David Macias:

0:00I think they just want to know like what can you actually do? And then like I'll go into your documentation or I'll go into your demos pretty quickly, right? So don't like waste my time with like sugarcoating what you can do. Uh I think it there's this like tendency to be like, oh, like if I don't put many words on a paper or slide or whatever it is, on a messaging brief, on a web page, like it's not, you know, it's not gonna do the job. And I think that was one of the things it's just like, no, like it's it be direct.Kevin Kerner: 0:28

Kevin Kerner:

Hello everyone, this is Kevin Kerner with Tech Marketing Rewired. I reached out to David Messias because he's a product marketing pro who did some amazing work at his time at companies like Dell and MongoDB. And he even took some time off work to learn Python at one point in his career. So I thought he's the right guy to talk to when it comes to marketing to developers. Right now, a lot of teams are wrestling with AI launches, not the least of which is what's real, what's hype, and how do you tell the story when your buyer is a skeptical engineer. Dave would walk me through how he thinks about AI messaging that earns trust, what developers actually want when they evaluate a tech brand, and a few simple ways to learn what they need fast. He's also taking some time off for his next move. So I had him walk me through why he's taking a purposeful pause and the process he went through to think through the transition. If you're a product marketer or anyone who's trying to message AI to a technical buyer, this one will definitely help. And here at Mighty and True, we do this every day for tech brands. So if you're interested in learning more about Mighty and True, uh go to our site at www.mightyandrue.com. Let's get to it. This is Tech Marketing Rewired. David, welcome. How are you doing? Good. How about yourself, Kevin? Good, good. It's good to see you again. Yeah, you too. We met uh through the Tech Marketing Rewired dinner that we had here in Austin. So that was a that was a good hookup. So thanks for coming to that.

David Macias: 1:57

Yeah, thanks for having me. It was great. Great food, drinks, and great conversation.

Kevin Kerner: 2:01

So yeah, what I learned about you over the last uh month or so is that you're an artist. Pretty impressive. Like the is actually your piece of art. People that can't start listening to the audio can't see that. It's really pretty cool. Yeah, thanks. Yeah. I learned that you're uh you're a talented musician as well. So that's cool. That's right. Yeah, well, yeah, I try. But um, it's pretty amazing. Like for people that you meet that are in the tech world, like you're a marketer and product marketer, and you've done all this stuff, and then you're also a painter. Like you do have like this, like people have a creative side, or they have stuff that they do outside of the their day gig. It's just so interesting to find out all the different things.

David Macias: 2:43

Yeah, yeah. You know, you it and everybody has one. It could be writing, could be music, art. I've met I've met some who here in Austin, he's like a VP or senior director of public marketing, and he's like a part-time journalist for the Texas Stars. It's the minor league hockey team. That's cool. Up in Cedar Park near Austin. Those people are you know familiar with the region. But you know, that's his passion is hockey and riding, and so it's a very cool thing he does on the side, but it's you know, it's related to Yeah, what a cool, what a cool gig, too.

Kevin Kerner: 3:12

Yeah, I love going to those hockey games, they're awesome. So yeah. Well, I wanted to uh I wanted to get into today. We're gonna be talking about kind of the hype between AI and the reality of being a product market who's trying to scale an AI product. You've got some great experience from from your background. And then the the other thing I really want to get into with you, and I don't think it's talked about enough, is the developer community, because you've been in a company most recently that sells kind of directly to the technical buyer. So um I think they get kind of ignored to some degree sometimes. So it'd be great to get your perspective on that. But before we dig into it, I wanted to give you a chance to just give a little bit about your background, how you got to where you ended up, and then we'll get into some uh some of our discussion here.

David Macias: 3:55

Yeah, yeah, thanks. Uh yeah, yeah, I'm Dave Messias. Uh, I'm based in Austin, Texas, was out in the Bay for five years, but spent a lot of my time here in Austin as a two-time alum of UT. I've been doing product marketing for uh a little over a decade. And um, yeah, started out at Dell, spent some time at Homeway, now VRBO, part of Expedia Group. So if you live in Austin, it's pretty common. You'll meet somebody who's worked at one of those two companies. Um and then I actually took time off to do a data science boot camp back before I would say the uh AI hype cycle, back when it was kind of more talked about as data science and machine learning. Um, this was about six years ago. Did it full time, took time off from product marketing. And um, you know, I had I had marketed some products that had some, you know, ML models powering them. Um and I just wanted to learn more about what was going on under the hoods. You know, I and I had taken a couple coding classes in undergrad as well. So it was, it was a time for me to invest a little bit in myself, uh, you know, gain some technical prowess, uh, both from like a coding perspective and statistics. And I also realized, you know, a career in data science wasn't for me. So I was like, it's good to reaffirm, you know, sticking with product marketing was was best for me, but it gave me this kind of newfound passion for more, you know, technical products and technical companies. Went to a startup briefly, and then I ended up, you know, one of the one of the products we learned during our data science bootcamp was MongoDB, where I ended up. Uh to me, one of the great database options, uh, you know, developer data platform, just really a way that's great for you know storing the data that applications are built on top of that can scale, store all kinds of data, really easy for developers to work with. Um, I'm kind of getting to my sales speech already from I'm going to be again, but I spent about five years there. We grew from about 1,800 folks when I started to almost 6,000 uh recently. It's been it's really awesome to be a part of that uh growth. Product marketing team that was about eight or nine when I joined, and I think, you know, in the 30s, and then we had DevRel as a part of organizations about 50 or 60 by the time I left. Went from an individual contributor to managing a team of six and uh made a really interesting acquisition in the AI space, uh Voyage AI, one of the leaders in embedding models. And so yeah, it was just a you know, I I really enjoyed my time there. It was an inflection point in my career. And and I recently, and we can talk about this later, uh, you know, I have decided to take uh uh a little bit of an intentional break, uh, my career. There's a few reasons to went into it, but and part of the reason I'm able and lucky enough to do so is just how you know great MongaDB uh has that was for me. But yeah, I you know grew a stronger appreciation for the developer, everything you know that's put on them to build, right? So many companies are really you know can live and die by the products, the software, and even not, you know, tech first companies, right? You think about banking companies, automotive, whatever, right? They're they hire developers left and right. And so how do they help create that competitive advantage for their company? So the pressure that's put on them and also the rate of innovation for everything, all the tools and products they have to use, but then how do they keep up with it while actually doing their job and then at times dealing with other people's messes for what they're taking out? Just so much. I won't get too much into it right now, but a great appreciation for the job developers have. And um, and yeah, and so being able to talk to so many over the last several years at conferences over Zooms and customer advisory boards, all that, it's just it's just really interesting and to see what they're building and how they build it, it's it's very cool.

Kevin Kerner: 7:46

That's so interesting you that you took time off to educate yourself more on the technical side of things. I did the same thing at some point in my career where I took more of the code side, and it was so helpful because you really don't, it's very difficult to talk to a developer without actually knowing at least the basics of the technical part. So that's really did you take actual time off work or did you do that while you were working?

David Macias: 8:08

No, I I took time off. Yeah, that's great. I did a full-time course. So I was basically coding in Python every day for about four months, and then while I was kind of interviewing after that, still almost every day. But yeah, I mean, I I did and I did a few data science interviews. So I had like coding projects and all that stuff. And so I I experienced what a lot of young developers experience, which is the leap code or hacker rank um you know, interview where they they get interviewed and they're being like watched while they code and get these kind of tough problems. And I did a couple of those. It's it's pretty, you know. If you feel like doing it as a marketer, doing a case study, presenting that is you know, is stressful. Somebody watching you type in code and and then seeing if it works or doesn't work. So yeah, it's keystroke, another way to just kind of you know empathize with with your with your customer, right?

Kevin Kerner: 8:55

Yeah, that's a gosh, I can't even imagine that. Yeah, because it's hard enough to write code. And you had to back then you probably had to do it more manually. Now it's crazy what the code assistance can do for you, but it's a whole different thing. So you saw when you joined Mongo, you know, it was already a kind of a ML company to some degree, a database company, and then you then you saw this acquisition, and now you have this AI capability. So you've seen the sort of the AI hype, perhaps. I mean, you they they built a technical product and it was in uh production, etc. But there is a lot of hype in the marketplace around AI, and now you have, you know, you're still trying to build this production-ready application. From your experience as a product marketing leader, can you describe what that gap looks like between the reality of what you're trying to build to the hype that's in the marketplace? What does it look like on the ground as a marketer?

David Macias: 9:47

Yeah, I mean, that's a great question. One that, you know, I would say for the last two and a half, three years. I mean, I call arguably anybody who works in tech once open, you know, open AI came out with GPT, was it fall of 2023? Am I missing or 2022? Uh I mean, it just kind of put everybody on blast, right? Uh I would say the interesting thing, MongoDB, we really weren't, we had very little messaging around ML and AI before that. In fact, most of what we did have was kind of through uh other technical partner. Um, you know, I actually worked on some stuff where it was like MongoDB and Databricks, you know, together. You know, it was just like, you know, you store your data in MongoDB, then you kind of send it elsewhere to go through different, you know, machine learning or AI models. And, you know, quickly everybody became an AI company, right? And we had some of our competitors and call it some of the smaller competitors. I mean, MongoDB, right, was already a public company when I joined, but say like two to three hundred person companies, uh definitely more startup y. And and you know, their home pages, everybody's home pages became like just like AI washed, like right away, right? And like they were just like an AI company, an AI product. You're like your product didn't change overnight. Really what you do didn't change. And but you know, we we like anyone, you were like, well, you you kind of have to like to a certain degree, you know, you have to make sure that you don't get passed over. Somebody's looking for uh an AI ready database or something like that, right? So you still have to do some of it. And just a little anecdote there. I mean, I think it was interesting because there's a lot of these companies that then about a year, year and a half later, you kind of saw their home pages revert back to kind of what they they really were before. I mean, we did too to a degree. I mean, you still see like AI everywhere and in the, you know, the subnab, uh sub nav underproducts and and in their messaging. It just wasn't necessarily the header, right? It was like the subhead. And it was how did they attach to it? And so I think for us, it was like, well, what is it about us that actually makes us differentiating and like for people who are trying to build something with AI? Because if you think about the actual AI companies, it's most of them, it's the handful of companies who are actually build, especially in like I would say AI and kind of like Gen AI, right? Like OpenAI, Anthropic, you know, obviously Google Gemini and you know, the other Mistral out of France and you know, some of the bigger, you know, meta. But as far as like the models go, I mean, it's like everybody else. It's like, well, what do you do to enable people to build models, right? And what is your differentiating standpoint? And then you kind of start to see, like, okay, talking to customers, what are they actually building? Oh, talking to conferences, talking to analysts. But at the end of the day, it's like, how is it that like what differentiated before us before is like still differentiated in the sense that like you know, we're a great database, easy to work with, AI adds a layer of complexity. We, you know, we are still make that complexity like easier as a database company, all these things. But I think it was one of those things is like, how did you like and maybe I'm kind of jumbling my words here a little bit, but you know, get back to like what your core value prop is and how it was good for those building with those AI models and not just say like, hey, we're an AI company now. Um, and maybe it's a little bit different from MamaDB because we are enabling companies to build their AI products. And so, you know, you might think of a Glean or a Harvey, which are some of these kind of newer AI companies. And so we're kind of almost selling to those companies now how do you store your data and use it properly with these AI models? But it's this, it's this weird kind of getting caught up in the hype cycle and you know, just remembering like what is it that actually differentiates us? What is it that people come to us for, but also realizing like there's a new audience out there too. So it's it was a lot. And I would say within all of that, there was a lot of and still happening today, these kind of sub-hype cycles. An interesting point when it first came out, retrieval augmented generation, an acronym RAG, is a way that developers build apps. That was a big way that MongoDB enabled developers to build AI apps to retrieve data via vector search to augment one of these AI models with our proprietary data. And very early on, it was like, do we even attach to this phrase? Like, is it just gonna go over our customers' head? Like, I don't know. And it was one of those things that we just kind of said, like, think, I think we just gotta like put it out there, you know, see what it is. And within a month or two of enabling some of our sales folks, very quickly we realized like customers started asking us for it. And it was good that we had already started messaging that. And actually, a year and a half, two years later, people are saying, now, is Raghdended? Are these AI models like do you need a retrieved proprietary data through this other you know, form? And so that's just like a hype. It's like, is that cycle already ended? And that's one where it kind of worked out for us. We went in early, but there's all these different things. MCP, if you've heard of model context protocol recently by Incropic. I had some member on my team, they were like, I heard about this thing called ACP. I heard I saw I read this thing as developer said, and then you know, the quick thing where this person on my team had to be like, wait, is that is that real? I I don't know because I know MCP is new. And so I say like AI, right? It's kind of here to stay, obviously. But then you have all these subtrends within it, and it's really hard to keep up with those, and which one of those are real? And so you start to say, like, all right, who are the author authoritative voices in the space, right? Like you've got to know that. Who are the authoritative people within your company, you know, product managers, product owners? And even then, everybody's a little bit susceptible because it might be somebody thinks this way of doing something is the right way. And a few months later, it's it's not. And so you always kind of have to like stay attuned to everything, but it is it is hard to do that while also doing your day job. So it's fascinating.

Kevin Kerner: 15:47

That's that was that was kind of a long, a long, a long way to do with these AI hype cycles and sub-hype cycles, but no, is I I I hadn't actually thought of it that way, but you're right. Like I heard the whole RAG thing at MCP, and agents would be another term. There, there are so many things you can get I don't want to say tricked by, but you can sort of start to lean into. And even as a business owner, as an end business owner, you get to be like, oh man, this is like a really cool I better be on this thing. But um so I think that's really interesting that as a database company, you you also could get caught up in those things on the product side. Is there any way to guide is there any way you found to guide yourself through the reality of this is how we should be messaging? Was there a foundation that you always stuck on? I love the idea of going to voices that are trusted in the space. Like that sounds really good. But how do you how do you filter through all that noise? Is it your product team that helps you? Like what did you find what did you find to be not get caught up in something that you shouldn't have got caught up in as a marketer?

David Macias: 16:51

Yeah, I I would say it's speaking to customers and prospects as much as you can. You know, I think this is easier done when you're at a smaller company. You tend to have more access directly to customers or prospects. And I say prospects, you know, it's it's easy when you're saying, like, I went to Google Next earlier this year, and that was an easy way to just have I don't know, 150 conversations in you know, a couple days. Uh anywhere from people who are like, oh, basically come to me because they need support on something very like niche within mommy to me, but other people are just like, why are you guys here? What you know, what do you guys do? And you know, that whole spectrum of like experts are already in our product, or just like need the the the two-minute pitch. But also, you know, nowadays it's really easy. Like it's so many companies record their sales calls or their customer success calls.

Kevin Kerner: 17:40

Yeah.

David Macias: 17:41

And and it's all, you know, AI, you know, transcribe with AI, summarize all these things. And we we worked internally to one, basically like send all these transcriptions through AI models, see which calls would be worth listening to. So I had my team of product marketers. We made it a point over about a month and a half to listen to a hundred calls across regions, across all customers, prospects, all these things. It just all these questions that we had, uh our product managers had, other marketers had. Um so it was anything from kind of trying to like hone in on the personas, honey on like, you know, what maybe kind of partners or competitors are naturally brought up, all these things that could help all these people. But, you know, one of the things is looking at the summarizations of these transcriptions, which is great, but at the end of the day, I would tell people like actually sit there and like, you know, when you there's a five or six minute moment where that customer is explaining their technical architecture and the products they use, their stack, they're basically ultimately their problem, their use case, and what they're trying to solve and how we might be a part of it. Like, listen to that actively. Um, and I would say the same with like, you know, you know, reading some of the experts out there. It's like you can easily get, you know, a summarized version of it. And we love, we all love the sound bites and stuff. But when you find something that you you've listened to, that sound bite or you see a summarization of a of an interesting call, like go dive into it deep. Uh and once we all did that and you know, collated all our findings, it really helped us kind of just kind of guide, like, yeah, you know, we really do need to talk more about a gen tick, and not just like agents, but for us, it was like, how are we the proper memory provider, right? And that's what people wanted to know. Like, that's where a database would kind of naturally fit in, but you know, that's where we were getting traction. And so it just kind of gives this like, yeah, this isn't just something that we should we should hold back and see how this you know framework for building certain you know, agent applications plays out. It's like, no, we that's starting to that trend is already starting to to come about, and that's how we can like better understand like you know what we need to talk about. Yeah, and that that's a that's a couple of things. And I think it's so sometimes that work can be tedious, uh, or like you know, when you're caught up in Slack and whatever else and Zoom calls all day, or you're like you just you forget to do it, but it's that dedicated time to you know continually learn uh about the industry and about what's going on through your customers, uh not just like competitor websites or you know what you see on like LinkedIn feeds and things like that. Yeah. Um yeah, it's it's taking that dedicated time and setting this aside. I would say the same too for even like learning your own product and actually trying to build with it.

Kevin Kerner: 20:21

Uh for me, I don't think did you guys get any of that stuff back to the product team in terms of what you were hearing from the actual customer?

David Macias: 20:28

Oh yeah, 100%. Um, I mean, I would say a couple outputs, you know, three of the teams that we would output to mainly were like the product team, our sales enablement team, and uh, you know, our our demand generation team as well. Because it was like, all right, you know, demand gener is like kind of the personas, things like that. What, you know, or do we want to do some webinars that kind of talk about us and a certain competitor or do anything, or just kind of like what words are really highlighted the most? And for sales enablement, right, they can just take little anecdotes here and there and help with like, you know, some sellers may have not spoken to customers who talk about these things yet, but for them, it's like, oh no, there are conversations after this, they're gonna come. I better be ready for when they happen. And then for products, obviously, you know, it's good for them to, you know, they might also have their own bias because they might have a handful of conversations every few weeks, but they don't have the time to go through a hundred over the last few months. So yeah.

Kevin Kerner: 21:26

You know, interesting, it always goes back to the customer. Yeah. Like let's just listen to see what the customer. And the customers might also be stuck in somewhat of an echo chamber, too. They're hearing all the hype stuff too, but over time, it gets so much easier now with AI to be able to call through the uh all the conversations that salespeople are having, et cetera. But I also I was just talking to someone about uh how I think AI as a marketer, it should, what it should be doing for us is taking all the stuff that we don't want to do that we had to do manually and automating it so we can spend more time on the things that we want to do. And the thing that we should be doing is spending more time with the customer because they're the ones that are actually giving us stuff. But I think there is a danger in AI that as maybe newer marketers that they just go to the AI for the answer. They're not using AI to not necessarily get the land answer, but they're, you know, they're not and they're not using it to automate to talk to customers, they're just spending all their time in AI. So I think it's really important that you say you gotta figure out what the customer is actually saying.

David Macias: 22:26

Yeah, I think I think that's a great point. And it happens, I think a good way to kind of have that BS meter too is yeah, you know, ask questions to the different models about your own product or things that you know about, and then if you know, you'll see that the there's sometime a little bit inaccurate. And so you're like, all right, well, then can I trust it about some of our competitors or partners even? And so, you know. Then you have to go to their, you know, I would just say like that's when you kind of have to dive a little bit deeper and go to the go to the sources it brings up, go to your actual competitors' documentation. Not fun stuff to read, but I think in this day and age, like when you when you can get the the quick and dirty very easily, what's going to differentiate you as a as a marketer is spending that little bit of extra time or finding something that gives you that kind of edge, whether it's that like a little bit of knowledge, help you advocate for something internally, or just make your messaging and your marketing just a little bit better.

Kevin Kerner: 23:16

100%. Now you're also you're also messaging to a developer community. And what I know about developers is they can be quite skeptical. They want to be in community, they want to be in a community that knows what they're talking about. Um they they've sort of sort of smelled the marketing hype really easily, and they're and they're not willing and they're willing to tell you that it's marketing hype. Like they're very they're very vocal bunch if they see something they don't like. So what have you found messaging to the developer community that's most important to keep in mind? And what's worked for you, especially given that your product was so technical and it also had an AI component to it?

David Macias: 23:55

Yeah, there's a there's a few of us there. I would start one with like at least for like kind of the more, you know, kind of top-level messaging and marketing. I would say like, and most technical companies like MongoDB will have like a developer advocacy team or developer relations team who might write some of the more of the like very technical stuff, and they themselves tend to be actual developers. But I'd say the high level is just less is more. And what I mean by that, it's like it's on a it's on a couple levels, like less is more and being that like just be direct, like, and and two, like really gotta like you know, cut out the fluff and all the marketing speak, right? And I know that's like hard because you want to like build it up, and everybody's gonna build up what they can do a little bit more than what it actually can do, at least today. You know, you're always kind of talking about what it can do in six months or 12 months from now. But um, I think you know, just for a couple reasons. I think they just want to know like what can you actually do, and then like I'll I'll go into your documentation or I'll go into your demos pretty quickly, right? So don't like waste my time with like sugarcoating what you can do. Um yeah, and just from like a you know, I and I I experienced this a little bit more. This was you know leading some some younger product marketers who I think were uh and this isn't like a generational thing, I think it's one of things like if you're like not very far removed from the school and you're used to like almost having to like hit word counts and like you know make your your writing more interesting, that I think it there's this like tendency to be like, oh, like if I don't put many words on a paper or slide or whatever it is, on a messaging brief, on a webpage, like it's not you know, it's not gonna do the job. And I think that was one of the things just like no, like it's it be be direct. And and and you can you can almost do that internally too, right? Like you talk to any, like if you're in a meeting or you have to write a memo for any like executive, like you think they want to read through all your jargon, they don't right. So not that different from that that perspective as well. But yeah, less is more, remove the fluff, and then um lean on lean on your technical experts. Uh I mean it's good if you can you can do some of it yourself. There's some very technical product markers out there. I'm I find myself somewhere in the middle of relatively technical. I'm not a ex-developer, but uh, you know, lean on them. Uh I I yeah, I just think, yeah, for sure, developers will they'll they'll cut through the BS. They like to question you. If you're in person talking to them, they'll they'll kind of ask the questions to get to the point to where you're like you can't any longer like answer their question right, they'll keep diving in deeper and deeper. Uh and it's good. It's good uh to be pushed, to be called out.

Kevin Kerner: 26:27

Yeah. One of the things I think people struggle with too is like to get a there's still a component of marketing where there's some level of interest sparked. And so there's a there's a if you're talking to an engineer or developer, you still need to get a you still need to get the value of the idea across quickly. And then if if interested in that idea, then you have to go real deep. So would you agree with that that there's a there's a need with developers to they have to know what your product does and you have to explain it very simply, and they have to see the value in it. At the point where they see the value in it, that's when you have to you hit them with the it's kind of like the sizzle and the steak idea. So it's like you got to give them the sizzle, can't be overly, you know, overly uh verbose. But then once you get that, they're gonna want to dive into the technical documentation.

David Macias: 27:14

I I think it's a great point. I would almost say like we had this kind of issue last year with some of our events, and just like what tagline did we have at our booth and stuff. Like what because we kept hearing people be like, oh, you have like we have this long MongoDB is the developer data platform for your AI applications, or something like you know, kind of mouthy then. Somebody, I think it was like a product manager, was just like MongoDB is a vector database and so much more. And it was just like very to the point. And then this year it was kind of like MongoDB is your like memory provider for agents, like just very direct. And it's kind of like, oh, this is why you're here, and then like now I'm ready to talk to you, and let's go into the like lengthy one-on-one conversation and stuff like that. But I yeah, your point is is totally right. And so, yeah, it's a little bit of spark and just like direct, like this is this is why we're here, and this is why.

Kevin Kerner: 27:58

Yeah, it's so different than like uh you know, a SaaS platform or something. It's just it's just so it's just because you can stay at a high level with certain, like let's say Martech products or but when you start getting into the developer community, you gotta go you gotta go really deep real fast, but they're really not willing to they're not really not willing to spend any time on anything unless they know what you do. You're not gonna look at the technical documentation until they you know figure it out. So it's just such a different uh animal. I wonder if um the same thing of course, one of your main channels to market is your your own salespeople. Like you've got salespeople that need to, you know, sell this for. And I think at MongoDB you had like 2,000, was it a couple thousand salespeople? Roughly.

David Macias: 28:41

I mean, yeah, it was a pretty sales person.

Kevin Kerner: 28:43

A big big sales organization. How do you how important are they in delivering the message? And then how do you did you have any role in helping them understand how to talk to these this developer community in a in a in a at least good enough way to their got got interested in the product?

David Macias: 29:00

Yeah. Um I would say that's probably arguably like the most challenging part of being a product market at a techno company is uh I mean it's already hard enough to kind of be like, all right, I'm marketing to someone who's more tech, like effectively kind of knows my product better than I do because they like work and live in it. But then you're like, now I'm going through a salesperson who, you know, and just naturally, sales tends to turn over more than other roles, right? And so you're constantly having new people, so they have to learn the core of your product and what it does. They've maybe never worked in the technical space, database, data management, um, all these terms, and they too, right? Like I've been in these calls with relatively newer reps, and it's you know, um it could be nerve wracking talking to somebody very technical and being trying to like have an educated conversation. And so it's it's a really fine line of like, how do I give them enough to? Like have their ears perk up when they hear certain keywords, and also the ability to then ask the right questions thereafter and get to the like root of what the developer's saying and not trying to come off as like you know an expert or someone who knows everything. Yeah, just dangerous. And and and I think that's like you know, that's that's uh and I mean that's been been true for when I worked at Dell and VRB as well, but I think MongoDB has been just like really tough. And I just because we're in the data management space very related to, you know, when we acquire Voyage AI, an AI embedding company, it's like, all right, how do I now sell this, right? Like, what are embeddements? What's the differentiation between these and like the benchmarks and all this stuff? What is this benchmark acronymity and all these things? It's like, you know, take a step back, right? And really like to a degree, it's like less is Morgan. It's like all you need to know is like, you know, these three points, and if they care at all about embeddings or like have these keywords. And so it's really trying to like simplify things as much as possible.

Kevin Kerner: 30:55

Yeah. Do you think there's a do you think there's an opportunity for specialized sales teams now that AI is a specific, you know, thing? Is there a way to cordon off your sales organization to specialty because it is it can't get so technical?

David Macias: 31:12

Yeah, I would say we have oscillated some doing that back and forth. And I I definitely think there is I think when something's new, there's that definitely helps. Almost kind of like, you know, uh I've seen this around other you know, projects wherever you kind of call it a tiger team or something like that. It's like we're gonna give these people all focus on this thing to solve this problem over an indeterminate time, and they can say no to everything else, right? And kind of same with a certain group of sellers, right? It's like let's get them hyper focused. I we saw it a little bit more with our what we'd call our our solutions architects, you know, technical pre-sales, whatever you want to call it. So it's like they can then go help out with the the the account reps, the account executives and things like that. I do think that's something that you know when you just have all these different, you know, yeah, we're like a core database, but then we have these like adjacent capabilities, and and any company as they get bigger is just gonna start having that. Like, yeah, it it can't help.

Kevin Kerner: 32:03

Yeah, especially with um the all the AI capabilities and acquisitions too. So in training people that you know, maybe there's also the counter that AI is kind of everyone's job now, so you're you're still having to, you know, your core sales organization needs to learn it.

David Macias: 32:18

Well, and that's that's where I say things have oscillated because that's even within a product market team. It was like, do we have a core AI team or does this everybody work on AI?

Kevin Kerner: 32:25

Yeah, right. So it's just like anything, it goes back and forth in terms of uh, you know, SDRs reporting into marketing, or do they report into sales? It's just the the high the cycle of you know which management team do you have in place? And then you know, there's probably no right or wrong answer, but it it just goes back and forth quite a bit.

David Macias: 32:42

Yeah. I mean, I've been on product marketing teams who are in the you know, report up to product or report into marketing, and it's and both and the same companies, right?

Kevin Kerner: 32:49

And they can both work. It just depends on the the leadership, really. Yeah. Okay, so I wanted to transition a bit because I know you've uh I think it's super interesting that you had this um experience at Mongo and then you've decided to take some time off. So it's kind of an intent, you called it an intentional career break to to focus on some things that you wanted to do. So I was I think it would be helpful for other people that you know are maybe thinking about doing the same thing. What was the signal that told you that you wanted that it was time to take some sort of reset? Because you did it once before when you went into the development side, which is so you already have a pattern of this, but what told you to do it this time?

David Macias: 33:28

Yeah, I the uh the the first time too was also a little bit more, it was kind of before there was all this remote and hybrid work, and we were it was kind of a little bit more personal reasons. You're living in Austin, and then my family wanted to personal reasons move to the Bay Area. And like, while I probably could have kept my job remote, it was kind of pre all that, so it was kind of like also there was a you know, kind of a reason to also take time off at that point. But you know, I would say one thing, like it's also it had been about almost two years in the making, like two or three years. Like I think I told my my my wife, my partner, like a couple years ago, like, hey, I'm I think when I turn, you know, calling out my age here, I was like, when I turn 40, like I want to take some time off. Uh and you know, I just wanted to think about it, you know, ahead of time. Because I like I'm also cognizant too. Like right now, there's a lot of people who, you know, unfortunately, like are not working and it's not their choice, right? I've had many colleagues or people reach out to me similar situations. So I don't want to make light of the point of like I'm extremely fortunate to kind of have this opportunity and fortunate because because of how great Mongabee had been to me in prior companies as well. But also like the more time you you take to think about it ahead of time, you can also, you know, get things like financial stuff in order as well and think about it. Um, I was very fortunate enough again, Mongano B, I had a career coach for a little bit as I was kind of like a growing leader. And I did end up, you know, sharing this at one point, and what came out was like, you know, a little tip. Um it's like, what are you gonna do? And I was like, well, you know, I kind of want to paint, I kind of want to do this. I think I have some passion projects, but it was articulate very well when it was maybe two or three sentences. And it's like, you know, write a circle on it, just get a you know, a letter size page, you know, whatever. Put a circle with your name in it, draw like, I don't know, just a bunch of lines coming out from it. And on every one of those lines, you know, I don't know, 12, 13, 14, 15, write a sentence or two saying like just write it in the in the first. I will be um for me, like painting, right? I will have a piece of art hanging on a gallery wall um in like you know, Carmel, California, something like that, right? Like maybe some of it like very lofty goals, some of it more just like, you know, I will have a guitar, you know, on a stand next to my desk and play it at least three days a week, you know, things like that. Just all these kind of you know, goals, and some of them don't necessarily necessitate you know leaving your job, but it's one of those things you kind of start to like one, it got me to thinking past two or three items, you know. Yeah, and so a couple of the other things I wanted to do, and I I you know, I've been doing some. It's like I haven't had the time to actually play with a lot of these new, I call it play, say build with a lot of these new technologies, like lovable, replit, others where they you can just put in prompts and they build apps for you, right? And get back into the coding thing. So those were the couple things I wrote down. It was like now just on the art side, but uh, I want to do that. I was you know, for us where our kids are at, I was like, I want to be able to do drop off and pick up, you know, more easily and do things like that. And so uh, but being intentional about what you're gonna do with your time, and so for me, it's partially a reset, but I think it's also to a degree an investment in some ways, because like I'm actually going to be able to spend more time uh learning about the space, whereas I felt like so much of my time I'm I can just you know caught up in meetings and caught up when you're trying to actually accomplish, you know, you're hitting your okay for a quarter, whatever it is. So it's for me, it's uh it's it's kind of twofold from that perspective, a little bit of a recharge, rebalance. Like, what is it that really matters to me? What interests me? I think too, anybody who who might be in that situation might be thinking about leaving and have has that fortunate enough to have that flexibility is you know, is is the company you're trying to work at or industry, whatever, is like the products interest you're like is it a type of size of organization? One thing I've realized is like organization size does kind of matter to me. Like I kind of enjoy a little bit smaller to medium size and have a little bit more agency. And that's like totally cool. And that's a lot of people I've met. Like, once my company gets to a certain size, I kind of go to another smaller one and then I do that over and over. And and I've met people recently that they're like, I think I want to like try a completely different industry and pivot and all these things and realize that you might have to take a step down or two. But you can be intentional about that somewhat beforehand, but yeah, I think I think too, if you're thinking about any of those pivots, talk to people in those industries as much as you can and just and network as well and keep you know, I think you were meeting you at that dinner, Kevin. That was like I was lucky enough that you know, Jennifer, your partner at Minding True, reach out. We'd worked together when I had was at Dell, she was at Media, and you know, it was like, hey, let's you know keep keep meeting people, keep finding what's what's interesting to others. You might you might not know what what you'll learn and pique your interest. And so that was a few different things from a very tactical, just write stuff down. Yeah, no, as a paper, to to being intentional. But that's that's kind of been my process.

Kevin Kerner: 38:21

And yeah, I think that so it'll be super helpful for a lot of people to hear. There's another process that I've been through. It's called a primary, you you write down your primary aim or you do a similar sort of thing. Like, here's the things I want to do, and here's the things I don't want to do in life, and you put those, you get them all written down, and you try to work towards a goal, try to get towards those goals, and just something about writing them down makes it so much more real. And then you taking the couple years to to plan for it, it's really, really smart. I think that's I think a lot of people will that'll be very helpful to a lot of people to hear that. So thank you for sharing that. Very good stuff.

David Macias: 38:56

Yeah, and I think even when I kind of made the decision to do it like this year, I was still like a few months out. I mean, it was like 100%, but I had kind of already was like, I so And you kind of got to put yourself out there too if you do that.

Kevin Kerner: 39:06

So it's it's kind of the other thing is that I've learned is just forcing yourself to even I'm an introvert, so forcing yourself as an introvert to just like put yourself out there and sort of work on serendipity as a as a goal, just things that happen that wouldn't have normally happened unless you just put the pebble in the stream and see what happened. So I think that's all really, really good advice. Um well it's so good to uh to catch up with you and talk to you. Yeah, I think this was a fantastic, um, a lot of good stuff. If there's anyone that wants to reach out to you, what's the best way they can get a hold of you to uh continue the conversation?

David Macias: 39:40

Yeah, I would just say go on you know, David Messias on LinkedIn. I'm sure there's a few, but one who's been at MongaDB most recently. So cool.

Kevin Kerner: 39:47

And is there anywhere your art's gonna show up?

David Macias: 39:50

Uh if you're in Austin, actually, I'm gonna host uh the first weekend in Boston Studio Tour. Awesome. I think it's like November 8th and 9th. I should know. That's great. Where's it at? I'm actually gonna host it at my house. Uh, but you'll see the brochure if you go online and stuff, I'll be posting about it. But uh, you know, it's like anybody like different studios can host and then people can host. So I'm talking about putting yourself out there. Yeah. My family, and they're just like, really? I was like, I mean, worst thing can happen is people just like that is so awesome.

Kevin Kerner: 40:21

Okay, well, I'll have to put a link in the podcast if you have anything on it or not. I'll when I see it on LinkedIn, I'll definitely promote it. Sure, thank you. Yeah, good stuff. Way to go, man. Okay, well, it's so good to talk to you, David. I hope to catch up with you soon. Yeah, I really appreciate it, Kevin. This was fun. Thank you. Okay, see ya.