Speaker B: And so that failure was the biggest motivation to not failing. And my parents just couldn't believe it. Like, they wouldn't believe that I actually had success. And when they asked, I said, it's because I just didn't want you to be right. I just didn't want you. And so I thought of every possible way that you could be right. And I did the opposite of that. I thought about what it would be that I would have to do so that that wouldn't happen. And so my plan was super strong and super resilient, and in retrospect, probably the only plan that would have worked.

Speaker A: Yeah, absolutely. Uh, Leslie, that story alone has been incredibly inspiring and has been transformative just for me. So if I'm being selfish amongst my audience, I've enjoyed this conversation thoroughly because now you have me thinking about things in a very different framework and light. And that's what I wanted for, for us to get together and have this conversation for and to share that with our audience. So, Leslie, thank you so much for this. Honestly, it's been incredibly insightful, thoughtful. I've learned a lot. Again, like I said, I honestly think when we're done with our conversation today, I'm gonna go about my day, George Costanza style, and try to FL on its head today, too, because I think that would just be incredibly fun to see how that would turn out for me.

Speaker B: Absolutely.

Speaker A: Uh, well, look, that will do it for our conversation today. Leslie, thank you so much for giving of your time and your expertise and just sharing some of the stories around Generative AI. Um, and as well as the book, um, which I encourage everybody to pick up. Um, so, Leslie, if folks want to continue the conversation with you, where can they find you online?

Speaker B: Well, uh, I have a website, leslie grandy.com and also a substack, so. So either of those places work and everybody's on LinkedIn, but everybody has different opinions about being on LinkedIn, so I, I, I offer the other two first.

Speaker A: I am going to take up the offer of the substack. I didn't realize that. So I will be doing that as well as soon as we're done today. So, again, thank you for joining me. I look forward to hopefully future conversations with you. This has been so much fun. Um, and for our listeners who are, uh, maybe listening in for the first time, let us know what you thought about this conversation. Let us know if there's any other topics you want us to cover on the Everyday pm. You can also subscribe to the podcast on any of your podcasting platforms, as well as drop a comment and let us know what you thought about our conversation today. Uh, so that will do it for the Everyday pm. Myself for Leslie. Thank you so much for joining us, everybody. And until next time, take care.

Speaker B: It.