TITLE: AI-First Marketing: Nick Brackney on Dell's Transformative Journey

Speaker A: First off, lean into the tools. Using the tools yourself. That shouldn't be shocking as advice. The second thing is realize that what you're bringing to the table might be different than what a traditional product manager is. You're bringing domain expertise, and that's really the key. You really need to lean into that and ensure that you're taking those advantages, because that's where you're going to do better than the competition.

Speaker B: Welcome to the AI uh Edge podcast for Enterprise Marketers. Uh, a show dedicated to sharing inside strategies and experiences from a group of experts who have successfully, successfully implemented AI solutions in a large enterprise B2B software company, specifically within the context of global marketing and how that effort can connect to sales, IT product and the rest of the business. I'm Edine Porter De Leon, and I'm joined by my fellow host, Jessica Ria. Jessica, things have been changing in your world. Do tell what has been happening.

Speaker C: Hi, Adine. Good to see you. Be here today. Yeah, it's first week back to school for my children, uh, so early here in the south, but also, yes, my first week at a new company. I am now working for Veeam Software.

Speaker B: Dun dun dun Veeam Software, in a

Speaker C: new role as Director of Marketing, AI transformation, which is really exciting. I, as many of you know, have been advising marketing leaders and teams for the past year and a half or so, but really, for my own career, wanted to get back into marketing. So I'm really excited to be back with an enterprise marketing organization kind of leading from within, which is one of my big advocacy platforms. So big changes upfront, uh, lots to do, lots of people to work with, and still the champion of champions and still happy to share what I'm learning and connect with anyone in this similar role, as always. So. So, yeah.

Speaker B: Yes. So when you were in college, Jessica was, uh, Director of Marketing, AI, uh, transformation a thing.

Speaker C: No, no.

Speaker B: It's one of the many things that did not exist earlier, three or four years ago that was not even a thing. Unless you worked at, like, for a. Paul Wright, sir.

Speaker C: Yeah. Or you might have called it digital transformation, maybe.

Speaker B: Yes, you would have called it digital transformation, but that is just amazing.

Speaker C: I'm not that young either, by the

Speaker B: way, but I think it's just amazing. So congratulations, Jessica. I think that's super cool. And the whole transformation within, I think it's something that's critically necessary, especially for the context of the show and the people listen to it. So, yes, please go out, see what Jessica's doing, look her up on LinkedIn. She's going to be doing some amazing stuff and sharing that out. So check it out. All right.

Speaker C: Speaking of amazing. Yeah, right. And new roles in marketing, here's your segue.

Speaker B: See, Jessica, you always do that. Almost like we plan on this. All right, we have a special guest today who I'm super excited about. The guest is Nick Brackne, the AI Product Manager at Dell, where he's at the forefront of building AI tools specifically for Dell's marketing organization. Nick is a product marketing professional with over 20 years of experience. I actually wrote in the intro at 15, you're like, no, 20 years of experience. We're taking it in the next level. Been with dell Technologies since 2017. Prior to Dell Technologies, Nick worked extensively as a consultant for some of the leading companies in technology, ventured into the startup world with a network analytics firm in Extra Hop, and worked at Microsoft, driving the IoT focused product launches. Nick's role is, uh, fascinating. I think so. Very much so, because it didn't even exist a few years ago. Speaking of amazing, yet it's now central to how a large enterprise company like Dell is embracing an AI focused future. Nick, welcome to the show.

Speaker A: Yeah, thanks for having me.

Speaker B: We like to talk our guests up to give everyone a sense of just the scope, a lot of really cool stuff in your background and sort of like very forefronty kind of things, like just things that just didn't exist and all of a sudden floating into now. Now they exist. And what was like that, rolling into things that just. You're like, oh, no one's ever done this before. Sure, why not?

Speaker A: You know, uh, it's a lot of curiosity. I think alongside that, you got a bit of patience as well. Because sometimes I've been ahead of these things. I kid you not. I had an event a couple of years back for AIOps, and you had Mark Hamill and had Dr. Michio Kaku on for that event. And the good doctor actually said he predicted that the soft skills would become the new hard skills that people would have to learn.

Speaker C: Yes.

Speaker A: And this is before anyone had even thought of generative AI. So it keeps me, uh, moving and it keeps things fun to kind of always be out there on the bleeding edge. We talked about IoT when I was working with Windows CE, the big challenge was connectivity. These devices, in order to get to the Internet of things, needed connectivity. And so you see sometimes these technologies that get out there really quickly and people get really exuberant and excited and then they kind of hit the trough of disillusion.

Speaker B: Some of Those faster than others. It's so funny. I feel like the trough of disillusion is more about expectations than actually anything else. If everyone did not expect it to do absolutely everything that it can't do, there would be no trough. But people are prone to hyperbole.

Speaker C: And where AI literacy comes in, we always say too, the more you understand what it can and can't do, the less the, uh, dip into the trough. So, Nick, I am obsessed with your role as you know, uh, and I think we have a lot of people who are trying to figure out what their career path looks like now with AI, and a lot of people who are extremely AI forward in their mindset and thinking and what they're doing and are just thinking like, what's next and how can I apply this? So I'd love to hear more about what is your role in the day to day life and if you were to tell somebody, what is that? AI Product manager. But also how did you get into this role and what did that trajectory look like for you?

Speaker A: Yeah, it's kind of funny because my title says Product Manager. And to ask what makes a good product manager, you'd probably say someone who's really structured, spends a lot of time in JIRA and all that kind of stuff. I like to think I got lucky on this one because I think what makes me a really strong product manager is just the domain expertise. And I think this is the one thing that no one's talking about yet that they should be is everyone talks about data and the importance of data to these tools. But what I'm finding is it's the business logic that's missing. How I got very fortunate in this is probably the most valuable experience I had is while some people were sitting there getting 10 straight years of experience in a domain like say, storage. I was working at a consulting firm for about five years and seeing the variety of companies, what their marketing styles are, and then really developing this idea of speed of delivery and even trusting other people to do the work. I was told if I wanted to scale my business, I needed to start leveraging, uh, some of our more junior folks. And so I think that's really helped me be okay with leaving it to AI at times. Right. When I had these folks, you'd see some people, they'd red pen everything that they give them and just destroy people's excitement to work. And they're soul crushing. The soul crushing is yes. And so I developed the strategy that would help me scale where I said, there's three ways to do something. There's my way, there's the right way and there's the wrong way. And as long as it's the first two, I don't touch it. That's really helped me kind of embrace this and kind of looking at this and jump into AI. What's really fascinating is maybe it took me 20 years to craft this much mastery in this craft. And, you know, we always talk about Malcolm Gladwell's 10,000 hours to become an expert. And what you're seeing is AI is just really putting that to the test. And that's where it's really exciting right now, is if you have an open mind, if you can get past the blinking cursor and really just challenge yourself to be creative and to ask yourself, can AI do this? I think that's what's going to allow you to really leap forward in your career.

Speaker B: No, I think that's great. Wait one second. Jessica. I zoomed past the intro of the show structure. We got so excited. We jumped into your background. So for those of you who listen to each of our shows, standard structure, topic objectives, strategy and tactics, teams and tools, business impact, and a weekly lighting round at the end where we talk about something that just knocked our head back and we're excited about. So we're deep into the topic objectives already because we're so excited about this. Jessica, uh, take it away.

Speaker C: Yadine's like, Jessica doesn't normally take this much control, but I am fascinated, clearly, as hopefully you can all hear this role. What were you doing before this role at Dell? Uh, and then what was that segue into this becoming a permanent position?

Speaker A: Yeah, it's really funny. The last couple roles I've had at Dell, I've kind of been tapped on the shoulder like, hey, we need you over here. And so I was driving AI messaging at Dell. One of the things I always find is maybe a superpower for me. What's really helped me in my career is I really take it on like it's my business. I really internalize that. Whatever I'm doing, I really want to live it. I want to embrace it and then make it my own. And so one of the things I did the last year and a half is I created a partnership with Nvidia. We were building a educational format for organizations to think about their AI strategy. And so we call that Genai Days. We put thousands of companies through that and it was really cool. It's really kind of amazing to see Dell being on the front edge of this. I don't know if we always get the credit for being on the front edge of this. But I've been blown away by our services organization, how much they were ahead of it internally, our own usage of AI. Keep hearing from folks that were light years ahead of. And that's really exciting to see that, uh, we've really marshaled this big interest in AI both for our customers and internally to kind of move things forward.

Speaker C: So you were doing AI messaging and then what were you doing where the organization was like, we need you in this internal product build mode for marketing.

Speaker A: And that's the thing is I typically was going to wherever, like there was a fire or wherever we wanted to really move the needle. And so I think that they were looking at and they said, you've got really strong aptitude in this area. You're a strong storyteller. What if we could codify that? What if we could hard code that in and solve for everyone? And that was really an exciting moment where I can now be in service of others. And marketing, we can do things like build audiences that are actually data driven, which is shocking.

Speaker C: Licks a finger and holds it in the air. For the podcast.

Speaker B: Yes. Let's do segmentation. Yep, that segmentation seems nice.

Speaker A: Yeah. So being able to do all the best practices, getting those in there, building apps using no code interfaces, I think that's one of those things right now is you're starting to see the models get commoditized. But it's the layer that you put on top of those models that is really what's going to allow organizations to scale. That's the problem right now is adoption and getting people to embrace the tools and think through what are all the use cases I can use the tool for because there's so many.

Speaker C: Mhm.

Speaker B: I think this is a good place for us. You're heading in that strategies and tactics section of the show because this is a critical thing, especially that we preach on this show. And it's something that you put some notes in the show, the run a show doc before we started this about what is your strategy? And then there's a process conversation around that as well. And not just hey, look at where's some tools and what's some stuff and let's just throw it at people and then they'll just, oh yeah, we'll use you give everyone a marketing cursor and then they're going to create these great apps to do what? What are they doing and who's enabling them? Um, how about we get a strategy together first? I would Love your sort of take on that because you were at the forefront in your career. You've had all these really great different experience that converged on these opportunities and you're coming in the room now and you're being asked to do X, but maybe a strategy needs to be applied before X actually even takes place so that you know you're going in the right direction. I would love for you to speak to that, being on sort of the forefront in your role.

Speaker A: Yeah, I think we've done a good job at Delt, uh, with really understanding it as people, processes and technology. We set out a strategy, we focused on just a couple of use cases and marketing happened to be one of them. Before that we had something like 700 pilots underway. We spent the first year really just kicking the tires and exploring and then when we got serious about it, we centralized it. We have chief AI officer building a strategy and where I'm going with this is really thinking through feature prioritization, thinking through adoption. So one of the things that we've learned very quickly is you can have office hours that everyone can go to that won't necessarily move the needle when you have different domains that you're addressing. So field marketing for instance, has very different needs than product marketing versus comms and social.

Speaker C: Mhm.

Speaker A: And so what I'm finding is that I really have to meet the user where they are. It's a real white glove onboarding approach. It's not hanging the banner and saying mission accomplished. The thing is, even the best laid strategy, even having those processes in place, this fundamentally is going to disrupt processes. What I try to do is I try to sit down with our users, I try to make the tool work the way that they do and I try to use. They're telling me as a known good as kind of the model for what we're building. But you still run into things where a uh, new model drops, the experience changes. Even the smallest UX thing can sometimes get blown out of proportions. So it's a constant battle to make sure that we're maintaining a uh, strong net promoter score and that people are excited with the tool.

Speaker B: That's great. Taking a quick step back here. So Dell really uh, emphasizes that business first approach. I think that was embedded in what you were talking about when it comes to AI. And how does this sort of business first approach drive the teams to say we're going to do this and not that. Here's our priorities. Which workflows are we going to tackle first? Because I think that's a really Key component of what you're talking about is at the core, is with that business first approach. What does the business need to get out of it? What is the business priority? What is the strategy? How do you do that? What are we going to tackle first? Who am I going to engage with to figure out how they work so I can build the right things?

Speaker A: Yeah. I mean, sometimes it's firefighting, it's thinking who's low on engagement and making sure that maybe I bring them across the finish line. There's some things that are just so critical to our business, like the ability to generate a PowerPoint that it's something that we're always constantly interested in seeing.

Speaker B: Oh, uh, can you help me fix that, Nick? That would be great.

Speaker A: We're not there yet, unfortunately. There's some tools that are out in the wild that can do some of those. And that's where one of the phrases I coined very early on, shadow AI comes in. Very concerned about that.

Speaker B: Oh, yeah, Model sprawl.

Speaker C: And meanwhile, copilot is doing what?

Speaker B: No.

Speaker C: Oh, I'm excited. I have copilot access now, so put

Speaker B: it to the test.

Speaker C: Gathering my pov.

Speaker A: Yeah. And I think it's just about trying to figure out what are those use cases that get things sticky. We realized very early on that if you're chasing ROI all the time, it can be very difficult to justify getting into this. What's really exciting is a lot of our, uh, marketers are telling us that they're saving time, 30 minutes to an hour and a half per time that they're building something. They've also been very excited about the quality of the work, which is interesting because sometimes you worry that people are going to say, I can write this better than the machine can. But they've seen through it that them plus the machine equals. They can generate more content, they can hit new use cases. And so it's not just top down, it's also being driven from our users. Some of them are coming forward and they're surprising us with some great use cases and some great usages of the tools.

Speaker C: What's really cool about both our past at VMware and Dell is the global marketing size of it all and the different functions that we have. And we partnered a lot. So I feel like we understand the similarities in our businesses too, and where they're different. But I'm curious if you're finding if there's any specific marketing function that is more skeptical and a specific marketing function that are more attuned to wanting to dive in Are you seeing any of that at all or is it really individual?

Speaker A: It is really individual, I would say. Uh, but what's really been interesting right now is as I try to automate a lot of processes, I found that the product marketers themselves are a little more resistant. We always joke it's like a mini CEO is, uh, a product manager or product marketer. So it's like they own a product and they're using AI quite a bit. But I'm sitting here trying to create a process we can run everyone through that can take a tier one launch, let's say, and just generate the first pass of that entire asset list in a matter of minutes.

Speaker B: That's great because you talked about the bleaching, blinking cursor. But it's really great to accelerate the process of creating that first terrible draft. AI can just create the first terrible draft, which is. Humans are really great at just creating a first terrible draft. Why don't we actually just get the AI to do that and then we can actually go back and get all the SMEs together and make sure that it's actually really good.

Speaker A: And honestly, I'm finding it to be not a terrible first draft. To be honest with you. It's very good quality.

Speaker B: Mhm. Exactly.

Speaker A: And this is one of the things I ran into back in my old role when I was using the AI tool, I started using it to create the draft that I would give to a vendor because then it would be directionally where I wanted to go.

Speaker B: Exactly.

Speaker A: Even communicating that can be hard sometimes.

Speaker B: And then you've accelerate that process of getting the vendor so you're not having three meetings, which are all just scoping meetings and directional meetings and strategy meetings. So now like, hey, that three weeks collapsed into 15 minutes in an email.

Speaker C: So you talked about meeting everyone where they are, that you can't have blanket rollouts and office hours. I think that's something that we saw as well. And I think it also goes to show how much effort it takes to do this at global scale. And so I'm curious how you guys are scaling that in terms of having team meetings or office hours or individual trainings per function, region or team? Because not all vendors can even scale from that side too. So is there a team that's helping you with this or how do you guys structure this?

Speaker A: Yeah, it's kind of a hub and spoke model. I'm working with a lot of these different teams. It does take a lot of time away from say, building apps and stuff like that. But what we've been finding is that uh, it's a mixture of those centralized. Make sure we do videos for new releases of app functionality or product functionality, having the office hours, then also going to team meetings and typically one or two get started. And then what we have is we have super users who are littered throughout who are also really helpful. These are people who just naturally lean into the technology which is really great because I always make sure I take care of them. We have these things called Inspire rewards where you can do a shout out to somebody and whenever you're getting that free help from somebody who's doing something beyond the call of their job, you really want to reward them for that. So we've, we definitely have been promoting the, those folks internally as uh, role models.

Speaker C: Yes, that is one of my keys as well is finding the AI, ah enthusiasts, inspiring the AI enthusiasts and keeping them happy and motivated and rewarding them through individual means that motivate them to keep going. Do you guys have a formal marketing, AI council or guiding coalition over there that's helping you too?

Speaker A: Yeah, I would say that there's obviously the chief AI, uh, office is a big part of this but then there's so many of these teams that we have that we come together with that we are sitting down, you know, Martech and marketing and it even crosses over to sales because you're not just thinking about how am I going to generate the content, you're also having to think about how am I going to put it in the hands of your sellers. Forgets, consumed. It's a very cross functional group that we have. Sometimes there are meetings for what's the strategy around tools. Sometimes it's meetings around a specific tool that I own. Sometimes it's more strategy. Are uh, we going to evaluate say translations or image use or image creation, that sort of thing. So there's a lot of different times where we're meeting up and we're developing strategy for this.

Speaker B: There was something you mentioned too with regards to data versus business logic. And when you're talking about working with all these different teams and having different levels of conversation, how do you start weaving in to that conversation, the sources of data to be able to drive maybe some model training or rag or other things that I'm going to be building for you. Um, but also how is that conversation different within the organization about the business logic? Because a lot of the times you'll get great things that are accomplished but they're not accomplished because processes are in place and it's followed and it's replicated across various different teams. It's because you've got just a team that just happened to vibe really well and they're working together great. And they just happen to click on this one thing and now all of a sudden this really great thing and so like oh wow, they must have a great process. Actually no, they may have no process whatsoever. So do you feel like you have to be the one to kind of come in and say look at, we need the consistency in data and also business process when you're having these conversations?

Speaker A: Yeah, it's actually been trying to create the business process and a lot of times where I'm shocked. It's really funny. I heard of a company that's called Salonis and they're business process mapping and they first were trying to build the digital twin and they were struggling with that. Uh, but their customers just told them just stop here at the business process. Just doing this was enough, right? That's enough.

Speaker B: Yeah, you had me at business process.

Speaker A: But I think it's an interesting question because I'm hearing all this stuff. There's all this chatter about the bitter lesson theory where effectively if you try to train a model on how it should operate, what they found is that brute forcing it with weights or a uh, larger model will always do better than it, teaching it what the rules are and things of that nature. And I'm kind of skeptical about that. Although who knows. I'm not a data scientist.

Speaker C: Mhm.

Speaker B: Are you a parent though? Because I would imagine that I'm not. So there's a parents. If you have kids there's like a different philosophy. I just brute force.

Speaker C: This never works.

Speaker B: No it doesn't.

Speaker A: Yeah. To me it's just funny because I've had to basically educate every single person I come across about what do we mean by business logic. And what's really funny is the first group that I built an app for, they had over engineered it. It was so good, the amount of stuff that they gave me instruction wise that a single one hour recording can generate 95% the way their case study for them. And it was just because it was so baked in all of the rules and the regulations and what a known good was. And then now I'm going into other groups where they don't have anything and I'm trying to explain to them like for example an FAQ for a product launch. There's got to be like 10 questions we always need to ask. There's got to be. And I'm like, come on guys, what are those questions? Because if we get those questions, I can write those in there. And now you put a product brief in and it'll just rip the information out of the product brief and answer all 10 of those questions. And now we have a repeatable FAQ app, right? Like, it's fabulous. It's really possible to get there. But what you need is one, you need a no code interface. Because I'm not going to be out there shoving all this into a context window in Python. But I always laugh too when pickle people say, why do you need a rag when we have a large context window? And I was like, because not everyone writes code, right?

Speaker B: Not everyone does write code. They need stuff. Here's some stuff I wrote in English, which is becoming the whole new vibe coding language of the future. But I think it was really interesting. You talked about a no code interface and you also mentioned very briefly, but I think I really wanted to underscore that where, hey, look at, could you take a 60 minute interview or a 90 minute interview with someone like an SME or a customer and just take that transcript and generate all the assets that you need? I think in this case you were talking about a case study, but would be great. The no code interface was just a Google Meet or Zoom call or whatever that happened to be. And then you talked about it. You hammer out the messaging, you hammer out the priorities, the feature functions. You, you get some specs in there and then boom, you just take that output and then boom, put it into the engine and then out you get at least maybe 70, 80% of the way there after just the call.

Speaker A: I actually think video is probably the best possible data source you could use for LLMs personally. And one of those things right there I'm thinking of is, I got a funny story on that. Using multimedia and video as a source for me, I had 104 pages of PowerPoint slides. That's for four hours of those Gen AI days.

Speaker C: Now mind you, I was like, that's not a lot. That's normal.

Speaker B: Don't we all, Nick, we all have our 104 page

Speaker A: in mind you. It's not intended to be death by PowerPoint. It's intended to be, uh, here's resources. You can navigate through these slides and you can talk to different points and you can skip stuff if you've already covered it, that sort of thing. But the proof is in the pudding. I recorded myself delivering all of those slides because I really didn't want to write speaker notes. I can deliver this like the back of my Hand. But I don't want to write speaker notes. And I just told the LLM, um, you're an AI expert. Go through what I've put out there as my speaker notes. And if I've not done a great enough job explaining it, if you want to expand on it, please do and tell me what you did. And I generated the notes for all but ten slides. And I was talking with Nvidia. Uh, they were like great speaker notes and everything here.

Speaker B: Uh, that's fabulous.

Speaker A: But you know, there's like 10 slides that really didn't have good speaker notes, so I got called out for the ones I didn't use AI on.

Speaker B: Oh, wow, that's fabulous. I think I'm. So I'm putting together a bunch of decks right now. I'm. I think I'm going to do that. Just run through it a recording and then take that transcript and then just have the speaker notes generated.

Speaker C: So my former boss just told me about Whisper Flow last week. Have you guys heard of it? I don't know what the security implications are at a large enterprise, but you just push a button on your keyboard and instead of having to type through all the speaker notes for all the decks, I was trying to wrap up as resources, I just gave the presentations and it dictated them. And also it doesn't AI ify them, it just organizes them. Gidevin will put bullets and numbers as an outline. It was life changing because normally I would just sit there and type it all out and you know, it doesn't sound exactly like you. So just hot tip for anyone. But also the cool thing that you said, Nick though too was expand on it. So that's not something that this would do. That's something that you're giving freedom within the context and parameters that you've set up within the LLM to add to it, which I think is another resource to add into your speaker notes there too, which is really cool.

Speaker B: I just downloaded it.

Speaker C: Jessica, I also tagged you in this LinkedIn post, Gideon, because I was like, Gideon always has a tool for me that's either really fun or really life changing. And so, uh, you're going to love this. I'm sure you were busy and missed it. Yeah. Let me know, uh, what you think.

Speaker B: I caught your LinkedIn post for your new job though. I made sure I commented on that.

Speaker C: Thank you.

Speaker B: But yes, I think I missed the Whisper Flow one. I'm backed up, but I love that. Nick, I think we're floated into the teams and tools section of the show a lot of people get excited about this point because a lot of practical stuff like, hey, how can I get up and do this? So I think there's two pieces. One is some of the technology components. But I think one of the big things that you've underscored in your efforts in all of these things is the change management component, which is a critical thing. I'd love for you to speak about all the different interconnected pieces and how change management was critical when pretty much as you say, firefighting or creating consistency with business processes and all of those different things.

Speaker A: Yeah, I think first and foremost having good relationships across all the teams is really important. Important. We're all having to make decisions. A lot of times there can be politics involved in large organizations. I will tell you this though. Dell, more than any other place I've worked at, you have people who are more likely to help you even if it's not on their KPIs.

Speaker C: I love that.

Speaker A: Yeah, so I mean there's that. This is an old method I think I told you about when I was in Windows ce where I just went around saying, don't tell me no, just tell me what it would take.

Speaker C: Ooh, I love that.

Speaker A: And I ended up opening up, um, shared source, which was a huge problem for us because Linux obviously is open source. I opened it up to China, Taiwan, India, Russia and how I did it was effectively what I found was that there wasn't as much resistance as people assumed. I went to our lawyers, they said, honestly, I don't care, but that's not our decision. That's Big Windows. Then I go over to Big Windows and they were like, we had the same exact problem. And I go, how'd you solve that problem? And they said, well, we let them bring their code into a, uh, secure Microsoft facility. We boot up our code, they look at the two, they tweak and modify their code. They can take their code out of the building and then we're good. All of our code is safe. Just replicating that fix. That's one of the big lessons into this team is sometimes somebody else is going to have an answer. Somebody's been through this before, going in, making sure. I'm asking them as well. It's a lot of different teams we work with to really build this and get this to work and having the change management. There's communications that we have to worry about, there's corporate level communications and my tools communications. So there's a lot going on there.

Speaker B: All right. I do want to be sensitive to. We're Getting toward the end of the episode. And I wanted to make sure that you had the chance to really highlight the business impact, the success that you've had and the changes that have occurred. Because you talked about a lot of really great programs. I think the listeners would really benefit from hearing about what was the impact of that. Specifically in marketing.

Speaker A: Yeah. Our reporting shows that uh, almost any task people are doing, they're saving 30 minutes to an hour to two hours. That's been one of the biggest from people ones that we're hearing. People are saying that they love the tools. It's made it much easier for them to do their job. There has been some stuff where say we had a vendor spend that we would traditionally do. For instance, that customer evidence case study app, uh, we were able to eliminate a lot of vendors film with that.

Speaker C: Sounds familiar.

Speaker A: Yeah. And really on the other side of things is we were gated by how much money we had to spend there and now you've taken that gate away. So potentially we could do more customer evidence case studies if that team has the time and the capacity. That's been really good. There's a little funny event that occurred that showed me just how much people loved our tools, which is inheriting stuff from all these big mergers and acquisitions. We had a subset of our users who had Migrate, an email server. And when that occurred they lost their single sign on to the app and they were very vocal about it. So it was a small outage, only an hour or two.

Speaker B: Wow.

Speaker C: How you know they love it and use it, right?

Speaker B: Mhm.

Speaker A: There you go.

Speaker B: Turn it off for a little bit.

Speaker A: Sometimes you need something to give you a little bit of a. Okay. I can see how much they like it. The NPS scores we have for the tool are off the charts. I think it was 80 people or 90 people we surveyed. And this is a subset of all of our users. We need to get more participation and it was something like an NPS of 68 or something. When you think about that, that's pretty significant because you're subtracting the tractors from that big number.

Speaker B: So that's fabulous. It's great to hear all that success. Now it's probably a good time for us to head into the lightning round section of the show. I will go first. And it's something that I've mentioned before too, and I just have to keep coming back to this because you mentioned interfaces. Nick and I know we didn't go over the whole agentic thing, which is a big, big hot topic, but I think interfaces is going to be a really important thing for Agentic is how are you communicating with it. And I've used everything from cursor to Agent Force workflows. For those of you can't see me, of course, got my Agent Force T shirt on. And I've found that Voices is the most powerful for me. And we talked about video. And so if you just get on a call, like if an agent could set up a call with you, you get on the call, questions are asked, you get to just jump on a call, answer some questions that are generated, and then that transcript kicks off a workflow. How amazing would that be? And what I'm experiencing right now, and I can't remember if I mentioned it before, but Sesame is doing this amazing work. Sesame AI is doing this amazing work with verbal interfaces. Cause a lot of people right now are used to you talk to it. It goes doot, doot, doot, doot, doot. Thanks. Goes back to the server. And the latency's understandably slow because I don't know how Sesame does the latency thing, but Sesame is like talking to, like a person. Like, it is like talking to just. You can interrupt it, they'll interrupt you. THEY LAUGH it's crazy. And I think as we go through this, want something like that. My quick take for, uh, my lightning round here is just check out Sesame AI because I really feel like that voice, uh, video or meeting interfaces, that's really going to be that real killer app user interface for enterprise workflow, especially in marketing and other places. That's mine.

Speaker C: I'm happy to use Whisper Flow as my lightning round. I think the big takeaway too was that my former boss was saying, I don't type anymore. So email, Slack, text, all of it is just voice. And I think we're hearing that more and more. Even Sam Altman is saying voice is underutilized from that perspective. So I think it's going to be really interesting. I even think about kids and students a lot. Will they voice an essay? How does that work instead of typing it all out? Is that the same value? You're still able to think things. And I think there are those of us who feel like we communicate better writing and struggle more verbally because it's more on the spot. So I think it's also a really good skill to build too, in terms of just thinking through and thinking out loud and having that become your written story. So I'm really interested to follow it all.

Speaker B: No, I think that's fabulous. I was not naturally like a Good speaker. It was totally different part of my brain and I could write, but I couldn't get on and just sort of riff. One of my failing obscurities was because I need to be able to actually speak well and articulate and why don't I just get on a podcast and have that forcing function? So I love your lightning round, Jessica. Nick, what's knocked your head back lately?

Speaker A: A couple of things you guys both talked about. First off, I was thinking about education and how, uh, alums can change education. And I remember when I was growing up and we had the multiple choice, what date did this event occur? And things of that nature. I look at this technology similar to the smartphone. There's an entire generation of people who don't know what it's like to be lost.

Speaker B: Yes.

Speaker A: They always know where they're headed. They always have a GPS that could tell them where to go.

Speaker C: Oh, yeah, it's traumatizing.

Speaker A: We're walking around with something in our pocket or something on our desk that can answer any question, mind you. You have to use your logic and you have to work with the tool and make sure you ask things the right way so it doesn't hallucinate or whatever. But there's no reason for ignorance ever again. I kind of joked about we had prehistory, which is before you had writing. Then you have history, and now this is a new age. Because when you think about it, I can load up all this stuff about how I think into an LLM and you could ask it a question. And I've never thought about that question, but it would provide an answer that would approximate what I'm doing. And then the last thing, agentic is obviously something that's very concerning. And there's a lot of things. We had a whole acronym. I had to go find the PowerPoint and find it. And we came up with a mnemonic called Learns. What are the right types of activities to give over to the machines? Number one is low risk.

Speaker B: Yes.

Speaker A: Cannot put anything in there that is very problematic. If it goes wrong. I needed to basically be fault tolerant. The next one is emerging. So, you know, you've been hearing all these scientists talking about being able to use LLMs and how they found black holes to find new antibiotics and stuff like that. It's crazy. They're asking it to basically make leaps, uh, forwarded understanding of things we don't know about. Arduous. The next one. So things like my friends that are on call and they can't leave for the weekend and they have to sit there waiting for something to fail. Wouldn't it be nice if the machines could take the first hit there and they could go on with their lives? The next one was remedial. So just tasks like you talked about. Note taking. I never have to take notes ever again. Then the end was not worth it. So things we've not done so far because we didn't have enough effort or money to do it. So you can message test anything now as a marketer, using the LLM as a proxy for a customer. And then the last one is speed, which is both speed and scale. When you think about it, if I need to get something done in real time, like in 30 seconds, the machine's going to be so much faster at doing that. And then there's also the needle in the haystack problem. Literally. I could say there's no possible way I could watch every single movie Fox has ever released, but you could tell an LLM to do it. And so we came up with that whole structure for agentic. That's still a hot button issue. A lot of people trying to figure out what it is and how it's going to work. There's a lot of smoke and mirrors right now.

Speaker C: I love that. What a great, pragmatic takeaway for our audience. One last really quick thing before you leave us, Nick. What advice do you have for marketers who are looking to get into an AI product manager role? Uh, in their own companies or in another company?

Speaker A: Yeah. I would say, first off, lean into the tools. Using the tools yourself, that shouldn't be shocking as advice. The second thing is realize that what you're bringing to the table might be different than what a traditional product manager is. You're bringing domain expertise.

Speaker C: Yes.

Speaker A: And that's really the key. And so you really need to lean into that and ensure that you're taking those advantages, because that's where you're going to do better than the competition.

Speaker B: That is fabulous. I love that advice.

Speaker C: Yes.

Speaker B: Phenomenal conversation, Nick. I feel like we could have talked forever, but we've reached the end of the show, so let everyone know who's listening. Where can they find you? Where should they follow you? What are you doing out there in the world?

Speaker A: Yeah. For right now, mainly on LinkedIn. Nick Brackne. I'm quite prolific there. Somebody once introduced me to Patience Morehead and he's like, I know Nick. He's pretty prolific on LinkedIn.

Speaker B: Fabulous. That's wonderful. All right, well, Nick, thank you so much for joining the AI Edge podcast.

Speaker C: Thank you, Nick.

Speaker A: Thanks for having me.