Building Before You Launch? David Hirschfeld on Why That Might Be a Mistake

[00:00:01] Welcome to the Startup Builders and Backers Show, a podcast which is part of the Tech Talks Network. I'm Neil C. Hughes and you may know me from the Tech Talks Daily Podcast, which covers a completely different topic every day around how technology is ultimately impacting our life, our work and even world.

[00:00:22] But the Tech Talks Network is a series of unique podcasts that drill down on unique subjects and showcase the voices right at the heart of tech startups. And in this series, I want to shine a spotlight on the energetic world of startups where bold entrepreneurs and visionary investors come together and create the world-beating solutions of tomorrow.

[00:00:47] So the conversations you can expect to hear on this show will dive right into the journeys of those building innovative companies and also the strategic insights of those who support them. Balancing the excitement of breakthrough ideas with the more pragmatic challenges of scaling a business. So if you're a startup founder, you get to learn from other founders some of the mistakes they learned and also some of the opportunities that they unlocked along the way.

[00:01:14] So I invite you to join us as we unpack the risks, the rewards and the realities of turning those groundbreaking concepts into successful enterprises. So if you're building a startup considering one or just fascinated by the intersection of AI, software, strategy and startups, this conversation is going to be packed with insights you're not going to want to miss. But enough for me. Let's get David onto the podcast now.

[00:01:44] So thank you for joining me on the podcast today, David. Can you tell everyone listening a little about who you are and what you do? Yeah. Hi, I'm David Hirschfeld, and I am founder of a company called Techies spelled T E K Y Z. We do custom software development for and I founded this company 18 years ago. We do a lot of software development for a lot of startups. That's not our only market, but it's a big part of our market.

[00:02:12] And I've worked with over 90 startups during those 18 years. A few of them really successful, but the vast majority fail. And that's true with all startups, especially in the software world. And I've found the patterns that I believe make software companies successful and the ones that cause them to fail.

[00:02:34] And realizing those patterns, I created a methodology called launch first, where we help startups get to cash flow in just the first few months, even before we develop their product by doing pre-launch sales as a way of proving product market fit. So that's what I do now. I've been in the software world for 35 years and even had my own successful startup before I started Techies.

[00:03:03] So, so I have some experience and what it takes to be successful with a software startup as well. Well, thank you so much for joining me today. And on behalf of every startup founder listening, we've got to dig a little bit deeper on that. So tell me a bit more about this launch first method and how it helps reduce everything from risks, costs and time for startups while also minimizing reliance on investor funding. You're ticking a lot of boxes for founders here, but tell me a bit more about this method. Sure.

[00:03:33] And thanks for asking about it, Neil. It's a favorite subject of mine because I feel like I'm oh founders. I owe founders. You know, they've been big part of my business and anything I can do to help them become successful is something that I should really I should bring forward to them. So. So what I noticed is that founders that fail or software companies that fail, they almost always fail for the same reason.

[00:04:03] And and statistically, they fail 43% of the time because of this. And that's that they lack product market fit. The other and another 40% of the time, depending on the studies you look at, it's because they run out of money. But I believe they run out of money because they lack product market fit. So I believe if you combine both of those around 85% of startups fail because they lack product market fit. So what is product market fit?

[00:04:30] Product market fit means that people will buy your product in enough numbers that your cost of to get to basically to acquire a customer. The marketing and sales cost to acquire customer is roughly one third or less of what the lifetime value of that customer is. So that gives you enough margin then to reinvest back in your business and scale and grow and accelerate.

[00:04:57] And if you don't have that three to one ratio, basically, or and you're not even close, you don't have a viable business. So as I watch startups design, develop products that look like they should be successful and then go out to the market and find out they built the wrong product for the wrong market. This is where most startups fail. They just wait way too long to prove that they've got product market fit.

[00:05:21] And since the only way you can prove you've got product market fit is by generating revenue from sales that it occurred to me that we could do that even before we develop the product. And and so that's where this methodology comes from. That's why it's called launch first launch the sales and marketing engine first before you even build the product.

[00:05:44] I love that. And one of the things that stood out to me when I was researching you looking at your stories that you've been working with software startups for more than 35 years, you've been through so many different trends and cycles. But this time around, it's not the Internet. It's not mobile or mobile apps or digital disruption. Of course, it's the turn of a I that is now transforming the way software and businesses are designed and built.

[00:06:08] So how do you see a development reshaping the software industry and what opportunities and equally challenges does it present for startup founders listening? Well, in a few ways. First of all, this the speed and acceleration of being able to develop a product is changing drastically erratically right now. I wouldn't say it has changed completely.

[00:06:33] It is changing because I is evolving and accelerating so quickly. And I can talk a lot about how that's happening internally in our inside of techies as well, because we're really embracing everything. A.I. in many different respects. And I can talk about what some of those embracement, how we're embracing it.

[00:06:58] But that's the first of all, it's changing how we're developing software and how quickly the software can be developed. But it's also changing what customers are expecting from software very quickly. The world is expecting software to do a lot for them, where before they were just expecting software to be a place where they can do things more easily.

[00:07:25] But that's that is shifting to expecting software to do it for them and to think for them. So the startup market is shifting to these tools that can, as you probably hear about A.I. agents, that are kind of like your friends, your buddies, your assistants, your that are doing things independently for you, sometimes before you even think about them.

[00:07:51] A.I. So the, so it's a huge shift in the market, probably the biggest technology shift I've ever seen bigger than a GPS and bigger than mobile apps. It's the biggest shift I've seen. And so it's affecting everything and it's creating an endless number of opportunities for new products and new concepts that were not possible even three or four years ago.

[00:08:16] A.I. Reading about you before you join me on the podcast today, I've seen you mention artifacts and how they've produced exceptional software development teams. Can you share what these artifacts are just for the non tech is listening and how they contribute to the success of any software project? A.I. Yeah. So let me rephrase that a little bit, if that's okay, Neil.

[00:08:52] A.I. Sure. Cool. A.I. And it's nothing and you never quite get there because you're always striving to be better. A.I. That's how I run my company is that we're never good enough. A.I. We're always working hard to be a better. A.I. And when you're exceptional, you produce certain artifacts naturally as a result of working in an exceptional way that typical teams don't produce.

[00:09:20] A.I. So I always say to people, don't we say we're exceptional. A.I. In fact, when you go to techies.com, you'll see that's kind of our heading or the head of our marquee is a exceptional software, hyper exceptional software development team. A.I. And I don't expect people to believe me when I say that. A.I. I say, let me show you what I mean. A.I. And then I show the artifacts that we produce. A.I. So I'll give you an example of what some of those are. A.I. In our weekly status meetings, which most people do,

[00:09:50] software companies do this when they're building products for people. A.I. They have a weekly or sometimes bi-weekly status meeting, depends on where you are in a project. But we produce a very detailed status report that has things on it like what we accomplished last week versus what we had planned to accomplish last week.

[00:11:09] A.I. So they can't set those expectations. A.I. They don't understand their delivery patterns where to a degree where they can deliver as accurately as that. A.I. And we pride ourselves on being very accurate. A.I. So that means we have to have a pretty detailed estimation methodology, which we do. A.I. So we produce really sophisticated project estimates. A.I. That's another artifact. A.I. Way more detailed than most companies.

[00:11:36] A.I. And I know that because I am friends with lots of other CEOs of other software companies, software development companies. A.I. And when we're talking, we talk about estimates and they say, yeah, we're pretty detailed in our estimates. A.I. And I say, so are we. A.I. And I say, would you like to see how we do it? A.I. Because I like to share. A.I. Maybe I'll learn something from them, but if not, I'm happy to share how we do things.

[00:12:00] A.I. And whenever I show them our estimates every single time, they say, oh, we don't do them anywhere near as detailed as that. A.I. And they start laughing and feel a little uncomfortable because our estimation process is really elaborate, but it's very costly to do it that way. And these are some of the things, you know, we're good at it, but it's still costly. A.I. And because of that, this is where A.I. starts to really play in a factor. We're building an A.I. model.

[00:12:27] In fact, we just finished the first release of it that mimics, basically, helps us produce our estimates using A.I. and helps us even improve on them a little bit. So, like I said, we are embracing A.I. in every aspect of our business. But those are just a couple artifacts, though what I call artifacts that being in what I consider an exceptional company, these are some of the thing artifacts that we produce.

[00:12:55] And it took us years to develop these, the ability to track things at this level of detail that we do to be able to create estimates and be accurate in terms of delivering on time, release after release. Anyway, that's what I mean by being exceptional and what I meant by artifacts.

[00:13:17] And as A.I. accelerates that pace of technological change that we're all seeing, there's so much hype at the moment, it can be challenging telling the difference between fact, fiction and hallucinations and so much more. So how should software development teams better adapt to stay ahead without compromising quality or innovation, for example? Yeah, so that's a good question.

[00:13:41] And I don't know that I have the best answer for that because it's because it's that's difficult to predict how much the state of the art is changing from day to day. We are internally doing exploring how to develop products faster with A.I. We've been benchmarking a number of different approaches for the last six months or so, and we're continually doing this.

[00:14:09] We have a continual effort at it. So now, so if we think of the user interface of an application, there's two aspects of that. There's the visual design component where are the visual layout. And then there's the event management, state management, all of the background stuff that happens on the on the interface itself.

[00:14:33] So those are two halves of the interface and we're about 90 percent, 85 to 90 percent have accelerated the very front end of that on the back end of the front end. We're at about 30 to 35 percent acceleration using A.I. We think we may be able to make a big leap there in the next week or two, but that's where we are on the back end, which is basically build the building,

[00:15:01] the business rules and the server functionality, the microservices architecture and components and everything else. We're at about 35, maybe 40 percent acceleration from where we were six months ago because of A.I. And here's the problem why we can't get to 80 or 90 percent on some of these areas, because, well, most of the things we're building are sophisticated.

[00:15:27] Most of the and everything we build, we build it to be scalable, which means microservices architecture and and component architecture and and making sure things are very discrete so that we can make changes quickly, deploy them independently and also have an automated deployment system with automated testing.

[00:15:50] And there's a lot of aspects to being scalable environment that we that's built into our own DNA of my company. However, when you ask A.I. To build something for you and there are some tools out there that are really cool, like Bolt and Replit and things like that, that can build entire applications for you.

[00:16:14] But they can't get very sophisticated before they start to fall apart, because what happened and the and the architecture of the code that they build is not scalable. It's not it's it's pretty monolithic. It's not maintainable. And, you know, it definitely doesn't come anywhere close to the level of quality we need for our clients. So so so when we're building products. So, for example, what happens with A.I.

[00:16:43] When you're working on more sophisticated things is that it loses the context of of how of every place where something in an application is is touch when you make a change that gets touched downstream. We call that downstream effects.

[00:17:01] So if I want to make a change in a business rule and that has downstream effects in other parts of the application, if when the application gets complex enough, which means the context keeps growing. A.I. forgets that there's other parts of the application that need to be considered because it's gotten too big for it to consider all of it.

[00:17:25] And it doesn't realize that its context has just gone outside of of its known of what it can control. And instead of it stopping and saying, wait, the context has got too big for me. I need to step back and break this into pieces and evaluate each one. First, it doesn't do that. It runs away with this new context and and can break things and can rewrite things that we're working in.

[00:17:54] And and very quickly, you start to get out of control. And so so that's when we have to kind of back up and and control the delivery of how what A.I. is building and writing and and and what it can think about and make sure that we're thinking of all the things it's forgetting. And that's why it's at 30 percent in some aspects of our code development right now.

[00:18:19] If we go back to the beginning of our conversation, I mean, you mentioned that after decades of experience working with startups, you've also identified so many different patterns that contribute to the success or the failure of a startup. Just to go back to that for a moment, can you share some of the common traits of successful startups and maybe some of the pitfalls often lead to finding. OK, so let me first start.

[00:18:44] Yeah, I'll start with the comment, the common traits of successful founders. Love the problem, not the product. So if you if you if you so what happens typically with founders and this is more of the pitfall thing.

[00:19:03] Is they figure they have a problem that there's maybe they're struggling with it personally or they've identified a problem related to somebody they know and they realize an easy way or some way or an elegant way or a clever way to solve that problem. Then they fall in love with the solution and they believe in themselves and they have a vision for how they can take that solution and turn it into a business.

[00:19:33] And they believe in that vision and they think very often that this can be a huge thing, right? A unicorn. And these are all code words for I'm going to fail having being focused on the vision, believing in yourself. Those are good things. But when that becomes your entire reality, you forget about the problem and you forget about the customer. And I see this happening over and over and over again.

[00:20:00] It's a natural tendency that founders have to want to drive forward with their solutions and founders who are consistently successful, especially like serial entrepreneurs. They love the problem. They focus on the customer and they continually talk to the customer about their problems.

[00:20:22] They never talk with them about their solutions because the solution is just the natural mitigation process of solving the problem. So they're not in love with the product. It's just the necessary evil, if you want to say. But they want to spend their time talking with customers, understanding the problems. How did they how have they dealt with that problem in the past? Have they been able to solve it in other ways? Why didn't they continue to use that solve it in that way? What's changed?

[00:20:51] Aren't there other products on the market that solve this problem? Why aren't you using them? Have you tried them? This is what founders who are successful spend their time doing. It's talking with customers about their problems, about how they've solved their problems, about the how much does this problem cost you? Is this something you feel motivated to want to solve? If there was a solution out there, would you be motivated to pursue it? You know, things like that without ever talking about their product or a feature.

[00:21:21] Now, that's a skill set. Some founders just instinctually have this capability. Most do not. The vast majority do not. But the ones that do, they always find a path to success because they know whether they can afford to develop the solution, because they know how much they can sell it for, because they know the value proposition,

[00:21:44] and how impacted their customer is from that problem, and who their customer is because they've talked with enough of them. And looking at your own personal journey there, where you've been building and selling your first software company back in the day, what kind of lessons from your own personal experience still resonate with you today? And how do they influence the way you might mentor startups as well?

[00:22:11] Because you picked up more than a few more stories over the years, I would imagine. So, that's a perfect time for that question too. Because my first software company I started in 92 was logistic. It was like an early ERP kind of for smaller companies, logistics route distribution, inventory management, and financial accountability for all the sales. So, we started that in 90. I was working at Texas Instruments at the time.

[00:22:40] Me and a guy, my partner was also working there. And the two of us thought we could start a software company in this market within Windows. Windows 3.1 was brand new. That was the very first version of Windows that was really usable. And so, we thought we'd come out with a Windows product for smaller companies. And that took off, surprisingly. We were both surprised by how it took off.

[00:23:07] We weren't expecting it really to take off that very quickly. And in eight years, we had 800 customers in 22 countries. And we sold it to a publicly traded firm. And for the next several years, I was VP of products for the acquiring company. So, I thought I knew what I was doing as a startup. And a few years later, I started another software company in the wholesale automobile distribution market.

[00:23:32] Where basically dealerships and car wholesalers could source from each other. Because at the time, there was no way to do that other than through the auctions. So, if you have a customer coming in looking for a particular make model car, there might be a car that was traded in at a dealer or a wholesaler may have just bought a car like that. And you wouldn't know that if you weren't on this network.

[00:23:58] Well, I didn't follow the playbook from my first successful software company. I did it a different way. I was going to go the critical mass and raise money from investor way. I don't know what I was thinking, why I didn't do it the way I did my first company since I was successful. But I didn't recognize that. I didn't recognize exactly what made me successful the first time.

[00:24:25] And so, when I wasn't following that playbook the second time, I did not realize I was going off track or off script. Anyway, so I did get offered the money that I was looking for in investment. That was 1.2 million. I had about 300 customers on the app, but I gave them all free trials because I wanted to build up critical mass on this wholesale trading network, which is also a mistake. There was no reason I needed to do that.

[00:24:53] I could have charged them a subscription fee. They all would have probably paid it or 80% of them, but I was afraid of turning that on before I had the financial investment so that I could accelerate the growth and grow the network. It's fear that often drives failures. And that was true here. I didn't take the investment offer because they wanted way too much equity from my perspective. I had never raised money before.

[00:25:21] I didn't ever get another offer. And so, eventually, I ran out of money and had to close that business. So, I had a success and I had a failure. And I didn't understand exactly what the difference was between the two or make the comparison until I saw a number of other startups make similar failures for the similar reasons.

[00:25:46] And then all of a sudden, I started to realize, oh my God, everybody that's failing, they're all failing because they're just way too long to start to generate revenue from sales. And that's because everybody has this belief that you have to have the product and the market. And sometimes you have to have the network in place and all that before you can start charging. None of that's true. And you've enjoyed a hugely successful career.

[00:26:11] But what I love about you, having listened to your story today, is how you're giving back to the startup community, sharing your knowledge, your insights and experience. And for any entrepreneurs listening, embarking at the very start of their journey, any practical advice that you'd offer to de-risk the process and ensure that their investment in software development ultimately leads to sustainable success? I appreciate it's a massive, massive question. But anything that you would pass on to those people listening?

[00:26:40] Well, yeah, if you start to generate revenue from pre-launch sales, which you can do without a product, you have to have something to show, usually a design prototype or something. And it's got to look realistic, even if it's not. That's a critical success factor because if it doesn't look like a real product when you're demoing it to somebody, then the first question you get from them is, how do I know you can build this? Especially when you're talking about software.

[00:27:09] So, like, if you've seen Kickstarters, which is sort of the mass market version of this, they always have some prototype to demo. They don't have the product yet, but they have something that looks like the product that you can see so you know the product, that there's something real behind it, even if they don't have the product. So you don't have that question, how do I know they're going to be able to build this thing? If it's just a drawing, you're probably not going to be able, they're not going to be successful on Kickstarter.

[00:27:36] I remember there was a Kickstarter I bought into that was a, what do you call those things? A roll-up? A roll-up, like what you use at a gym, a foam roller? Foam roller. Oh, fuck. This was one that would fold up for travel. And I saw the prototype on Kickstarter, a little video on how it worked. I thought, okay, this is cool. It was a year and a half before they actually came out with the product.

[00:28:02] So whatever they had, I think they probably made it from, you know, from plastic that they cut out with an X-Acto knife, but it looked like the real product when they demoed it. So with software, you can do the same thing with iFidelity prototype.

[00:28:21] And it doesn't take, and you can build the whole vision of your product out, not just the MVP, which is minimal viable product, which is what most founders will develop the first time. And that's not a lot of features and that's hard to sell. Your prototype, you can build the whole vision of your product out and just a couple months and go out and start demoing that to potential clients.

[00:28:47] And then if it's realistic enough and you offer them a high enough value opportunity to get in early, they'll buy. And you start to generate revenue and prove that you've got product market fit the right product for the right customer at the right time. And if they're not buying, you can pivot cheaply and quickly because you don't have software that you're having to rewrite. And you can pivot two or three or four times in the space of a couple months until you find that product market fit.

[00:29:14] Or you convince yourself that, you know what, this is the wrong time for the wrong market, the wrong product, whatever it is, and you fail fast and cheap. But assuming that you do find product market fit, which you will find it much more easily in this approach than you would if you've already built your product because of the cost and time it takes to pivot.

[00:29:36] Then you're building up a number of highly invested beta users who will give you real feedback instead of free beta users who don't. And if you do then decide to raise money to accelerate your growth, now you've got traction and revenue and customers that you can show to an investor. And that changes the whole conversation with raising money. Well, thank you so much for sharing your insights with everyone today.

[00:30:05] But before I let you go, I'm going to ask you to leave one final gift to everyone listening. And that is a book that has inspired you or something that you'd recommend that we can add to our Amazon wishlist. All I'm going to ask is what book would you like to leave and why? Okay. It's my favorite business book. It's called The Mom Test.

[00:30:25] And it speaks exactly about the same thing that I've been talking about for a long time, but he puts it into a really good framework. And that is talk about the problems and talk to your customers. Don't talk about your product or your features.

[00:30:44] And it's called The Mom Test because if you came up with a business idea and assuming you have a good relationship with your mother and you ask her what she thinks of your idea, what's she going to say? She's probably going to say, oh, darling, that's wonderful. I think you're so smart. You can make anything happen. I think you'll be really successful with that idea. None of that feedback is helpful or honest. Right.

[00:31:11] It's honest that she loves you, but that's all you get from that. So how would you ask questions about a new business idea that you have from your mother and get valuable feedback from her about that business idea? And the way you do that is you never talk about your business idea or about the product you want to build or about the features that you think would have value. You talk about the problems that your customers have.

[00:31:41] Right. And how they've and you talk about their history with that problem and things like that. Anyway, that's what The Mom Test is about. It's so well done. Everybody should read the book. What a great choice. I'm going to get that added straight to our Amazon wishlist. And for anyone listening wanting to find out more information about you, your work, what we discussed today, where would you like to point everyone listening if they just want to find out more? Well, so I would suggest you go to techies.com.

[00:32:08] That's my corporate website, T-E-K-Y-Z dot com. And anybody that made it this far into the podcast, you can email me directly. And I love to talk with people in the industry, whether they're other software developers or whether they're startups and they just want and they were they're even thinking about starting something. Want some feedback from me. I like talking with everybody. And you can email me at David at techies.com or find me on LinkedIn.

[00:32:38] I'm easy to find on LinkedIn. Awesome. Again, thank you so much. Having founded a successful software company and now honing the launch of your first method, I love how you're sharing unique insights into reducing startup risks and costs and everything in between. So just thank you for sharing that and your practical strategies that you've developed over the years. So valuable for startup founders listening. But thank you for taking the time today. Well, thank you for having me on your show, Neil.

[00:33:07] Having spoken with David today, it seems that startups aren't just about ideas. They're about execution, strategy and understanding customer problems deeply. And David's insights today, I think they highlight why so many startups fail and more importantly, how founders can avoid these pitfalls by just proving demand before development.

[00:33:31] So a huge thank you to David for breaking down how AI is reshaping software development, why founders need to fact, why founders need to focus on traction, not just technology. But over to you. What are your thoughts? How have you seen AI impact software development in unexpected ways? Let's keep this conversation going. Instagram, LinkedIn, X, just at Neil C. Hughes. Let me know your thoughts.