How Klaviyo is Redefining B2C CRM, Services, and AI with Grant Deken, Head of Product of Klaviyo Services

Speaker A: Foreign. Welcome into another episode of Lessons in Product Management. I'm your host, John Fontenot, and today we get to speak to Grant Deakin, Head of product at Klaviyo Services. In this episode, I sit down with Grant to explore how Klaviyo is reimagining customer relationships in the B2C space. From the convergence of marketing and service to the real world implications of generative AI and product development, this conversation dives deep into the future of product management, CRM and AI driven customer experiences. Some of the topics we cover is what Klaviyo is and how it's expanding beyond marketing and customer service. The philosophy behind building stronger B2C relationships through CRM, balancing qualitative and quantitative data for better product decisions, and so much more. I know you're going to enjoy this episode and the conversation that I had with Grant. So let's get started. Hey Grant, welcome to the podcast.

Speaker B: Hey John, excited to be here. Thanks for having me on.

Speaker A: Yeah, absolutely, absolutely. So before we get started, could you, uh, give the audience a brief introduction of yourself, what you're doing today over at Klaviyo and what Klaviyo is all about?

Speaker B: Yeah, definitely. So, uh, so yeah, I'm Grant Deacon. Um, I am the head of product, uh, for Klaviyo Service here. This is a really exciting, um, new, new sort of area that, you know, Klaviyo is investing in, you know, really helping to bridge the, between, uh, between marketing and service and bringing those worlds together. So maybe just like to take a step back like on, on Klaviyo, you know, um, Klaviyo, you know, really exists to help help brands and help creators really connect and build better relationships with their customers. Right? And we do that through, you know, a really sort of, um, important kind of, uh, data sort of platform, right, which has the sort of core of Klaviyo. And so by bringing all of your data together in one place, all of your customer information, right, you can have more thoughtful int. Messaging that really resonates with folks and, and drives, drives the right outcomes, builds those better relationships which if you're a consumer business, right, you have many, many, many folks that you want to engage with. And so that's really, really critically important. Um, and so, you know, um, we've been really more on the, the marketing, um, side and you know, really known for, for email and sms and also like I mentioned, our data platform for many years. But if you think about the customer relationship, right, it's not just about the marketing messaging, it's about the whole, it's about the relationship, right? So it's about what happens before I buy, after I buy, when things are great, when things are not so great. Right? And so service is a really important part of making that whole. Um, and so we're building on that same data platform, you know, thinking about customer service, um, customer experience, you know, and the products that really matter to doing that really well. And so the team that I have is really focused on leading that across three really important areas. So we think about um, the self serve experience. You think about something like Amazon, right? We're all, you know, our buying behavior has sort of changed over the last, you know, number of years, you know, where consumers want to be more empowered. You know, we're very busy, we're on our phones all the time, right? Um, so you know, we want to be empowered to take action quickly and get on with our um, our day and make that as easy as uh, as possible. Right? Whether that's getting an order status or starting a return or you know, getting information about a product that you're interested in, sort of think about that as self service. We have a product called Customer Hub that we're building. Um, and then you know, really importantly, especially over the last few years, right, we talk about so much but the role of AI and sort of how that can help facilitate, you know, um, also just great experience I think for customers. You know, AI is getting to the point where it's not even just about you know, helping to um, you know, check an order status, which you know, which we certainly do, but it's also you know, guiding shoppers, helping them know which products are right for them based on what they're interested in. You know, really being a companion. And I think we're going to see consumer behavior change quite a bit there over in the years ahead. So we're building at sort of, you know, the uh, the intersection of service and sales and um, really owning kind of the consumer facing AI here at Klaviyo. And then of course we have um, our third sort of within this portfolio of service which is called um, our help desk. Right. So this is our sort of traditional kind of um, sort of command center, uh, you know, sort of platform for humans to orchestrate all their service processes and also deliver great service. Um, so we really think about customer Hub and AI and our um, AI agents as really that sort of frontline experience, deflecting common issues, delivering value and then really helping uh, human service agents really um, focus on the hardest problems and delivering better for customers. So, yeah, that's what we're focused on. And it's, uh, it's a really exciting time.

Speaker A: Love that, Love that. So you mentioned AI. I want to get to that in a little bit. But you also mentioned kind of the relationship piece. And I know Klaviyo is kind of at its core CRM and you hear like, relationship as part of that. Right. But a lot of times I see CRMs used very transactionally and it seems like Klaviyo is very relationship focused. So could you maybe double click on kind of the philosophy of Klaviyo and the, the drive and mission to really bring relationships back to CRM?

Speaker B: Yeah, yeah. I mean, I think you hit the nail on the head. So CRM's been around for a long time. Um, right. And certainly more in the, it's more known in the B2B context. Right. Where you've got, you know, a lot, you can throw a lot of people, you know, at sort of problems. Right. And, uh, like you said, maybe it's more transactional, just kind of like logging deals and, you know, things like that. Um, but with the sort of really exciting thing about what Klave is doing. You go to our website, it doesn't just say CRM, Right. It's, it's really. We're the only, uh, CRM built for B2C. So really thinking about what consumer brands need to deliver those better experiences at scale. Right. In that one to many context. And so from a relationship perspective, it comes back a little bit to what I was talking about. Um, just kind of walking through some of our thinking and how we're approaching service, which is, you know, you need to be thinking about the right way to engage with customers. We're all humans, right? That's like the essence of the relationship. Right. Um, and so everything, um, is about when and how to engage with somebody, you know, at any, at any given time, when, when to know to lean in, when to know to pull back. Um, you know, uh, you know, things like that we just announced like channel affinity, like understanding which channels people want to engage on. Do I prefer to chat on SMS or do I want to do everything through email or maybe web chat? Right. So it's that intelligence that I think helps make it feel more authentic, make it feel more natural. Right. And that's, I think those are really important parts of a, you know, a relationship not being transactional. Um, and then of course, transactions so are a part of the relationship that someone has with a brand. And so how do you make that a great Experience, um, because we want to obviously, um, you know, drive outcomes, you know, drive um, you know, drive purchases, drive ROI for our uh, you know, 170,000 customers, right, that are building great businesses. So it's really, I think the essence of doing all that well is like really hard. And I think that's, that's sort of what Klaviyo thrives at is like how to bring all that together.

Speaker A: Yeah, that's awesome and, and really cool that you kind of own that, that position in the market where it's like you are the go to for uh, B2C CRM. And it's interesting right, because I've talked to a lot of product people across B2B. B2C outside of my business path to product. I've been in B2B my entire career. And um, one of the things that I think is interesting is kind of the debate of like what do you emphasize? Is it quantitative data, is it qualitative data? And I'm curious like what from your perspective, like, because Klaviyo is like B2B 2C right? Like you help brands work with their, their consumers or their customers. Like how do you balance that, um, like for, for yourself as Klaviyo and then uh, for your customers too to like have maybe the, the analytics but also have the qualitative insights to be able to improve.

Speaker B: So it's such a good question. It reminds me actually of one of the, the keynote speakers. Um, I think it was Rory Sutherland. At our K London events we had about, I think we had like a thousand, thousand twelve hundred people come out, um, for our, for our, you know, sort of big event in London. Um, it was uh, it was really exciting. We announced, announced a bunch of stuff and we're doing another big event here in September here in Boston called K Boss. Um, and he, he had a really interesting perspective. I think in the age of data and the age of you know, AI and having access to all this information like can, can easily, easily be lost where people you know, are really over rotated on the hard results. The data driven, right? Like everything has to be super efficient. Um, and if you're only in that lane, you sort of uh, sacrifice the sort of the innovation, the creativity to being comfortable, failing and trying new things. And that's where like when you think about like the massive breakthroughs, whether that's you know, on revenue or a new product or like a new way of thinking or new framework like that, that's where that stuff happens. Um, but you have to allow for, you have to allow for that margin of error, to be comfortable with that and to exist and you know, to facilitate that. So uh, you just, when you ask that question, you made me think about that. And I think it's something like every uh, business, you know, struggles with. I think every PM has to think about. Right. Um, and uh, and I think it's a very, it's uh, very like timely sort of, uh, points in like in sort of where, where we are today, um, in business. Um, but for how, how, you know, I think we think about it and how we sort of like want to empower brands to think about it is giving them the tools to make those decisions. So it's really up to them to think about, you know, what, what they want to test, what they want to do. But they need the, they need the tools, they need the visibility to be able to action on those things and have those. So really it's like feedback loops, right? Like how do you have great feedback loops? The same in product, right. Like how we have. How do we get those like early feedback loops, right, to understand like, is this idea working or not? And how do we get that signal as early as possible so we can course correct. And I think that's where, you know, Klaviy has done a really great job is, you know, giving brands that visibility, you know, attribution certainly, you know, one of them. But being able to, you know, very easily ab test all of your work, right? Like a b test all your subject lines, you know, generate two versions of creative. You know, we're doing a lot more around AI to sort of like make that as easy as possible on um, you know, on email marketers and brand managers and lifecycle marketers, right, to just move faster, um, take more of those creative risks and. But then also have the hard data to reinforce, you know, is it working or not. So you have to, you have to kind of bring them together I think to do really well there.

Speaker A: Absolutely. It's kind of like this uh, virtuous cycle of feedback like you mentioned, like a feedback loop where it's qualitative and forces quantitative and vice versa.

Speaker B: 100%. It's really well said.

Speaker A: Awesome. Cool. So I do want to jump into the AI stuff and how that's impacting Klaviyo today. But I have one more, one more question for you personally. So in your career you've started businesses, you've sold businesses, you've been in marketing, you've been in product. I'm curious as like a co founder, as a marketer and A product person. How are those different experiences shaped your philosophy, uh, that you've taken into Klaviyo and in your career for product building?

Speaker B: Yeah, it's a great question. Um, there's a lot. I think, I think that. So I'll kind of. This, this could be a whole sort of episode in my take. But um, I'll focus on sort of two things here that I think could be interesting. Um, I think the first is around starting something. Um, when you start something, you know, you have no customers, nobody knows you are, nobody cares who you are. Right. Like, it's really, it's very nebulous and it's all on you. And so there's an extreme sort of ownership that comes with, with starting something. Nobody, um, is going to tell you what to do. Nobody's gonna steer you. Right. Um, one of the things that's so interesting about being a CEO, I think of, you know, many, uh, um, sizes of companies as most CEOs, like these are typically like, they don't get a lot of feedback. You know, maybe you get it forward like once, you know, quarterly or like ad hoc. But it's a little different than a lot of us are used to getting regular feedback, right, like from, you know, from our boss or whatever. Um, and so it can be like, you know, it's really on you a lot of times to, to figure out. The reason I'm saying that is because when you, when you go and do something, whether it's a side project or you, you know, you know, work on something for like, you know, maybe a community organization you're involved in or whatever, when you take something on, you go do something entrepreneurial, um, you know, you really just figure it out. And I think having to figure something out and, and knowing that no one's going to do it for you, I think is a very valuable skill, um, in today's world for thriving, you know, in um, in any sort of environment, you know, the more you can kind of take things on and drive, um, you know, we have a value here that sort of drivers wanted. You know, I think that's, that's a really critical thing to be successful and take on, I think hard problems. The harder the problem though, the more typically like the more nebulous it is. Like the m. Like at least less understood it is. And so like, if you want to solve hard problems, like you have to be able to jump in and, and just figure it out. Um, and so from a. That's really like putting my kind of co founder, like entrepreneurial Hat on. And you know, for folks listening, you know, I think it's a, it's just sort of a great way to get um, to challenge yourself and to learn. And it doesn't mean you have to, you know, quit your job and go start a startup. You know, that certainly some people are going to do that. But there are lots of ways to get into like build like, you know, more like entrepreneurial muscle that I think will translate really well for folks, um, looking to advance their career. The second thing is, um, you mentioned like versus marketing, um, when you're also. When you're in a, uh, sort of startup, you're also thinking about finance and HR and ops, uh, and design and just like strategy. Right. And all the things. Um, and then even more professionally. You know, in my last role I ran a lot of sort of like go to market. So it was like growth and marketing and some strategy and some corp does stuff. Um, and so I think the more exposure you get, very big companies do this too. They have these like rotational programs where like, you know, you'll do MBA and then you'll go, go to like, you know, General Electric or something, or General Mills and you'll like go around all the different like, sort of areas kind of like get. And the, the reason that I think people do that, I think it's. And, and why I think sort um, of experiences I've had, uh, have been really great for me is that you just have so much more understanding and empathy, uh, for working with other folks. Um, and you can never by the way, going back to the hard problem thing, you can never do that uh, like by yourself. Right. Every hard problem requires lots of people, diversity of thinking, you know, different teams. Right? And so the ability to understand where those teams are coming from, to be able to collaborate with them productively, to move fast, um, I think is tremendously helpful. So I would um, I would always say if you have an opportunity to do a rotational, even if it's maybe not the dream sort of role that you would want to be, but you can go get some experience. You know, hey, I want to understand like what is marketing like, um, you know, or even just like, you know, doing some finance work or working on an M and a deal, you know, like just going, pulling numbers and like that kind of stuff just like gives you perspective that other folks won't have. And I think, I think that um, it's really important the more cross especially I know we're gonna get into a, in a second, but like in a world where AI can do a lot for you. I think being able to cross disciplinary and being able to apply thinking in different ways to different areas is really valuable.

Speaker A: Yeah, I agree. I've seen a lot of negative connotations, a lot of negative conversation around stakeholder management. And I, I think to your point, like we should think about it like stakeholder partnership and the best way partners to build more cross functional competencies and empathy. So that way we can be more effective in um, you know, helping other departments help us make our product successful. Because to your point, again, we can't do it on our own. We need a whole organizational engine to make our products successful.

Speaker B: Yeah, 100% you need, yeah, you need finance, you need, you know, billing folks, you need engineering, you need design, you know, you need ops. Like it's uh, it takes village.

Speaker A: For sure. For sure. All right, so we've touched on AI a lot. So I want to give you the floor and um, just kind of share like how is Genai and this whole machine learning revolution LLMs impacting Klaviyo as a business? How are you taking advantage of it? How uh, do you think about it?

Speaker B: Yeah, I mean this is certainly not unique to Klaviyo. Right. Everybody is thinking about this. Um, and I think it's a, I post a lot on LinkedIn, just like little different kind of thoughts of the day as we're, we're digging in on this stuff. And usually the end of every one of those posts, I don't always write it, but I always think it. At least it's like, man, it's such a cool time to be building um, at least in my career. Like, you know, I, I want to get to the root of your question, but I just want to share this like quick anecdote. I just was very exciting. For me, this is like maybe, I don't know, like maybe four or five months ago. I like fired up, lovable for the first time. Um, which is like you know, v0 or replay, right. You can make prototype, you know, real working um, sort of products very quickly. Uh, and I was just so floored by what I could do and you know, and 30 minutes or whatever. I, you know, essentially had a working app. I had a back end wired into it as texting. My friend. I'm like, you know, um, for me, you know, growing up as a kid, like there's, there's only like a few moments that were as cool as that. That was certainly one of them. The other was like, was like when I got high speed Internet in my house you know, uh, you know, like, it was like, they're just maybe the iPhone, right? Like, there just aren't that many moments where like, there's like a huge shift just like across the board and like how we think about technology, um, and the impact of it. And this is like, for sure one of them. So every company, um, is sort of like working through this. Uh, and there's some really, I think, exciting things. There are challenging things. Um, so I have a kind of unique perspective because we're building AI products. Um, uh, we're also thinking about how do we, you know, not just me, many others at Clover think how do we bring sort of more AI thinking into just like, how we build non AI products, right? Like, how do we just go faster and like, how do we use this stuff? Um, I think a lot of people are figuring it out. Uh, you know, there's. There's like, you know, it's. And I think the rules, frankly, are like, you know, being rewritten every. Every six months with. As models evolve and new things come out. You know, Cursor wasn't around a year ago. And like, that's something that we, you know, we use here at Klaviyo to try to, you know, we're learning how to incorporate that in the workflow and like, where it's strong, like, where it's sort of like, you know, where are we getting the time, the time, you know, back, you know, like, having it work for us. Things like, you know, writing tests, for example, is like a great use case for that. And there are other things it's like, not as good at. Um, and, uh, it's funny, I actually heard. I saw a post yesterday on LinkedIn from the founder of Replit. He was saying he was talking to a public company CEO. Um, and, you know, they talk, uh, companies are increasingly talking about, oh, like, X percent of our code is like, written by AI. Um, but the CEO said in this post, if I'm recalling it correctly, was like, hey, the actual, like, manifold value that we're getting, like, yeah, like we're getting some value from AI writing, writing some code and stuff, but there's like a lot of debugging there. Like, it's almost a lot for them at least at this point. It's kind of a wash, right? There's all the debugging and like getting into production. Like, it's. There's like a lot there, but the product and the design teams, right, who don't have to deal with that, you know, who can move really fast to Communicate ideas, validate them, talk to customers like, you know, they're shortcutting and doing so much more with, with so much less. So product folks have this like superpower now and product design folks have this superpower now that none of us had, very few of us had, I would say, uh, up until about, you know, like, called six, eight months ago. So that is like an area that, you know, for Klaviyo, we're thinking about like, how do we just innovate faster, sharpen our thinking, move quicker, validate ideas quicker. Going back to those like feedback loops you talked about before. Right. Uh, creating that virtuous, uh, sort of engine. Right. Like that. This is like where I think there's a lot of power in AI right now and expect it's going to get even better here. Um, and then in terms of like just how we're thinking about AI for products, right. It's all about how we enable the customer and how we deepen those relationships so we think about even our service AI, Right. It's, it's, it's not just about being able to respond, um, to you know, a traditional customer service question, which we, we definitely do and we do that really well. But it's also just being, having sure that AI is thoughtful and has the right tone of voice that it's able to recommend great products and understand that, that that brand's catalog, um, how are we making it brands able to move faster and do more with less. Right. Something that's working. You know, you're essentially like your best salesperson 247 around the clock on every channel. Right. Like out of the box. Um, so I think AI is really enabling some really cool, um, ways to kind of push on Klaviyo's vision. Right. And deepening those relationships and delivering better there. So it's both, yeah, in the products that we're building and then also, um, in the work that we're doing. Right. I think it's like really those two categories.

Speaker A: Yeah, I agree. I think one of the, to your point, like the feedback loops in research and discovery have accelerated so much to where like we're, we're months ahead of where we are in our dev cycles now at the startup where I run product at Solumina, because of like, we use replit and we put in like a prd, we put in a few screenshots of our app so it kind of understands the design pattern and within 10, 15 minutes we have something we could put in front of our customers and our customer advisory board and the Feedback loops are just much, much quicker than what they used to be.

Speaker B: Yeah, it's like I said, it's such a cool time to be building. Right. I can see it in your, like, you know, how you're smart. It's hard not to get exc about. Right. Because this is just really, it's really fascinating stuff. And it's just, like I said, it just keeps, um, it keeps evolving. Right. It's like, you know, I'm. Who knows like what we're going to see in a year from now, right? Like, I think there's going to be some. We're very early and I think there's a lot of really interesting stuff to come.

Speaker A: Yeah, for sure. And we are early and I know Klaviyo's like the rest of us where it's kind of early days on AI, uh, and agents and like how are we utilizing this stuff? But have there been any like, really cool learnings that you've gotten so far? Whether it's using it internally or as you're building it into the products, getting feedback from customers, any, any really cool like wins or learnings that you've gotten so far that you could share?

Speaker B: Yeah, I think, I think there's a few things I think. Um, so, so one is um, in terms of how, when you think about. So I think one generally like, as easy as it is to build these prototypes and do these things to build like production grade AI that's reliable, that really works. Like, you know, it's, it's hard. Right. It takes a lot of work. There's no shortcuts. Right. Um, and so I think one of the things that we've learned is really where to spend time and think about um, how we're investing and sort of the foundations are really important. We talk a lot about feedback loops for um, in product getting that customer feedback or whether it's brands getting the qualitative and quantitative. Well, it's also, I think in AI it's foundationally important that you're early on building in feedback loops where you're getting that human in the loop input to make your product better. So I think that's one of the things that you know, um, you know, we've, we spent a lot of time thinking about how do you incorporate that. And then I think from a product perspective that's like more technically. But then like from a product perspective it's like how do you then design your products to reinforce the behaviors that you want uh, your customers to do to make your product even better? I Think that is like very like interesting, um, problem set within AI products. The more you put in, the more you get out. Typically, um, you know, it's like, like, hey, uh, I don't know if you, if you're a cloud person or you're a GPT person, right? But like once you kind of get into one for a while and you're giving it more information and it's kind of learned about you, it's kind of hard to switch, right? It's got all that context. It just gets a little smarter every time you put more in. And so, you know, I think there's a very important like, kind of like PLG sort of, you know, if you read like Hooked, right, The you know, sort of classic uh, like near, near walls book, right? Like um, you know, creating those, those loops and, and thinking about like how to, how to build for driving the behavior that you want. I think is, is also like really important learning and thinking a lot about. And um, I think if you move fast, you know, you can react to that. You can, you can make some pretty great progress. The other thing too, I think this is like where it's a really fun. Klaviyo is a really great place to come build AI. If you're thinking, thinking about uh, you know, um, you know, great company to work for. Like, I'll definitely plug Klaviyo here, you know, because at the core, you know, you're a data company, right? Like we're a data company that has built these incredible applications on top of, you know, that, that data foundation. And um, I think that's a really interesting opportunity for companies like us, um, to be able to build great um, AI applications on top of so having that data, um, using it thoughtfully, um, I think that's where it gets really fun. So we're having a good time there.

Speaker A: You mentioned something that I want to press on a little bit because I think it's important. Like you mentioned earlier, we're kind of at another inflection point. There's the high speed Internet, the iPhone. We're at Gen AI and I think at every major technical inflection point we kind of forget lessons learned from the past of uh, we actually need to create value. And it's really about how do we help our customers have the right behaviors. Um, and we just kind of build and think, oh, because we have this cool technology, people will come and they'll adopt it. But you made the point around like how are we using these AI tools to reinforce the behaviors we want our customers to do or that they should be doing. And I just think that's a point that, that um, I don't want to let slip in the conversation because it's so important right now that we keep top of mind. It's not just the technology but it's what does the technology enable and how does it help us solve problems and reinforce those correct behaviors?

Speaker B: Yeah, yeah. And I think like 98% of people are like they need, like they need to be coached into understanding like how to get the value from the AI, uh, from these tools. Right. This is all like, it's new for many, many folks. Um, some of us are like little more early adopters. Right. But you know, you about your, your parents or something like using these, these products. Right. Um, so, so the way that we design the products, um, the way that we think about the ux I think is, is really important for you know, being able to unlock the value because like without, without that like they will do, do some really compelling things but to really get the value right it's, you've got to, they got to put those things together.

Speaker A: Absolutely agree. I, I feel like we could probably have another 30 minutes to an hour going back and forth because it's been a really fun conversation. But um, to wrap things up we do have a uh, pretty good sized audience of aspiring PMs who are trying to get into product. And I know when I was trying to get in years ago it was always this ambiguity of do I need an mba, do I need a certificate, like what do I need to do? So especially in light of like gen AI and how that's changing things about the product profession, what's some advice you'd give to the listener who's trying to get their first shot into the field?

Speaker B: Yeah, um, it's a great question. I was talking to some colleagues about this even just yesterday. I think there's, I mean there's a lot, there's a lot. So um, just like broadly speaking like product management is like a pretty wide category. Like the skills you might need for like you know, an Iot sort of company are a little different than maybe what you would do to Klaviyo. But I'll try to kind of like broad base a couple sort of like archetype traits that I think matter pretty broadly applicable. Um, the first is I uh, think we, what I look for and I think that Klaviyo we're looking for is like people, individuals for high slope. And what that means is like are you able to adapt and learn and Kind of always be kind of um, expanding your thinking, ramping quickly on new concepts, you know, um, taking information and actioning on it. So I think the ability to kind of those sort of like being, being a self learner, really curious, like really being able to get, get deep into problems, um, I think and, and, and, and sort of like have a perspective and understand those is, is really important. The second is, and I think also this is a little bit like where the entrepreneurial comments are coming in. You know they sort of the drive to just go in and, and do it. Like you know, um, be an owner, go build some things. Um, I think now also with all the tools that we have, you know, the other way if you're, if you're trying to get into product and maybe um, you have a non traditional background, um, go build some products, right? Like it's never been easier to go and build products. So I would say go out there, build some stuff, you know, have a perspective, go you know, come up with a passion project, you know, go talk to customers about it. Um, and you, you, you know, you'll just, it's, it's great because you're just gonna, you're gonna learn so much, um, you're gonna have fun doing it. Um, and, and then you know, from a career perspective I think it's going to give you more ammo, you know, to kind of show up and have a strong perspective about like what it takes to build software. And that's probably the third thing is like learn how, learn how software works. You know, I think there's a lot of folks who um, you go and get an MBA or you know, whatever and you get into a PM job and like maybe you have like finance background, you took a couple of courses on it. But like if you don't really understand how software works, I think it's hard to show up and be credible in the room. You know, when you're talking with engineers and trying to swag out, you know, what, what it's going to take to build something and how long it's going to take and which details really matter versus don't. And so I think really kind of taking the time to build things, understand how software and systems work I think is really, really important. Um, because in my experience the best functioning um, product development teams are the ones where Eng and product are really co partners, co founders of driving the product and both, I think engineering needs to have a good product sense and product has, has to have somewhat of an engineering sense. But you, I don't think that means you have to be a software engineer. I think it means you need to like, know enough to be dangerous and get in there and like have a perspective. Um, and so I would say those three things, if you, if you focus on those, I think there's um. Yeah, I think anybody can, can break in.

Speaker A: Yeah, I couldn't agree more. The, the opportunities to build your own thing is, is completely democratized today. Even if it's just a prototype that you can get feedback on, like you can get, get. You can get those experiences. If you learn a little bit of technical stuff, you could probably actually get that deployed and actually into production. So, um, yeah, I couldn't agree more.

Speaker B: So granted, easier to learn too, right? Like go to somebody. Somebody. I'm uh, taking an AI sort of evals course right now and there's a lot of terminology in there. I'm like, like, I think I know what that is. Not really sure. Like, I'll just drop that in GPT. And now, now it's like, exactly class on like everything you would want to know about evals or about, you know, um, yeah, like, you know, whatever, whatever you can think of. Right. So the resources are there. It's, it's really just the uh, the motivation and ambition to go, go and do it.

Speaker A: It's so true. Uh, I come across that all the time where it's like, oh, just drop it in GPT and like get, get a full course on. On what it is. It's pretty great. Cool. Well, Grant, thanks for joining. If uh, somebody wants to connect with you or learn more about Klaviyo, how do they get in touch?

Speaker B: Yeah, so I mean there's lots of ways. So I'm. You can find me most easily on, on uh, LinkedIn. Just search my name. Uh, Grant Deacon. Um, and then if you're interested in what we're working on at Clay Vo, um, you know, you can go to our website. We've got a bunch of stuff around Klaviyo service. You know, come check us out. Drop me a DM. Um, and uh, yeah, klaviyo.com, you know, you can come find us and see what we're all about. And we are hired from many roles, so if you're interested in, in the problems that we're working on, we'd love to, to chat.

Speaker A: Awesome. Well, I'll drop the link to your LinkedIn in and to Klaviyo's website in the. In the show notes. So go check them out. Thanks, Grant.

Speaker B: Thanks, John. This is great.

Speaker A: Thank you for joining us for another episode in Lessons in Product Management. I hope you enjoyed the conversation as much as I did. Before you go, don't forget to rate and review the show. Follow us on Apple Podcasts, Spotify or wherever you listen to your podcast. Go over and find us on the path to product YouTube channel. Make sure to subscribe and like the video there as well and I will see you you next time for another episode in Lessons in Product Management.