SaaS Scaling Secrets
The SaaS Scaling Secrets podcast reveals the strategies and insights behind scaling B2B SaaS companies to new heights. Dan Balcauski, founder of Product Tranquility, leads conversations with successful SaaS CEOs, exploring their challenges, triumphs, and the secrets that propelled their businesses to the next level.
SaaS Scaling Secrets
The Unexpected Ways AI is Shaping SaaS Companies with Tom Car, CEO of Productive
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Dan Balcauski interviews Tom Car, founder and CEO of Productive, an AI-enabled SaaS platform for agencies and professional services that unifies task management, time tracking, invoicing, and resource planning to improve productivity and profitability. Tom explains how Productive chose early AI features by focusing on customer bottlenecks rather than asking what customers want from AI, starting with AI-assisted report building. He contrasts traditional software with AI’s non-deterministic inputs and outputs and emphasizes the need for evals, evolving engineering practices, and shifting roles across product, design, and engineering. Car discusses integrating AI into existing tiers to avoid stifling adoption, using in-product nudges to build habits, and considering future usage-based pricing for higher-cost AI workloads. He notes AI affects sales as a “future-proof” signal, while some customers remain skeptical or treat AI as magic, and he advises SaaS leaders to rethink playbooks from first principles as the industry changes.
01:50 What Productive Does
03:05 First AI Features
07:17 Building And Testing AI
09:29 Surprises In Production
12:03 Roles Shift And Evals
14:26 Chatbot Versus App UI
15:39 AI Pricing And Credits
20:34 Driving Adoption With Nudges
23:06 Trusting AI Over Time
27:48 SaaS Defensibility Debate
30:57 Governance and AI Magic
32:28 Founder Leads Product
36:59 Rapid Fire Wrap Up
Guest Links
The biggest problem today with building AI software is the non-deterministic nature of it, and there's a joke that like every product manager now thinks that are an engineer, and every designer thinks every product, everybody's now everything. it's, the rules have gotten close to each other. And then we would ask them, well, what would you like? And they're like, well, we don't know. You tell us. They know the technology is out there and they want somebody that's they can bet on it's gonna execute in the future and not gonna become a legacy player in a sense. But then the other thing also that's very interesting for me is that sometimes people consider AI basically magic, which is interesting. The entire playbook I think is changing right now. I don't think a lot of what was worked before in terms of SaaS is gonna work in the future. So you need to think everything you know, from grounds up from first principles.
dan-balcauski_1_03-10-2026_111009Welcome to SaaS Scaling Secrets, the podcast that brings you the inside stories from the leaders of the best scale up. B2B SaaS companies. I'm your host, Dan Balcauski, founder of Product Tranquility. Today I'm excited to welcome Tom Carr, founder and CEO of productive an AI enabled SaaS platform that helps professional services teams improve productivity and profitability. Tom is a Bootstrap founder from Croatia who's built productive into a global company growing 40% year over year with 150 plus people and customers across six continents beyond productive. He's founded, invested in multiple tech companies, including Infinum and joint venture with Porsche Digital, with more than 600 people working across his portfolio today. Let's dive in. Tom, welcome to the show.
tom_1_03-10-2026_171009Hi. Thanks for having me.
dan-balcauski_1_03-10-2026_111009I'm very excited for our conversation. Before we dive into your scaling journey, give us the elevator pitch. What does productive do? Who do you serve?
tom_1_03-10-2026_171009So productive is we mostly serve agencies, consulting companies, and similar companies that do what you would call professional services. We offer them like a one-stop shop so they can do like task management, time tracking invoicing, resource planning, all of that in one place. And that's basically how they can save, like they don't have to run multiple tools, multiple different processes. and basically there are two main aspects that we offer. One is like productivity, so making them productive, that's where the name came from, and also profitability so they can be more profitable because a big part of our platform is actually financial aspect of everything that happens with the client work.
dan-balcauski_1_03-10-2026_111009So helping professional services manage the work that they're doing day to day, and then also making sure that they're making money
tom_1_03-10-2026_171009exactly. So both those things juggling because in the past you would typically have multiple tools doing that, and they didn't talk to each other. And that's where we came in.
dan-balcauski_1_03-10-2026_111009Fantastic. Well, I think there's a same problem on a lot of software companies as well, where your costs cost and revenue side is completely separate from the technology side. But so you explicitly focused at professional services. I think, in terms of the world of technology every. Software company maybe every company is racing to add AI features and capabilities right now. When you, I'm assuming product if productive is not any different from that. When you started thinking about this AI world and where it fits with productive, how did you decide what to build first?
tom_1_03-10-2026_171009So I think the first thing we, I mean we obviously looked at the capabilities, like what can we do with the technology actually, and then what are the obvious low hanging stuff that we can just. Dip part those in and see if it works, right? So it's not just AI that we just added there. We wanted to find something that people would really use. The first thing we did basically was just report building.'cause everybody hates, building reports, configuring them, all that part. And it seemed like an obvious thing, just type something into a prompt and you get like a really nice report before, but you had to click around and basically know how to use the ui. And we got the idea obviously from our customers and like all the stuff that we do now with AI is coming from our customers. But it a different way in a sense that like if you ask customers, what do you wanna do with ai? They don't really know how to answer that question. It's not a straightforward question. It's more like, what do you wanna automate? What's where are the bottlenecks in your business? What are you wasting a ton of time on that, could be faster? And then we try to figure out how to use AI to improve that.
dan-balcauski_1_03-10-2026_111009Yeah. I find that when you talk to customers about. Out, those type of bottlenecks as well. They tend to, obviously depends upon the skill of the researcher asking this kind of question, but they also try, tend to think within the frame of the solution that you offer. So I'm curious, like, how have you thought about that or approached it as you've interacted with customers to try to say like, okay, we. We have a sense of what AI as technologists can do, and then we're going and talking to our customers about, what they're trying to do with their business. How have you navigated? Okay, like use an example of like, well we used it to help with reporting, right? Because currently that's very painful, but that's painful within the scope of your solution, versus thinking about how do we take this capabilities and really. Expand the scope of the problems that we solve for customers. How do have you navigated that and like I'm especially curious like if that's been a challenge as you've tried to manage your internal team as well on shifting that mindset versus just trying to take, hey, what are the friction points within our existing product and how do we think broader?
tom_1_03-10-2026_171009Yeah, I mean there are two, two points there that you made, and I think they're really good. One is what we do with the product and how do we figure out what the customers want and how do we build it and what's the best strategy there. And then the other is just the internal thing, team thing. I'll just, I'll focus on the first one, which is what did we do inside a product? And you mentioned you researchers, and I think that's very important. When you're like a smaller company, which we were as we were growing, we didn't have any researchers. So at the beginning it was hunch driven. Then you might hire product managers and then they're like moonlighting as researchers. And at some point we did hire reaches researchers and that kind of really changed the way that we do this stuff. It's always like research first, it's always talking to your customers, your users, which again, it is a problem when you're a smaller company'cause you don't have any users to talk to. So it's like very, few and far between and it's hard to generalize it. With our larger customer base, we can obviously generalize this stuff a little bit better. That can always be better. But yeah, we didn't try to approach them with the AI angle. With all of those research sessions we're more around, again, what do you want to improve in your business? And yeah, you're right, it does boil down back to our product, but that's also good for us because. don't wanna go too far. We want to improve what we can with the data we have with the product. We have that was at least when we started doing this, maybe a year and a half ago, today. We can expand more on this stuff. But yeah, then the customers are just, you start, you get them talking and they're like, yeah, I can do this. I spend a lot of time on, I know compiling reports. Not like data reports, but project updates, all of this stuff, and I need to build tasks from notes from a meeting, blah, blah, blah. All these like typical things. And then we sit down and see what's, what are the common themes or the most important themes, and just get into it and figure out how to solve it.
dan-balcauski_1_03-10-2026_111009So once you've. And if it helps to talk about a specific feature or even keep it at the general level. One thing I'm interested in is that, as companies have started to add AI enabled tech, feature sets into their products, it's one thing to say, okay, we're gonna go build this, and then it's another to actually go and do it with the way that a lot of these AI systems interact on the backend. How have you seen the difference between, building the, with these AI enabled capabilities versus maybe what we might refer to as traditional software?
tom_1_03-10-2026_171009Yeah. Yeah. I think that's a good thing. Traditional software. The biggest problem today with building AI software is the non-deterministic nature of it, and it's on two sides. You have the input is non-deterministic.'cause typically it's like a chat box, it's a text box where people type in whatever they feel like it in whatever language. And sometimes, we see what people type into and it's like somebody types in three words. Somebody types in like a paragraph and it has to work the same for both of those things. And then it goes through a system and it, there's an l lm in that system that spits out an output. And then the output is also non-deterministic. You, it's not always the same. So you have done determinism on two sides and if if you're used to, building typical, traditional software where kind of the input is a form and a button and the output you can test with automated testing, this completely different. There that's a mindset switch both for kind of the product side of the business, product management, but also for the engineering side of it and the design. And it's all becoming different. And it's also very new. So there's not so many established practices that you can copy paste from. You gotta figure this, a lot of this stuff out yourself. It's very, it's changing a lot. The biggest kind of thing here is evals. For everyone who's not familiar with evals, it's automated tests, but more geared towards LLMs and, AI systems. And it's a different way of testing if your thing actually works. And figuring out how to build that and get source the data from it. It's like a new skill, I would say in product management and in building these ai, AI enabled applications or AI native applications.
dan-balcauski_1_03-10-2026_111009So as your team. The business went through adding these AI capabilities, I guess what surprised you in that process? I think evals are starting to percolate a little bit more, but, I imagine if we went back even 12 months ago, if I'd asked anybody what an eval was, they would have no idea. So I'm curious like what surprised you, like as you and the teams, like, Hey, we got this great idea, we're gonna go do it, and. Maybe the CTO like, spends a weekend and built a really impressive demo, but then that's different from getting set that into production. What were the areas that, either were surprised or were bottlenecks as you guys made this transition to, to build these products.
tom_1_03-10-2026_171009Yeah, when you start, you do just like a vi check. Type of thing. It's not you. You try it out, if it works and you go, oh yeah, this works. And then you give it to customers and they just surprise you with what, whatever they put in that, from that non-deterministic side of the product. and then you have to go back and figure out some, a more structured approach. So that's one thing that surprises also, some of the stuff that worked that we built out, I would say a year ago. We don't need right now because the way the kind of, the models have changed and related to that, or we're doing it a different way now like a lot of these like models are very smart now and you don't have to instruct them so much more as in give them tools. So it's an orchestrated in, in, in a better way. And you can see that a lot with coding right now. So what happens with for example, cloud code and everything that happening there, it's more around the orchestration and just giving the actual LLM everything it needs so that it can, code and not giving so many instructions, which was different like a year ago or two years ago. You had to build these. elaborate prompts and dictionaries and everything, and right now it's a little bit different. So you know, things are changing, but that's been the biggest surprise for me. That's something that we built a year ago was, we're doing completely differently now.
dan-balcauski_1_03-10-2026_111009So I'm curious kind of maybe tying a couple of things together.'cause I think maybe what I just heard was like people have referred to this differently of like, scaffolding or guardrails, right? Some of these models had very poor, recall or they would go off on, in tangents areas, right? There are a lot of funny jailbreaks of people, tricking ai service chatbots into, giving them a bunch of, money that was it, possible or you know, give me a recipe for a tuna salad, uh, whether you're chatting with your Salesforce support agent. So, you know, the models themselves have got more capable. So I imagine, you know, that's changed a little bit in engineering. But then you also talked about, you know, the evals. Has that changed? I guess either one of those, has that changed organizationally, like responsibilities inside the company? Um, meaning like, you know, in traditional sort of product design engineering, right? You've got a spec and sort of the engineers build to that spec and they test against that spec. But something like an eval. Starts to get a very, starts to get squishy, right? You have a little bit more because you have so many different other dimensions, you know, does that creep into, oh, well we actually need the designer or the product manager or the customer success people to actually be running these evals. Like how has that affected the organization in, in, or in your view of who is responsible and who needs to have in insight into that.
tom_1_03-10-2026_171009We're still also trying to figure out the best way to move forward. And you typically have these three roles. You have the engineers, designers, and product managers. And right now these roles are changing a lot. And there's a joke that like every product manager now thinks that are an engineer, and every designer thinks every product, everybody's now everything. it's, the rules have gotten close to each other. I don't think they're still or they're ever gonna be. Completely merg into one thing because just some people are better at certain things. But you as a product manager need to be closer to the code, the technology. You as an engineer need to be closer to the user, so meaning design because as an engineer before maybe you didn't need to be so close to what the customers are saying, but not what the customers are saying. They're saying in a. bot chat box that's going directly to you as an engineer to figure out how to create an interface out of. So it it, it has changed a little bit and we are trying to also figure out how to do it properly. The whole eval thing, it's mostly around product management and it's mostly around engineering, I would say. Not so much design, at least for us, I think. But the other thing there is, that's interesting to me is figuring out to what. Degree, your product is a chat box. And to what degree it's a application. And where do those things blend and how do they work together? Because a lot of products today, you take anything like lovable, it's here's the interface you're building, here's the chat bot. What is your, what is that for your product? And doesn't make sense in all situations. In certain situations. It's it's very interesting and I don't think it's, the same. So we're also trying to figure that out.
dan-balcauski_1_03-10-2026_111009I think that, even over the last, two years, right? I think when maybe GPT-4 was released, I think the first round of AI enabled applications, everyone just added a little chatbot to their product. It was like, okay, now we have ai. But the problem there is that it's like. One, it's a blank slate. And so anytime, if you give a blank slate to a very technical power user, they're like, this is awesome. I can do everything here. If you give it to, quote unquote normal user, they're like, I don't even know what to type here. But then even if you look at something as simple as, you know, a lot of these, even the. Foundation model companies open ai, philanthropic they can now create, documents in a workflow. Well, okay, now I have a chat and a document, right? I mean, you mentioned lovable, right? Which is, okay, now I've chat and a user interface. Well, what do I change directly in the document versus what do I chat about changing in the document, right? So even something as easy as like document management just in. Implies a whole new paradigm of interaction that we haven't had to deal with before. And so I think a lot of companies, I don't think anybody's figured it out yet. I've seen some interesting ideas, but I don't think, uh, the industry as a whole has aligned on a pattern. One thing I wanted to ask about was that, you know, looking at your, I was looking at your, uh, your pricing notice. You know, you guys have included AI across, all your tiers versus having that as a, premium, you know, paywall or add-on. I'm curious, how did you arrive at that approach? I think there's a discussion going on across, boardrooms in every, tech company being like, well, these. Large language models, right? We could have a large bill going out the door to open AI or Google Gemini every month. Like, we, we want to, charge customers, more for this because it cost us more. How did you guys end up at this approach where it's embedded in your product across the tiers?
tom_1_03-10-2026_171009Yeah, so I think that there are a couple of questions there. One is do you have a separate tier for your AI functionality? And right now for us, that is merged into the basic product line.'cause as we were building out the AI functionality made sense. But the other thing is more about the credits. So usage based pricing, meaning the more you use the more the customers pay. And that's what all the large language models you mentioned the foundation labs are doing. So you're paying it, either, it's either through a bundle or something, but at the end of the day, you are paying for the. Tokens or credits or whatever you call it. And that's like also our direction going forward. So, we are gonna offer for those functionality that's not very cost prohibitive for us, we'll just wrap it up probably in the main product. But anything that's higher throughput, that kind of requires more AI usage I think the only sensible way is to do some sort of credits pricing, usage based pricing or outcome based pricing. If you can do. It. which are all I think, interesting. Some are easier to do in some industries than others.
dan-balcauski_1_03-10-2026_111009As and I apologize because I maybe skipped over this. Is the is that sort of credit bundle offer like on in, in your price, existing pricing? Today?
tom_1_03-10-2026_171009No. Not the public one, but yeah.
dan-balcauski_1_03-10-2026_111009No, not.
tom_1_03-10-2026_171009up.
dan-balcauski_1_03-10-2026_111009It's coming. Okay. So I, my research was correct but we're talking futures. As you've gone into it sounds like there was, you're seeing a potential change of even more advanced capabilities that are, potentially going to drive more costs. There's more or tokens generated.
tom_1_03-10-2026_171009And also,
dan-balcauski_1_03-10-2026_111009curious.
tom_1_03-10-2026_171009value created through that process. It's if you're just generating tokens, value, nobody's gonna pay for them. So that's where we see opportunities.
dan-balcauski_1_03-10-2026_111009Yeah. I'm curious, like going back to like even the stuff that you launched originally though, right? You know, because I think what's interesting about, you know, your approach is that wasn't, it sounds like you're going to the go there for at least some features, but I think out of the gate, the majority of companies that I. C I spent all my time in the pricing and packaging world, so this is a pretty thing I pay attention to a lot. And so I think the initial sort of gut reaction of a lot of companies is like, well, this is gonna cost us tokens. We're going to charge it as an add-on. I'm curious, what was your thought process around not, around the bundling o option, like upfront?
tom_1_03-10-2026_171009The thought process mainly was we don't wanna, stifle in the beginning. We don't wanna stifle usage on, because it's always like you have the U and monetization and those are two levers. If you pull on too hard on monetization, usage is gonna drop off. Especially in the beginning when you're building a new feature or a new product you can afford it. I don't think you should over monetize because you want to see what people are gonna do with it. It's probably also. It has bugs and maybe it doesn't work. A hundred percent you want user feedback. And a good way to do that is to not over monetize. And that was basically our strategy. And now that things are progressing there, we're gonna work out some monetization strategies that are a little bit.
dan-balcauski_1_03-10-2026_111009Yeah, that's I was pointing it out because I think it is unique and, there's always a risk of a. Any new product innovation, right? You put out a new feature, no matter how much, how many, customer conversations you have, you build something, you think it's gonna be awesome. And then, Pareto's principle pers law, like Rule Supreme, right? It's like, the majority of your feature usage comes from 20% of the features and a bunch of thought stuff you thought was gonna be, life changing. So you always have that risk. And I think what you pointed out really well is like as soon as you put up a monetization gate. You, you increase that risk because like, we didn't get usage, just because of the, every feature that we introduce has a risk of not being adopted. And now we've also made that hurdle even higher for our customers to, to get it. I'm curious, like, as you have gone down that path I'm wondering if you could talk a little bit too, what were the things that you were able to learn with that approach? Because I think a lot of companies are throwing AI features out there and are, just like, I don't know, like, is somebody using them? Yes or no? Like, as you were able to increase that, flywheel of usage and adoption, what were the things that you learned that you might not have otherwise seen if you had, more gated monetization? I.
tom_1_03-10-2026_171009I think one of the main things I would say in general with AI usage across, let's say a product that's implementing AI functionality is you talked about it before, is like you give people a chat bot and they don't know what to do with it. So what we found that works is just plugging various functionality across the traditional interface that feeds into the chat bot. So I'll give you, I'll go back to our example of a report building. So you go to our report builder, the traditional one, and there's like a button air reports, and the only thing that button does is it opens up the chat bot with a pre-selected prompt, but then. People, oh yeah, I could do this in the chat. But if we didn't have that there, people wouldn't be like, oh yeah, let's open up the chat bot and ask you to build a report, because the habit is still not there for most most customers, most users. So these like little habit building situations all over the product, which is what we are doing actually have a really big impact on the adoption of the whole thing.
dan-balcauski_1_03-10-2026_111009Yeah, so there's little, uh, yeah. Uh, habit adoption hooks. Yeah, nudges. Which yeah if, each of those has a, somewhat percent chance of being engaged. And again, if you have just a smaller pool of people who are paying you for that I remember, you know, uh, personal, my personal experience, my, my CRM that I use, you know, at some point, two years ago, uh, for the plan I was on, they introduced, you know, summarize the account history with this customer option. And they gave like three uses a month for my plan that I was on. Right. I was on symmetry level plan. And I say this to say that I completely align and empathize with that point of view you just said, because, you know, it's like once I hit that three usage. It was like, okay, that was interesting, but it didn't become, it wasn't like enough for it to be like, oh, now this is taken away from me, and like, I need this for my business, so please let me pay you the extra to like, upgrade. So I think there's always that that it, there's a lot of like art and science to that of like, how much do you give in a particular plan before you let someone, upgrade. Right. And so, that was
tom_1_03-10-2026_171009But
dan-balcauski_1_03-10-2026_111009good.
tom_1_03-10-2026_171009yeah, but like our strategy from beginning implementing AI was not to make money off of it, because we still think it's very early. So we want to build a good product, the best product, and we want people to use it. And then we'll figure out how to make money. Kicking out monetization straight through the door I think wouldn't be good. So like we, we don't, we wouldn't wanna do that. Like charge for three uses of a thing that probably doesn't cost you too much.
dan-balcauski_1_03-10-2026_111009Yeah. Well, I think a lot of folks are. Finding that, these ais, right? We run the risk of, uh, too much anthrop authorization or treating these ais like a human, but to a certain extent you know, a lot of these models have, they become smarter. They're now at the level of maybe a junior employee and you don't give the junior employee a new, Hey, re-architect our software like on your first week, right? You build up that trust and capability over time. And so it's almost like you need to.
tom_1_03-10-2026_171009And you train it, and you figure out the various skills and tools and everything. Yeah, exactly. Exactly.
dan-balcauski_1_03-10-2026_111009And so, you know, for users to adopt it, right? I think it requires, you know, just for their perceived value of that. You know, before you say, okay, well now it's time to charge. I think that's what I don't wanna gloss over what you said, but I think was really important because it sounded like you had a defined business objective in mind, which is, it's early. We want to, drive value, learn. Our goal is not maximizing monetization outta the gate,
tom_1_03-10-2026_171009absolutely.
dan-balcauski_1_03-10-2026_111009I'm double clicking on that because I think that's so important, and it's an area that folks don't really spend the time in the executive room discussing what is your goal for this, right? Because it's very easy for the CFO to say. Hey, we got this big bill from OpenAI this month. Uh, we need to not, I need to make sure my margins don't change. Uh, and then for product to react to that versus having that discussion at the executive team level, even at the board level, saying like, look for the next year or two years, like, we're gonna treat this as an investment to learn, to figure out what is actually valuable. And then, align, you know, longer term monetization goals after that. So I think that's really smart. How has you ob you're in a very competitive space, so I'm curious, like, as it pertains to these applications of artificial intelligence within the platform how have you viewed that through like a competitive lens? Because, you know, as I mentioned before, right, like everyone maybe ran out and added a chat window to their ai and then. I think what I saw across the board is everyone's like, we're now AI enabled. Well, but so all your competitors claim the same thing. How have you thought about it from do you feel that like. These AI capabilities are commoditizing.'cause look, the next person next to you could use open AI or aros, most latest model. How have you thought about it through like a differentiation lens to avoids like, yeah, okay. We've now added additional cost profile, but you know, we're no better off than our competitors in this landscape.
tom_1_03-10-2026_171009You have your traditional software business and you have your traditional competitors, and like you said. Some of them added the chat box, some of them did the chat box. Some are, more into into the, down the AI rabbit hole and summer life. But I think, what I at least look at it and what our, I guess what our strategy here is we are building these features and we are using all of the same lms, but. The way that you work with the lms, the data that you have and the way you structure'em, I think that's where the gains basically are. So it's again, it boils down to like a product management and a strategy decision. It's I don't know, 20 years ago you would say, yeah, we're all using the same databases, we're all using MySQL, we are all using the same Ruby rails or whatever you're using. like the products are gonna be the same, but they're not, it's depends on who's building it and what your ideas and what your strategy and what. What your vision is. obviously, in competitive spaces, people always look what, look at what everybody else is doing. Which sometimes I think is good. Sometimes I think it's bad'cause then everybody just starts doing the same thing. But it is the same game, but with different tools. The way that's, at least the way I see it. I think that the other question is more around the categories of software. So are they gonna change? For example, you typically had like project management, software, resource management, software, CRM, et cetera. So we are in that space. We are project management, resource management, CRM bundled it into one thing. What's gonna happen there, like if, like way that people work with this software changes and that's like a question what's gonna happen with. Our customers and the way, their businesses evolve with ai. So those categories might change and then that's an interesting, I would say, thing to see. So are people gonna use, I don't know, Chad, GPT for some stuff? So how does that impact us and other products? is CHE PT like a gateway thing? So they start using it, okay, now I need to connect this to an actual database, an actual system. Et cetera, et cetera. So that's what we're trying to figure out.
dan-balcauski_1_03-10-2026_111009Yeah I gave you a little bit of an impossible question because I don't know exactly when this will come out, but if folks are paying attention to the, what's going on in the stock market right now there's many terms for it, SaaS apocalypse or the AI tidal wave et cetera. And so I think a lot of even, very large public companies are getting, revalued of like, what does this all mean for your, long-term defensibility. And I haven't heard anybody give. At least anything that's a hundred percent of a convincing answer. I think it, it really depends upon very different types of software and applications and specific focus to customers. I was listening to a good conversation yesterday and someone made a very astute point of like, people often talk about these, system of record versus system of, workflow or systems of profit. Processes. Because, it's like databases are systems of record, right? We haven't really been thinking about those forever. It's, when we think about I'll use Salesforce as an example love it or hate it, right? Salesforce has an advantage because there's a good chance if you hire a sales rep. They probably know how to work on within Salesforce on the first day, right? And maybe there's some customizations for your company, but and then if there are customizations that defines specific workflows for your, for your company. And so I, I don't think that companies are gonna come in and, vibe code their own version of Salesforce. But, there probably is another layer of, challenge to their competitive differentiation because, if they come out with a new feature, you know, that's super AI enabled, if. The hype is to all be believed if, even if you couldn't do it now, you know, the software development cycles should be getting shorter. And so the ability for, uh, their competitors to, to catch up, uh, maybe, uh, decreasing over time as well. And so, uh, you potentially run into this, uh, race where, you know, consumers are the net beneficiaries or consumers, either business or, uh, regular. Uh, non-business, uh, customers of software because you're gonna get more and more value of that differentiation is not gonna hold up over time. I'm curious how, if at all, has the introduction of these AI capabilities changed the conversations that your sales teams are having with customers?
tom_1_03-10-2026_171009That's really across the board. Like some people really expect it and it's a way that they gauge your platform as being like a serious future proof player. It's what are you doing with ai? Also very interesting, like we, we had conversations where, customers will ask you. What are you doing with ai? And then we would ask them, well, what would you like? And they're like, well, we don't know. You tell us. It's not like people know, they just know they, they know the technology is out there and they want somebody that's they can bet on it's gonna execute in the future and not gonna become a legacy player in a sense. I think that's the biggest way of changed it, but also on a lot of topics, people are hesitant, I would say skeptic. ai for various reasons. Sometimes it doesn't really work, so they're ah, think you know what I'm talking about, right? That, that, so those situations, people just want a traditional piece of software that, does the job that they needed to do. And we're very flexible in both of those situations. So I think that that's good for us.
dan-balcauski_1_03-10-2026_111009Have you, uh, maybe you're not directly involved with this conversation, maybe you are with some of the, you know, larger customers have you noticed a increase in sort of customers. Fluency and understanding of the technology such that, I've talked to other folks on this program who, you know, depending upon the industry that they're in they've had changes to that have affected them at like a procurement level where like now they have to go through, you know, especially selling enterprises. Maybe they have an AI technology board who they now have to go through. Um, have you noticed a change in, your customer base of how they think about AI technologies or maybe just'cause you of the market you serve that hasn't been as much of an issue for you.
tom_1_03-10-2026_171009Yeah, that actually hasn't been much of an issue. We al there's always the whole data governments question and that's been around even before AI now is like a little bit more. So, are you training, the models getting trained on our data, et cetera, et cetera. So these questions which, we give answers to and that's okay. Other than that, we didn't see a lot of problems there. Like I said, it's customers are either, we want this, it's interesting, and we are or we don't want it. But then the other thing also that's very interesting for me is that sometimes people consider AI basically magic, which is interesting. Like you, when you talk to them and you see some use cases and those are use cases that don't have anything to do with ai. It's more around some like regular automation or like a workflow or something. But it's more like, I just want this problem solved. And I want AI to do it. It's it's very interesting.
dan-balcauski_1_03-10-2026_111009I, I do wanna transition a little bit because we, I've been asking you a lot of product focus questions. And as I understand, you're still leading product at productive. Is that correct?
tom_1_03-10-2026_171009Yeah. Yeah. So I lead a team Product managers and product managers working on the, on the product.
dan-balcauski_1_03-10-2026_111009At your scale of about 150 folks, I think a lot of folks might be surprised by that. May, maybe, maybe not. What has been your impetus to still, keep that hat on as you've grown the company?
tom_1_03-10-2026_171009I think I'm, I've always been a product person. It's part of my nature. What is that saying? When you have a hammer, every problem is a nail or something like that. So basically that's me in my career. I've always, when I had a problem, I tried to solve it by building something, like a product to
dan-balcauski_1_03-10-2026_111009Hmm.
tom_1_03-10-2026_171009and that's how actually I ended up here. So it is something that I think I'm good at, or at least that I like doing, which kind of then just motivates me to, invest a lot of effort into it. Very early on we started building the product and we started doing sales. My, my basically idea was. I don't wanna sell the product.'cause if I have to sell it, and I'm gonna probably do it for 30, 40% of my time. And it's never gonna be, great. So out the door, we hired, salespeople at the beginning and I wanted them to sell it. And then the other idea was also if they can't sell it, then the product is not good enough. If I have to come in personally and, convince somebody, well that product really is not good enough. And then me as the product builder has to make it better. it, we started like that, selling it. And that was the phase where until you get product market fit. It. as we got it later on, it just the flywheel starts and that was good. So yeah, that's like my main drive. I obviously run the entire company, but like for this particular area, I don't have a VP of product.'cause that's like my dual role for all the other areas. Marketing, et cetera, et cetera. I do have, technology, I have VPs that handle it, but this is just like an area that's very close to me. The question I always ask myself, obviously is how long is, can I keep it up? And I don't know. We'll see. I think right now in this whole crazy AI age where everything is changing, you mentioned vibe, coding there's a lot of stuff. Ev everything is getting new and the cards are being rearranged. I think as a founder. very beneficial to have you close to the actual product and to the users in a way, just by proxy and to their needs and requests. I think it's beneficial at this stage, and I guess at any stage, but at this stage I think it's even more beneficial than before.
dan-balcauski_1_03-10-2026_111009Yeah we're seeing that actually across even some very mature companies where, founders are getting involved even all the way going to Sergey brand at Google. Right. Jumping back in, started writing code again which I don't know that anybody had on their bingo card in 2020. But I'm curious like. Given that role, like, how do you decide, like what does your schedule look like? How do you decide to split time between sort of the focus on the product and the broader responsibility? Because I'm thinking, um, that must imply a serious amount of, uh, delegation, uh, work on your behalf. I'm just curious how you've how you've approached that.
tom_1_03-10-2026_171009Yeah, I try to do like a cadence. So basically, I don't know, every Monday I have a bunch of meetings, like one-on-ones with with my direct reports, and that's like the company building part the sales part, the business part mostly around that marketing, et cetera. I'm focused on the product, so I do syncs with all the product people and see where we are with that. And Wednesdays and Thursdays, I like to keep open as much as I can to do like workshops and to work with actual, people in the office. Let's sit down. There's a problem when people need my help. The people don't need my help like all the time, often they do'cause. I have the knowledge, the, like, how customers work and also how the product works and like decisions we've made in the past and why did we make them, et cetera. But yeah, so I like to keep a big part of my schedule actually open so that people can, pull me into these discussions. and that's been working really well.
dan-balcauski_1_03-10-2026_111009I wish you continued success. It sounds like you have a highly regimented approach. So probably more so than I could pull off. So quite impressed by that.
tom_1_03-10-2026_171009So today's Tuesday. I like you're my last meeting today. I've been like at it since morning. Half an hour. Half an hour. Half an hour. I think I had 10, 10 meetings. It's very fast. It's very, what are problems? Okay, try this. I don't know. Okay, we don't have a solution. Let's do a workshop, let's do brainstorming, et cetera, et cetera. And that's every week. That's what I'm doing.
dan-balcauski_1_03-10-2026_111009Oh Tom, this has been great. We're running up on time, so I want to segue out to a couple of rapid fire closeout questions. Is that okay?
tom_1_03-10-2026_171009sure.
dan-balcauski_1_03-10-2026_111009What is either a book or podcast you find yourself recommending? Most other people these days?
tom_1_03-10-2026_171009Ooh, our podcasts are like my thing. I dunno. I like all the landing podcasts of a product. I like Pragmatic engineer, which is very interesting to figure out, how people are coding today. I think those are the two main ones like out, out of the big ones that I listen to.
dan-balcauski_1_03-10-2026_111009Nice. When you think about all the spectacular people that you've had a chance to work with, is there anyone who just pops to mind who's had a disproportionate effect about the way you think about building or leading companies now?
tom_1_03-10-2026_171009Oh, that's interesting. I think, my career has been mostly influenced by, people that have I've lived with, like, give you an example. When I went to high school, I had this guy who was a computer science or whatever it's called, the course. Teacher and he never actually taught me anything about computers or anything, but he gave me so much confidence that I could do it all, and that basically labeled my life, up until today. The interesting thing is, 25 years later, I'm still friends with him.
dan-balcauski_1_03-10-2026_111009I gotta ask the follow up what did, what was his method by which he gave you so much confidence? I think that would be a amazing for other folks.
tom_1_03-10-2026_171009It's, he, at some point, like I was 15 years old and I already knew coding, like there's nothing I could actually learn in the actual courses.'cause I basically knew it all because I liked it. I was doing it in my spare time or something and he was like, You, it was me and my co. Co-founder later, but my friend back then, and he was like, okay, you guys know more than me. You guys know more. Here's just, here's computers, here's time. You guys are smart. Figure it out. And constantly when you would maybe dive yourself or something, you would say, okay, you're smart. Figure it out. You can do it. Ah, don't gimme that, blah, blah, blah. You're building up your confidence that you can actually do it. I think that's important. Like in your life, you need probably just one person to tell you can do it right.
dan-balcauski_1_03-10-2026_111009Yes. We're all lucky to have such folks. Glad you guys have remained friends over all those years. If I gave you a billboard and you can put any advice on there for other B2B Sass CEOs trying to scale other companies, what would it say?
tom_1_03-10-2026_171009The entire playbook I think is changing right now. I don't think a lot of what was worked before in terms of SaaS is gonna work in the future. So you need to think everything you know, from grounds up from first principles. What is this gonna look like in, five years? These, like, technological shifts don't happen that often. And I think that, yeah, that's my main advice. Everything's getting rewritten, so, think everything through yeah. If you're reading a book 10 years old, how to build a SaaS company it's not applicable today. So it just you have to figure it out yourself.
dan-balcauski_1_03-10-2026_111009Yeah. Well, that's a long billboard. I think it's the, all the playbooks are changing. Figure it out. Uh, for the prince of. Well, and also the reason that this podcast exists, so, continue to tune in to other leaders as we figure out what they're learning from the ground up. This has been fantastic, Tom. For listeners wanna follow you connect with you around the internet or learn more about productive, how could they do that?
tom_1_03-10-2026_171009Yes, probably LinkedIn. You can connect with me there. Follow me there. See what I really up to. And yeah, you can also follow me on Instagram if you wanna know where I travel and what type of music I listen to. And that, that that's the two main places.
dan-balcauski_1_03-10-2026_111009Which, what's go-to on your Spotify or iTunes these days? What's what are you listening to?
tom_1_03-10-2026_171009Oh, it's like Croatian, Serbian music. But
dan-balcauski_1_03-10-2026_111009If I had to, if I had to listen to one artist, if I had to listen to one artist in that category, who would it be? Gimme a name.
tom_1_03-10-2026_171009Oh, lately, oh, we have voco v That's these an interesting artist. He has a new song.
dan-balcauski_1_03-10-2026_111009Okay.
tom_1_03-10-2026_171009And
dan-balcauski_1_03-10-2026_111009All right. I will, I will,
tom_1_03-10-2026_171009I listened to Blink 1 8 2, which is like music I've listened, has had listened to for 20 something years. It's probably now classic rock or something that you would call it today, whatever.
dan-balcauski_1_03-10-2026_111009Yeah. Yeah. Well, I remember when as a child, I used to go to the grocery store. They play all these old old timey songs, and now I go and they play these amazing bangers. So I don't know what that means about about my life. Well, I'll put links into the show notes for of all that for listeners that wraps up this episode of Sask Galy Secrets. Thank you to Tom for sharing his journey and insights. For our listeners, if you found Tom's insights valuable, please leave a review and share this episode with your network.
tom_1_03-10-2026_171009The.
