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 Truth About AI in the Enterprise with Ed King, CEO of Openprise
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Dan Balcauski hosts Ed King, CEO and founder of Openprise. Ed shares how Openprise helps operations teams improve their go-to-market data with AI and automation. They discuss the impact of AI hype, challenges in AI implementation, and the concept of 'flying too close to the sun'. Ed highlights the importance of pivoting strategy to focus on AI orchestration over developing AI agents, and emphasizes the need for robust infrastructure to support AI deployment in enterprises. The conversation also touches on fostering a supportive company culture, especially within offshore teams, and the value of continuous learning and career growth opportunities.
01:51 What is Openprise?
02:57 The AI Hype Cycle
04:58 AI Orchestration and Strategy
08:31 Addressing AI Challenges
24:32 Building a Strong Company Culture
30:27 Success of the India Team
33:05 Rapid Fire Questions
Guest Links
So every time when Apple asks a new function, probably 20 startup just died, right? And that's what I call the flying too close to the sum problems that, and you're seeing this in the AI space. And sure enough, we start seeing that, for example, in the vibe coding space, right? The moment philanthropic put out their own coders like. Guess what? They own the model in the background. They, of course they will, even initially, they're not the best vibe coding tool. They will be the best vibe coding tool. 95% of the AI projects are not producing ROI. Most of these projects are stuck at the pilot phase. So we never ever throw people under the bus. Because you know what? When things go wrong, things will go wrong. Things go wrong all the time. But what you find is that very, very rarely is people, it's just people just screwing up.
dan-balcauski_1_11-26-2025_111427Welcome 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 Ed King, CEO, and founder of Openprise, a no-code data and AI orchestration platform that helps operations teams make their GTM data smarter with AI and automation. Ed has over 30 years of experience in enterprise automation software, having led product and marketing teams at both startups and large enterprises like Oracle and IBM before founding Openprise. Ed, welcome to the show
ed-king_1_11-26-2025_091426Thank you for having me. I just realized I sound really old with the intro.
dan-balcauski_1_11-26-2025_111427experience and wise I prefer, but before we get into your scaly journey, can you give us the elevator pitch? What does Openprise do? Who do you serve?
ed-king_1_11-26-2025_091426Sure we are a data orchestration platform. Like you say in your intro, we help companies create smarter go-to-market data with AI and automation. We sell to basically all types of. Go to market operation teams, marketing, operations, sales operation, rev ops. We really help people improve the quality of the data and all their go to market system like CRM marketing automation and how to then turn those data into action.
dan-balcauski_1_11-26-2025_111427Your key buyer, just so folks are tracking is primarily folks on the like revenue operations team, or is it also span, sales and marketing? Is it all of the above?
ed-king_1_11-26-2025_091426Yeah, all the above. Basically all the all the ops teams. So if you think about it, it's the ops and the technical folks on the sales and marketing
dan-balcauski_1_11-26-2025_111427I.
ed-king_1_11-26-2025_091426that are managing all the systems, all the technologies, automating their processes. They own the data, right? That, that the go to market team rely on to be successful.
dan-balcauski_1_11-26-2025_111427Got it. I want to dive in directly. We are in the hypest of hype cycles in ai. And we'll leave aside whether we're in an AI bubble or not. But I, the other rule of podcasting is they take away your podcasting license if you don't talk about AI within your podcast. So we're just gonna dive right into it'cause I wouldn't want to get in trouble. But look, you've been watching this AI hype cycle unfolded real time. When did AI start showing up in conversations with your customers or your board? And those might have been a different time period.
ed-king_1_11-26-2025_091426Yeah, it really started about probably two years ago. We started, of course, when. EBT Web3 0.5 came out. Everybody's like, oh my God, this is the coolest thing. And this is also when you see all these new AI companies started to really emerge and we jump on that bandwagon internally, right? We actually started to say, Hey we knew that because we're in the automation business. And one of the big gives value that you can think of that AI can do is basically is. Is another set of automation tool. So we saw the potential. So we started, started trying to use it internally. So our own operations team to dig in. We bought a couple of tools and and you can say that we learned everything that kind of the hard way, right? By bringing the Guinea pigs ourselves. And this actually. It's all before our customer even brought this to us, probably I would say about a year ago, year and a half ago, this is where most the customer they are getting mandates from their management, from their board, say, Hey, we all have to use ai. Probably not the first time you heard this they get a little guidance on. What use cases you use it for, how they should, you see that it is just go use AI and a lot of customer then actually turn to us, and I'm sure they asked the other vendor as well is like, Hey, do you have any guidance and tips on I should use ai, which use AI use for, oh, by the way, what AI features do you have? So we started building out our AI capabilities and if you think back about two years ago this is when you're still mostly just have the foundational models, agents start, people started talking about agents. And so we started going down a path of building out oso agents. And what's funny is that then about. I would say, and just right about the end of last year, about same time last, this time and last year, it was becoming very clear that that is the wrong path to go down to. The this problem I always tell people is what I know. If it's a problem it's a thing I call basically being too close to flying too close to the sun. So I think this script, not script, I think this scenario happened over and over in different industry. Probably the easiest one for people to, associate think about is, as platform like iOS, right? Google Google, the Android platform assay evolve. They keep on adding new feature and functions. So a lot of the the apps that we used to use, they disappeared. Because they became standard features, In iOS. So every time when Apple asks a new function, probably 20 startup just died, right? And that's what I call the flying too close to the sum problems that, and you're seeing this in the AI space. So early on, of course the AI vendors, all they did was building models. And then you have all these some people call them basically AI wrapper companies. They're building all these capability around the models. and we were one of those thinking we need to do that. But very quickly, only about six months into that journey I realized that we have a flying too close to some product scenario going on here, and not just us, the entire industry. You can already see clearly that the models are almost interchangeable the, a lot of the value add these cocoa AI companies are doing are simple wrappers UX around these models. And then you can also see that. of writings on the wall. The model companies, once they get the model to it, if you want a good enough face, start building the applications. And once they start building the application, then if you're the application vendor, you're in trouble now. And sure enough, we start seeing that, for example, in the vibe coding space, right? The moment philanthropic put out their own coders like. Guess what? They own the model in the background. They, of course they will, even initially, they're not the best vibe coding tool. They will be the best vibe coding tool. we decided, you know what, yes this is, this makes no sense for us to try to build agent platforms because people like Salesforce, all these guys, these people with billion dollar r and d budgets, right? They to say a startup like us can out output, out, build them on the, on what? On the agent platform. That's, you're just dilu deluding
dan-balcauski_1_11-26-2025_111427Mm.
ed-king_1_11-26-2025_091426if you gonna think that. we started to really think about, okay, what are the things that nobody else is working on? So we start to, based on our own learning of all the struggle we went through trying to deploy ai, we've picked out, there's a set of capabilities that are just missing. That's preventing a lot of these AI projects from going beyond the pilot phase. And we we build a roadmap around that and we call AI orchestration. It's really so we pivot a sense. And right now that's the where the path we're marching on and getting very good feedback from our customer. We're general feedbacks that they thank that us for addressing stuff that's necessary but not sexy and nobody else seems to wanna talk about.
dan-balcauski_1_11-26-2025_111427So you laid out a full arc there. I wanna probably, uh, walk back through that and maybe flesh out a couple of areas. So, uh, you mentioned originally that you were, first of all like customers were sort of coming to you being like. If we were told to use ai, what should we do? Which I don't, it probably happened to a lot of folks, a lot. A lot of folks were probably still asking those questions of like, I'm being asked to use this. What do I do? And even though these, you know, foundation models have gotten, uh, more and more powerful. You mentioned you started to look at this AI agent. Idea. I'm curious what were you, what did that mean to you? Because I think agents is one of these things that has probably been abused heavily this year. I mean, and it's been around forever. I know you're an engineer. I mean, I started my career over 20 years ago in software engineering, and we had agents back then. So now folks are just like, oh, now we have these other agents. You know, that used to just be a piece of software used to run autonomously on an endpoint. That was an agent. And it would, you know, do something in a, programmable logic controller or on a, on a endpoint somewhere. And so what were you guys trying to build and I guess how did, what was compelling about that, giving those early conversations that you were having at the time?
ed-king_1_11-26-2025_091426Yeah, so we were trying to build something that's fairly, classically defined as the AI agent these
dan-balcauski_1_11-26-2025_111427Mm-hmm.
ed-king_1_11-26-2025_091426essentially a piece of automation that, that sits on a large language model.
dan-balcauski_1_11-26-2025_111427Mm-hmm.
ed-king_1_11-26-2025_091426they're doing. and. Pretty much every major platform vendors building that, right? Salesforce, ServiceNow. And of course you have the the model, foundational model vendors like Open AI and Google Andro, all building, right? So it was a very classic approach to agents, which of course, you know the fact that the everybody's building, So you're like, should I be one of them?
dan-balcauski_1_11-26-2025_111427Mm.
ed-king_1_11-26-2025_091426Because customer's not going to, nobody needs 20 agent vendors, right? So those and if you are a Salesforce customer, right? Eventually you'll probably be using Agent Force one way or another, right? So it is just, again, competitively, unless you have a. Very unique angle to how you want to, you can build out an agent platform that people like Salesforce, people like Service Now people like open ai, people like Google somehow cannot offer. Then if you're just a me too agent platform, which a lot, most agent platforms out there are, again, what's your moat? And one thing I think is, was a kind of a dead giveaway for us early on, is that a lot of AI tools we were trying to use, there's a setting in there that says, which model would you like to use? Would you like to use open ai? Would you like to use Gemini? Would you like to use cloud? And now if you can easily swap out the model in the back, then that tells me two things, right? One is models, commoditize. Two is also, you don't have any moat, right? In fact I know people are familiar with Jason Lambkin from Ster, right? In fact he the article he wrote this morning, he's been a big AI enthusiast. And he built a bunch of agents. And the thing in his blog this morning, he talked about how easy was it for him to move from one AI to another. It's literally copy paste your prompt. And that's again, another reason why we decided that we need to find a AI strategy that has. Durable modes is
dan-balcauski_1_11-26-2025_111427Mm.
ed-king_1_11-26-2025_091426it's not, it is not just a commodity thing where people can easily go for one platform to another. The, so that's, that was important to us when we redid our strategy.
dan-balcauski_1_11-26-2025_111427You know, you mentioned, you know, this problem of, you know, iOS, they ship a new feature. Hey, we added a. A new timer or a new way to manage your inbox or some other capability, and all of a sudden 20 startups die. What was it? You know, so, because you decided to go down a path, what was it that changed your thinking? Because I'm imagining you already knew about this sort of iOS history before, uh, but you started going down a path and then. You know, was it a conversation? Was it like how did you come to the realization, was there, were there signals that maybe when you made that decision that you had missed, that you saw later?
ed-king_1_11-26-2025_091426Yeah, it was two things, right? It is. One was when we were trying to use these tools, we saw how they're all using the same foundational models in the back. And it was really also
dan-balcauski_1_11-26-2025_111427I.
ed-king_1_11-26-2025_091426easy it was to go from model one to model two, that kind of triggered this whole thinking process about, all right, the models are being commoditized and they are definitely are right now. And then it is just the ease of moving and then not really again, got us thinking about then. What exactly is the value add here? And then you start to think about, okay, if I'm a commod, if I'm a frontier model maker and my model's being commoditized, what will I do? If I were running a company, what will I do?
dan-balcauski_1_11-26-2025_111427Mm.
ed-king_1_11-26-2025_091426I build applications on top of it, right? So all these things just like play out the market scenario in my head and just led me to the conclusion, almost a year and a half ago that that, this is where the markets go. Then if we are just building something that has no technical mode people can easily jump to another platform and the, and there's no way I can do as good a job as somebody with a$5 billion research or r and d budget, we have to do something different. We, this is when I realized we are in a flying too close to the sun situation.
dan-balcauski_1_11-26-2025_111427So I think you mentioned it before, but what is your so then okay. You remake that realization and then what did you pivot sort of your AI focus to today?
ed-king_1_11-26-2025_091426Yeah, so it's what's something we ca we call AI orchestration. So it's all the if the best way to think about it is all the supporting infrastructure that's missing around ai. Just quickly gonna I mean, we're not gonna go into details, for example, like. Context, manage context orchestration, prompt management. management model, orchestration. And hybrid integration. This is all about all the kind of infrastructure that's necessary to make an enterprise application secure secure and scalable. And and improve its accuracy and help try to bridge a lot of the kind of native native gaps or challenge that AI has. Like hallucination, for example. AI hallucinations. That's a feature. It's not a, about. How can you improve on that so the enterprise can gain the trust that this technology is accurate and reliable? Very few people talking about this right now, just telling you, oh, it's gonna get better, or, we've made it better, if you, but if you look at the university researchers, what they're doing, what they're, what they're poking at these models and try to figure out the, that challenge is not only is persisting, it doesn't, it's even argue in some cases getting worse. And those are then, so the hallucination, just one example of these are all the kind of supporting functions as. Missing around AI to make it really enterprise ready. And those are the things just from my 30 years enterprise software experience, that are the things that, yes, they're not sexy but they're the things that's actually the most defensible when you build it.
dan-balcauski_1_11-26-2025_111427And I think like, so you have the AI agents, which maybe is like the endpoint doing the work. You've got the foundational models, so you guys are in the like middleware layer to actually make those type of systems work. Is that like way to think about it?
ed-king_1_11-26-2025_091426Yeah. So for example, how do you make sure you have the right data going into the models? That's context orchestration for context engineering. Then once you're prompting the models, making sure you get managing the versioning, the testing, the security of the prompts that you're right. And also once the AI comes back with this response, 20% of what AI comes back's, hallucination. How do you detect that? How do you fix it? AI today, for example, yes, it's sick. It can save you a lot of time. The work, right? Whether it's co or whether it's data, but because of hallucination and all the other related issues, the effort to to do quality control on that output actually has increased orders of active what used to be, intro before ai, when you deploy new technology enterprise, you go through a testing cycle, right? Once you, if you use, if your test cases are good. The system pass all your test use case test cases and you're good. You can reliably assume that the technology will work every, pretty much every single time right outside some edge cases. is different. Ai, even if you fully test it, like I said, hallucination is a feature, so it will still hallucinate anywhere from 10 to 20% of the time. Have to do continuous qa, which is a, it's a, something that's very fundamentally different about ai and that's a, and that's one of the challenge that we saw that nobody was addressing where everybody just rather not talk about that problem, if you will.
dan-balcauski_1_11-26-2025_111427Yeah. Last question,'cause I wanna tie it back to, you know, you, you started hearing from customers, a year or two ago asking you, Hey, like what should we do with ai? Now you've kind of gone through this journey, so I'm curious now like. How do you talk to, prospects about this space? And I guess is that, you've hinted at it a little bit, I think in your arc, but is that sort of different than what you're hearing from sort of other vendors? Like now when they come to you like, Hey, what do we do with this thing?
ed-king_1_11-26-2025_091426Most vendors out there talk about what's possible, right? They sell a dream around AI and that's why the hype fixes, right? And now. Interesting is that we collectively, as an industry, we're about, what, two years into this AI cycle, right? Where for the last two year, most companies, they actually been in this experimental phase, right? This is where the management says go use ai, there's a slush fund of AI budget. You can. use from and nobody's asking for hard ROI yet right? Managing understand, we're all collectively trying to figure out. And so there's a lot of'em have still going through this kind of experimental phase. And some of'em have done the demos, they've done the pilots, and you're probably seeing a lot of reports out there. The MIT one, everybody's signing right. 95% of the AI projects are not producing ROI. A lot of pro, most of these projects are stuck at the pilot phase.
dan-balcauski_1_11-26-2025_111427Mm.
ed-king_1_11-26-2025_091426can't go into production for all the issues I talked about earlier about accuracy, reliability, security, and all that. So what we're finding is that for folks that have got a gun through that experimental. Faced in the last 18, 24 months, when we bring up all these issues they immediately can associate with it because they ran into those exact problems. Those were the roadblocks that they ran into, says yes, accuracy's too low. It's not reliable. I have, my security won't let me deploy it because, it, can be prompt injected. We are talking about the exact things that those people ran into. Now the rea and we are credible because we ran into this space problem ourselves. Well, we were trying to use it that, so we literally say, Hey, and what happens when our ops team started, use our product, try, try to solve those problems that they ran into, that led into our producting, sort of build out those features. So for the folks that have it's in that journey. journey and getting, running into roadblocks. we basically, what we say immediately resonates, right? The challenge is for people who are a little earlier in that phase, they haven't gone, they haven't run into the wall yet, and they're listening to a lot of this kind of hype and promises from vendors about the dream,
dan-balcauski_1_11-26-2025_111427Mm.
ed-king_1_11-26-2025_091426This is where we find that we have to do a lot of education. Then you have customer who are open to learning from other people's, kind of nothing in front of them, right? And those are the ones that also immediately tunes in. And that's also one thing I find very interesting. Different about AI compared to all the other technology I've worked with before. This is that historically you don't have to be an expert in the technology to deploy it, to use it, right? Even I find that AI is different. AI because it has a very, very, these unique things about hallucination, for example. You really have to understand the technology fairly deeply. If you want to be able to do a good job at selecting the right use cases, knowing how to overcome the limitations and not fall victim to, if you will the hype, right? So as absolutely a powerful technology, we love it. But we find out that unless you are fairly well educated about is. Tendencies and weaknesses are, is really hard to make it successful.
dan-balcauski_1_11-26-2025_111427Yeah. Yeah. Well, there's definitely things like, I mean, I, how many people I've had to talk to to explain what a context window is and like, oh, it just, it starts forgetting things, like, why does that happen? Or, you know, if it starts going down a path, uh. And it, it makes a wrong decision and you, it gets stuck in some some well of sadness. It's easier to actually go back into your conversation to restart it than to try to dig it outta that well, because the way these models work, they'll just kind of continue digging in that direction. Uh, it's just part of the, uh, auto regressive capabilities of them or, you know, and so, but you have to kinda understand that if you want to use them or build them appropriately and yeah, to use a, I dunno, yeah. I dunno what the appropriate, uh, version of analogy would be and easier to use, uh, technology land. But yeah, it definitely has a learning curve.
ed-king_1_11-26-2025_091426for example, we've been running these, what we call AI workshops and these three hour workshops. They're not even talking about our product, just basic education. About the state of the art in ai. What are the challenges and tendencies and because, and how do you, what do you have to look out for? What do you have to plan for and what are the techniques you can use to overcome these? And like I said, we barely talked about our product at these workshops. It's just that we, it we found such a need educate people, for them to realize what technology they actually going to need.
dan-balcauski_1_11-26-2025_111427Yeah. Well, you're doing the Lord's work. I wanna pivot off the AI topic. I wanna flip from the technology and market perspective into the internals of building and running a SaaS business. So, I'm one of the topics that's pretty popular on this show is. The idea of culture.'cause it's one of these things that people tell you, you need a good culture and I wanna work in a place with a good culture. And as a leader you're like, well that makes sense. And then you're like, well, what do I do now? So I'm curious for you, like, as you've built Openprise, I guess, what are the cultural practices or I guess points that are matter most to you as you've built the company?
ed-king_1_11-26-2025_091426Sure. And as you mentioned probably you won't find any founder. C there says culture doesn't matter. But I will also tell you a lot of'em, that's just lip service. And we came to the conclusion early on, what we're about 30 people We really have to get serious about culture, because, we know that as a company scales when you're small, everybody knows everybody. Everybody talk to everybody every day. And and I'm involving every hiring process, but as we scale, that can happen anymore,
dan-balcauski_1_11-26-2025_111427Mm-hmm.
ed-king_1_11-26-2025_091426So next group of people have to carry the torch, if you will, on a day-to-day basis. So we put a lot of. Effort into that and just a couple of things that we have done that we think that has worked well. One is that, we make sure the first of thing I have to guess. And so like I, some tell people that building companies not too different from parenting you can say, you can tell employee what to do all day long. They watch what you do, they watch what a management team does. If what you preach doesn't match your actions, doesn't matter what you say. So you have to lead by example. And so a couple things that we have done that I think that's very foundational to having us building a very strong culture. one is that you wanna make sure you always focus on the processing issue, right? So we never ever throw people under the bus. Because you know what? When things go wrong, things will go wrong. Things go wrong all the time. But what you find is that very, very rarely is people, it's just people just screwing up.
dan-balcauski_1_11-26-2025_111427Mm-hmm.
ed-king_1_11-26-2025_091426It's almost always, especially when you are in scaling phase, it's always some kind of process deficient. Right process that didn't exist because you're still scaling or something. The process just got gaps. So what we have found is really works well is that when things go wrong, when you try to figure out what's going on, again, don't, it's not about assigning blame. It's not about figuring out what, where what's missing in terms of our process and what's not robust enough. Let's focus on how do we improve on it so this doesn't happen again. Okay, so that's important because people have to feel safe that they don't, when things go wrong, they're not, you don't, they, they don't have, they don't have to go on the def defensive posture immediately,
dan-balcauski_1_11-26-2025_111427Hmm.
ed-king_1_11-26-2025_091426Because that just doesn't do anybody any good. Other things that we do is that the we wanna make sure we have quite a few young, we hire quite a few young folks, so you always wanna make sure there's career options within the company. We like to say that I'd rather that you stay and do something different than you leave. If I like you. So we always we make it very clear to our folks is that, hey, if you want to try something different or you want to take your career in a different path, tell us, we'll work with you, we'll make sure that we support you. In fact, for example, our customer success organization is almost like a training ground for the rest of the company. These days. We have our current, for example, director of Maps, he came out customer success our head of solution engineering. He came outta customer success, right? Our, one of our product managers came outta customer success. So you, I think it's important to give people that kind of environment set expectation upfront that we're supportive of your career. It's not just do your job and then don't, don't, and that's all I want outta you. And just one last thing I'll throw out. This is a very, sounds like a very trivial thing. I stole this idea from a friend of mine who was, who used to work at Marsh Food. You know how people named the conference rooms? And there it is. People have all kinds of schemes, right?
dan-balcauski_1_11-26-2025_111427Yeah.
ed-king_1_11-26-2025_091426cities, whatever. We name all our conference rooms after our core values. I learned this from my buddy. said, ed, think about it. Outside of your own product names, your own company name, the thing that gets brought up most frequently within company communication, conference room names don't waste. So all our confidential names are after, named after our core value. So every time people say, Hey, where are we meeting? They reiterate the core value of the company.
dan-balcauski_1_11-26-2025_111427What's the most hotly contested conference room that everyone tries to book and no one can get
ed-king_1_11-26-2025_091426actually rank the, we, oh, we don't really rank, but for example the boardroom, of course, is the biggest room. And that's the one, actually, it's our number one core value. We, it's called trust.
dan-balcauski_1_11-26-2025_111427trust.
ed-king_1_11-26-2025_091426So outside of that is, it, we just, it's. just by size. But the, yeah that's one trick I would recommend to anybody is that it's a, it is a, it is the most economical and persistent way just to remind your team every single hour what your core values are. When they walk through the hallways, they see the signs on the rooms. You don't need to put posters up.
dan-balcauski_1_11-26-2025_111427I love that.
ed-king_1_11-26-2025_091426We don't need to see flying ego pictures. But the conference zone, its name is what our core values.
dan-balcauski_1_11-26-2025_111427I I love that it's, uh, yeah it's tactical, but I think that could be very powerful. Uh, and I've never heard it before, so, we'll give you full credit or,
ed-king_1_11-26-2025_091426I
dan-balcauski_1_11-26-2025_111427Alright. Alright. That's fine. Well, and just on one more note on culture when we're talking off camera you had mentioned how proud you were of your India team and I'm curious like how your cultural practices translate to, you mentioning them specifically. Were there things that you did specifically that that maybe. Differ in the way folks build an offshore team. I mean, I'm sure'cause you guys are based in California or headquartered in California. So not a traditional, uh, headquartered India team. So this is an offshore part of the business. What what makes you so, happy about that team success?
ed-king_1_11-26-2025_091426yeah. About serve our teams in India and we, what we do this differently is that we actually hire people fresh outta school. In fact, we hire them before they even graduate. So we go into these campus recruitments and we we basically provide them internships.
dan-balcauski_1_11-26-2025_111427Hmm.
ed-king_1_11-26-2025_091426so when they work with us interns, we also take the opportunity to further educate them, if you will, right. To on being like, being a good engineer, being assistant architect. And that will of course give us the opportunity to also have a. evaluation of if they're good or not. If they're good, we extend the offer before they graduate. that has really worked well for us. And also we, we're very good about, challenging them upfront. So we give'em very meaningful work. So what, when consistent feedback you'll hear is that folks are joining us, after like a year they compare. What they do the, at work, at award price versus, for example, the, their friends at school that graduated at the same time, that may be working for these larger companies like Wipro or Tata Infosys, they're doing just way more meaningful work. They have more responsibility
dan-balcauski_1_11-26-2025_111427Mm.
ed-king_1_11-26-2025_091426they being ed proactively educated. So they, so in terms of their skillset, they can see a drastic difference between where they are. In their career already, even like one year into just our school. And that has, that has built such a loyalty within the team, such low churn. And for example, the person who's running our entire India team right now, we hired him our school nine years ago. And he has just grown up with us. And he was one of those that made us realize that even, like I said, year into it, he was telling us he was already probably three years ahead of all the, all his friends that graduated at the same time.
dan-balcauski_1_11-26-2025_111427Wow. That's a, that's incredible longevity for for one of those teams. And, uh, yeah, I could see how providing meaningful work and getting emer, getting high performers early, giving'em meaningful work and accelerant in their career would all be powerful. Ed, there's so much I would love to talk to you about, but we're running out time, so I wanna pivot to some rapid fire closeout questions you up for it? Awesome. What is your favorite business book or podcast?
ed-king_1_11-26-2025_091426Business book. I can't say F1 consistently, but this is really not a business book. It's a Yuval Har he's a Israeli historian who wrote the Sapien. A bunch of
dan-balcauski_1_11-26-2025_111427Mm-hmm.
ed-king_1_11-26-2025_091426These are history books. But there's shocking amount of application in the business world. I'm a big fan. I read every single book. Yeah, he has written and highly recommend to everybody. Like I said he can get a little bit depressing sometimes about where the society and humanity is going. But I think, I fundamentally business, especially in enterprise software, SaaS business, is all about human relationships. So understand fundamentally how society and human works. I think ask, give you a lot of insight on how you write, how you should base, how the business should run. Anyway,
dan-balcauski_1_11-26-2025_111427very good. Uvaldo Harra highly recommend it. What's your go-to productivity hack?
ed-king_1_11-26-2025_091426Productivity hack writing. I tell, I I do a lot of writing for the company, and I've done that since the beginning. I, my, one of my advice to every early stage founder is that you have to write you, because, as you. In, as a startup you come up with new things all the time, right? You sometime during a sales meeting, you come up with an idea, you start pitching it, and if, and a lot of times, if you just keep on doing that without kinda circle back. Collect your thoughts and then it just, well, it never gets ref refined or sometimes it just goes, it comes in one door, it goes out the other. So I do a lot of writing on the weekend. That to me is a way to force you to revisit those new ideas, new thoughts. And you, I guess I probably all heard the expression that you have to, you learn it, you do it, then you teach it. And to me the writing part is almost it's a different version of teaching, right? This is where you really have to say, okay, I tried this. This is a response I get. Does that make sense?
dan-balcauski_1_11-26-2025_111427Yeah.
ed-king_1_11-26-2025_091426That digestion process, which you have to do when you have to write, is very, very important.
dan-balcauski_1_11-26-2025_111427Nice. If I gave you a billboard, you could put any advice on there for other B2B SaaS CEOs trying to scale their companies, what would it say?
ed-king_1_11-26-2025_091426Understand why you're doing it and what's your timeline, right? So now everybody have different reasons for why they start a company. Some may be money, some may be whatever. If you don't understand why you're doing it then it can easily lead you to the wrong strategy and the wrong approach. Understand why you're doing it. Not only is important for your own it also will impact what kind of investor. You should try to go after, or if you should go after investment at all. Are you trying to have an outcome in three to five years and so you can go to your next thing? Or is this, you're gonna try to, or this is a long kind of marathon. This is a journey. You're gonna try to scale this company out. Be honest with yourself about why you're doing this and what's your time horizon and you're, what you, why are you trying to get out?
dan-balcauski_1_11-26-2025_111427I don't know if we can fit all that on the billboard, but we'll try, we'll try. Well, we'll ask, maybe we'll ask nano Banana Pro to turn that into an infographic.
ed-king_1_11-26-2025_091426Honest with yourself, right?
dan-balcauski_1_11-26-2025_111427be honest with yourself. Awesome. Ed for listeners wanna connect with you, learn more about Openprise, how can they do that?
ed-king_1_11-26-2025_091426Yeah. Our website is ww.open price tech.com. That's O-P-E-N-P-R-I-S-E. I also do write a newsletter on LinkedIn as well. It's a published monthly we go, I go into. Topics about operations and these days, surprise, surprise, writing a lot about ai. Yeah, invite you to subscribe to my newsletter as well.
dan-balcauski_1_11-26-2025_111427Awesome. I will put links to those in the show notes for listeners everyone that wraps up this episode of Sask Scaling Secrets. Thank you to Ed for sharing his journey and insights. For our listeners, you found Ed's insights valuable. Please leave a review and share this episode with your network. Really helps the podcast grow.
