John & Tyler: Is Your Startup Idea Actually Good? AI, Vibe Coding, Steve Blank & Idea Validation

[00:00:00 -> 00:00:23] Because AI is making product building so easy to do and complete and accomplish that his students are getting lazier around lean startup principles saying, look, I don't need to talk to customers because I can just build it so easily that I can throw it away if at the end of the day it doesn't make any sense or it's not working or I'm not hitting the nail right on the head. [00:00:23 -> 00:00:37] We spend most of our time evaluating ideas, don't we, Tyler?

Because if we don't start with a good idea, you can't pre-seed invest in it. And the idea is more than just saying, here's the problem, here's the solution. There's a lot of other elements. [00:01:02 -> 00:01:11] All right.

We are back with an episode of the Startup Ignition podcast. Welcome back. My name is Tyler Richards. I'm your co-host over here with John Richards, my dad.

[00:01:12 -> 00:01:12] Hello. [00:01:12 -> 00:01:17] Also a co-host. Today, we are joined by Nadia. Nobody.

[00:01:17 -> 00:01:36] Because it's just me and my dad in the studio today, we thought we'd come back at you with another hard-hitting startup episode. We love the stories and we love the founders coming into the room, but at the same time, we think it's also great to just share principles, methodologies, strategies, and things that we're seeing within the startup ecosystem that we're in and out of every day. [00:01:36 -> 00:01:38] Do you think everybody speaks Spanish? Nadia?

[00:01:39 -> 00:01:42] Nadia. Nobody. It's kind of English-y. [00:01:42 -> 00:01:42] Okay.

[00:01:43 -> 00:01:46] I don't know where every word comes from, but I know that everything has a Latin root, right? [00:01:46 -> 00:01:47] That's right. [00:01:47 -> 00:01:47] So nobody. [00:01:47 -> 00:01:49] Nadia, that's got to be connected somewhere.

[00:01:50 -> 00:01:51] And this is episode 58? [00:01:52 -> 00:02:07] 58. We are on episode 58 today. Again, it's just going to be me and John today, and we're going to have a great time talking about a cool topic that we think that everybody is searching, looking for, and answer for, at least within the startup realm.

[00:02:07 -> 00:02:17] But before we get to that, even though we have no guests, we're still going to do an icebreaker. We're going to play a game called, What Did AI Do For You This Week? [00:02:17 -> 00:02:30] Because I feel like AI is becoming a part of almost everything we do as founders, almost everything we do as investors, as teachers, as operators, and some of it's... [00:02:30 -> 00:02:31] Family members.

[00:02:31 -> 00:02:40] Some of it's genuinely useful. A lot of it is surprisingly bad. And so today we're going to play, What Did AI Do For You Today? [00:02:40 -> 00:02:41] So here's the first question for John.

[00:02:42 -> 00:02:47] What is one thing you used AI for this week that would have taken you much longer? [00:02:47 -> 00:02:51] Even just two, three, four years ago? [00:02:51 -> 00:02:56] Oh my gosh, there's so many things. Let's see.

I'm just looking at my recent things. First of all... [00:02:56 -> 00:02:58] He's pulling up his AI bot right now. [00:02:59 -> 00:03:07] Yeah, just looking at it.

So I have it hunting for a car for my wife. So it is researching constantly. [00:03:07 -> 00:03:08] Who is my mom? You're going to give mom a new car?

[00:03:08 -> 00:03:09] Maybe. [00:03:09 -> 00:03:09] No. [00:03:09 -> 00:03:10] Okay. [00:03:10 -> 00:03:12] What are you looking for?

[00:03:12 -> 00:03:18] We're just looking for the different types, and we've got it done. And it's doing a cron job. A cron job is a cron job. [00:03:18 -> 00:03:26] A cronological job where it goes and is constantly searching for the type of cars we want, and the best deals, and the values, and what's going on, incentives, all sorts of stuff.

[00:03:26 -> 00:03:27] And it's searching for that all the time. [00:03:29 -> 00:03:40] Also, I have it every day. So today, indeed, it does triage on my email, and it really helps me get through the massive amounts of email I receive. [00:03:41 -> 00:03:46] And I needed it.

I'm now very frequently in box zero because of AI helping me with that. [00:03:46 -> 00:03:48] Yeah, I think that's one of the first. [00:03:48 -> 00:03:57] I also task management. So now all my fathom or note takers from Zoom meetings, all my emails, all my daily activities, it scans all that.

[00:03:57 -> 00:04:06] And then I've created a replica of my Franklin Day Planner system for task management in Google Tasks. [00:04:06 -> 00:04:14] AI completely manages it for me and gives me, if you're familiar with Franklin Planner, ABC system and all that. [00:04:14 -> 00:04:17] And it completely is filling my tasks with what I need to do. [00:04:17 -> 00:04:20] So it's doing that.

There's so much more I could say. [00:04:20 -> 00:04:25] Okay. So, okay. Then what's one thing it's completely done wrong or has gone completely wrong?

[00:04:25 -> 00:04:34] You know, it's a couple of times I've had AI do something for me right before I needed it, and I didn't review it and used it, and it completely blew up in my face. [00:04:34 -> 00:04:36] Yeah, I've seen those ones. [00:04:37 -> 00:04:45] Okay. How about something else?

What's the most ridiculous thing that you've seen AI do recently? [00:04:45 -> 00:04:47] For me and my interactions with it? [00:04:47 -> 00:04:51] Or even anybody that you have seen? [00:04:51 -> 00:04:53] Well, actually, I'm going to be honest.

Lately, AI has made some mistakes. [00:04:54 -> 00:04:56] I've caught it in mistakes, and I say, what are you doing here? [00:04:56 -> 00:04:59] It goes, yeah, you're right. I made a mistake.

I'll correct that and fix it. [00:04:59 -> 00:05:03] The good news is AI then learns from itself. [00:05:03 -> 00:05:05] And it doesn't repeat the mistake again? [00:05:05 -> 00:05:06] Yeah.

[00:05:06 -> 00:05:08] Yeah. Well, how about something? [00:05:08 -> 00:05:14] I know something, ridiculous things that people build or that they're using AI for in their personal life. [00:05:15 -> 00:05:17] Like I go to the gym with a buddy.

[00:05:17 -> 00:05:22] And I see him every once in a while when I go to the open gym. [00:05:22 -> 00:05:25] And he came up and he told me that he has a lighting business. [00:05:26 -> 00:05:36] And so he's built his own application to automatically measure and estimate and give bids for lights on a house. [00:05:36 -> 00:05:37] So like, you know, the permanent lighting.

[00:05:37 -> 00:05:43] And he's like, yeah, I basically just, you know, vibe coded my own lighting bidding app over the weekend. [00:05:43 -> 00:05:45] And he was talking my ear off about that. [00:05:45 -> 00:05:47] And I'm like, wow, that's ridiculous. [00:05:47 -> 00:05:53] It's a very niche, really crazy product, but he's like, yeah, it's, it's saving me hours of time.

[00:05:53 -> 00:05:54] I'm like, wow, that's crazy. [00:05:54 -> 00:05:55] I've built my own apps too. [00:05:55 -> 00:05:56] So I'll take about an app. [00:05:56 -> 00:05:58] So I'm a member of a pickleball group.

[00:05:58 -> 00:05:58] Oh yeah. [00:05:58 -> 00:05:58] Okay. [00:05:59 -> 00:06:01] And it uses Google sheets for signups. [00:06:01 -> 00:06:11] So in other words, you go into a sheet and the sheet, you just, you know, in a, in row a, or excuse me, column a in a row, you add your name in to sign up.

[00:06:11 -> 00:06:16] Well, we had a recent episode where a new user, a female user. [00:06:17 -> 00:06:17] Um, [00:06:17 -> 00:06:25] Um, God came on and overwrote people that already signed up with who she was signing up and eliminated people from the list. [00:06:25 -> 00:06:28] And they got locked out when they were the first signer uppers for this session. [00:06:28 -> 00:06:31] And so that was really a problem and it was happening more and more frequently.

[00:06:32 -> 00:06:39] And this spreadsheet was designed with some techniques to also be able to do a court assignments at the time of starting the session and all that. [00:06:39 -> 00:06:47] And so I just went in and had AI built a dedicated app for this process and every thinks I'm a genius. [00:06:47 -> 00:06:47] They love it. [00:06:47 -> 00:06:51] And it literally works incredibly well and it handles everything.

[00:06:51 -> 00:06:55] And I just had another feature asked of me to do it. [00:06:55 -> 00:06:55] It's so cool. [00:06:55 -> 00:06:59] It, and it actually really works well and now it's set up. [00:06:59 -> 00:07:04] So it just goes and he's doubly the pickleball master, not just for skills, but for now his app that he built.

[00:07:04 -> 00:07:14] And what's cool is it, you know, sends it to get hub automatically, and then it deploys it on a Vercel and I have an app and I just, and it works and it worked great. [00:07:14 -> 00:07:17] That's a really interesting case, but it really did. [00:07:17 -> 00:07:17] It makes. [00:07:17 -> 00:07:23] It makes everything run smoother in this pickleball group and this pickleball group has, you know, 180 members in it.

[00:07:23 -> 00:07:23] Wow. [00:07:23 -> 00:07:25] That's, that's actually pretty useful. [00:07:25 -> 00:07:26] I'm actually impressed that you've done that. [00:07:26 -> 00:07:27] Okay.

[00:07:27 -> 00:07:28] Um, okay. [00:07:28 -> 00:07:30] So one more thing. [00:07:30 -> 00:07:33] So what did AI do for you this week? [00:07:33 -> 00:07:48] One more thing has AI changed anything that you, any workflow or personal life thing or business life thing outside of email and writing.

[00:07:48 -> 00:07:48] Yes. [00:07:49 -> 00:07:50] What? [00:07:50 -> 00:07:52] Analysis of massive amounts of data. [00:07:52 -> 00:07:55] So in venture capitalists, we use it to do stuff.

[00:07:56 -> 00:07:56] Yeah. [00:07:56 -> 00:08:02] I'm just trying to think of anything outside of like language or writing golf calculation. [00:08:02 -> 00:08:03] Oh yeah. [00:08:03 -> 00:08:04] I built that golf app.

[00:08:04 -> 00:08:05] You did a golf app. [00:08:05 -> 00:08:09] And what I do for golf is I take a picture, it's getting crazy. [00:08:09 -> 00:08:11] I can't even remember all the apps that I've built. [00:08:11 -> 00:08:13] I literally cannot remember what I've been doing.

[00:08:13 -> 00:08:18] I build something, throw it away, build something, deploy it, forget that I even built it. [00:08:18 -> 00:08:18] I've trained by AI. [00:08:19 -> 00:08:19] Yeah. [00:08:19 -> 00:08:34] I send it to my agent, my personal assistant to, if I send it to the two, the front nine and the back nine scorecard, and it now is trained, I just take a photo, send it in, and it gives me a complete infographic of who owes what money in our golf group.

[00:08:35 -> 00:08:35] Yeah. [00:08:35 -> 00:08:37] That's, I like that. [00:08:37 -> 00:08:37] I enjoy that one. [00:08:37 -> 00:08:39] I'm a user of that app.

[00:08:39 -> 00:08:41] Um, it's just crazy. [00:08:41 -> 00:08:49] The, the mix of impressive things that AI can do with the mix of unreliable things that [00:08:49 -> 00:08:50] it can do is crazy. [00:08:50 -> 00:08:52] Cause one day I'll just be completely impressed. [00:08:53 -> 00:08:57] And then the next day I'll be completely unimpressed and have a completely different.

[00:08:57 -> 00:08:59] Here's another one that I use. [00:08:59 -> 00:09:00] That's big, important, hard. [00:09:01 -> 00:09:02] I'm a hard money lender. [00:09:02 -> 00:09:05] So I do high interest loans to businesses that are in cash crunches.

[00:09:05 -> 00:09:05] Yep. [00:09:06 -> 00:09:09] And so when things happen on that, it reviews paperwork. [00:09:10 -> 00:09:12] It, um, gives me best practices. [00:09:12 -> 00:09:13] It protects me.

[00:09:14 -> 00:09:19] And when there's, uh, it calculates the payoff amounts and double checks and triple checks. [00:09:19 -> 00:09:20] It goes into spreadsheets. [00:09:20 -> 00:09:24] It goes into the documents, um, saving me massive amounts of time. [00:09:24 -> 00:09:28] And I have to check up on it, make sure it's correct, but it does 90% of the work.

[00:09:28 -> 00:09:30] And I do 10% now when I used to do a hundred percent. [00:09:31 -> 00:09:33] And I think founders can relate to this too. [00:09:33 -> 00:09:38] I mean, I, I gotta assume that active operating founders, even though we are founders have [00:09:38 -> 00:09:42] been founders, we're not actively operating our own startups or tech startups or apps. [00:09:43 -> 00:09:49] Um, but I gotta assume this is impacting everybody on every level in any kind of [00:09:49 -> 00:09:51] niche, in any kind of market, in any kind of product.

[00:09:52 -> 00:09:52] It's just crazy. [00:09:53 -> 00:09:57] So, yeah, that was just, I just wanted to see what AI was up to this week with you because [00:09:57 -> 00:10:00] I know you're infinitely implementing AI and [00:10:00 -> 00:10:01] significant purchases. [00:10:01 -> 00:10:03] I haven't researched all of my significant purchases. [00:10:03 -> 00:10:04] Yeah, that too.

[00:10:04 -> 00:10:06] I'm of course doing that. [00:10:06 -> 00:10:07] Okay. [00:10:07 -> 00:10:10] We can move into real quick, just recent startup news. [00:10:10 -> 00:10:12] I wanted to bring up something because we don't have a guest today.

[00:10:12 -> 00:10:14] It's just me and you, and we have a little bit of time here. [00:10:14 -> 00:10:18] I thought something that was really cool that was talked about back in July. [00:10:19 -> 00:10:23] Um, there was an article that came out, I think it was tech crunch or crunch base that [00:10:23 -> 00:10:30] reported on July 2nd, the global startup investments, um, VC reached approximately [00:10:31 -> 00:10:34] $510 billion during the first half of 2026. [00:10:35 -> 00:10:40] So like an all time high for a half year increment in 2026, a lot more than I would [00:10:40 -> 00:10:42] have thought it was 510 billion.

[00:10:42 -> 00:10:43] That's a lot. [00:10:43 -> 00:10:48] Obviously a lot concentrated in a couple of ideas of deals. [00:10:49 -> 00:10:51] It wasn't, you know, a ton of deals. [00:10:51 -> 00:10:57] It was maybe the top three AI companies or large that had large funding rounds, but crunch [00:10:57 -> 00:11:02] base came out and said, that's the most ever venture capital invested in a single [00:11:02 -> 00:11:04] half of year really surprises me.

[00:11:04 -> 00:11:05] Yeah, that's a large number. [00:11:05 -> 00:11:09] Cause I, I, you know, I've been a venture capitalist and an venture investor for, you [00:11:09 -> 00:11:12] know, multiple decades and that's a very high number. [00:11:12 -> 00:11:16] So it's kind of contradicting it in a way that a lot of founders are saying, Hey, you [00:11:16 -> 00:11:19] know, venture capital is so hard to run. [00:11:19 -> 00:11:19] It's so hard to raise right now.

[00:11:19 -> 00:11:21] It's really hard to get a check. [00:11:21 -> 00:11:29] And then you see numbers coming out with $510 billion and there's enormous amounts of capital, [00:11:29 -> 00:11:32] obviously out there, but that can create a false impression. [00:11:32 -> 00:11:39] I think because those dollars are really concentrated in these privately held huge AI [00:11:39 -> 00:11:42] companies that are getting massive amounts of capital. [00:11:42 -> 00:11:47] Open AI did $110 billion, $110 billion round one round.

[00:11:47 -> 00:11:54] So does a massive increase in that AI funding mean that there's, there's going to be more [00:11:54 -> 00:11:56] great startups down the road? [00:11:56 -> 00:12:00] Like, will those VC dollars trickle out to the venture and startup community? [00:12:00 -> 00:12:06] Or is it just mean that these startups that are building right now, trying to raise right [00:12:06 -> 00:12:12] now are competing for the same capital that those massive capital takers are hoarding [00:12:12 -> 00:12:13] to themselves?

[00:12:13 -> 00:12:15] Like where, how do you see it? [00:12:15 -> 00:12:16] Are you going to see this as beneficial? [00:12:16 -> 00:12:21] Is it beneficial for VC or that this is kind of not a great thing because it's just concentrated [00:12:21 -> 00:12:23] in like there can only be five top deals only be so many winners. [00:12:23 -> 00:12:24] There's going to be a lot of losers.

[00:12:24 -> 00:12:31] A lot of it, it's a land grab and it's like, you know, uh, when the United States went [00:12:31 -> 00:12:35] from 13 colonies and expanded westward, there were huge winners that went and grabbed the [00:12:35 -> 00:12:36] land and got the land. [00:12:36 -> 00:12:40] And there were people that went out and didn't get any land and didn't win the lottery from [00:12:40 -> 00:12:42] the government for land and they didn't win. [00:12:42 -> 00:12:45] And so there's gonna be winners and losers is how it's going to be just like always.

[00:12:45 -> 00:12:46] I went through. [00:12:46 -> 00:12:51] Through the PC revolution in the late seventies, early eighties, and everybody thought all [00:12:51 -> 00:12:54] the jobs are going to disappear because these personal computers replaced everybody at their [00:12:54 -> 00:12:58] jobs that didn't happen, created more productivity, more things happening, but there were winners [00:12:58 -> 00:12:59] and losers. [00:12:59 -> 00:13:00] Then I went through the internet revolution.

[00:13:01 -> 00:13:04] Everybody thought the internet was going to put all businesses out of business and this [00:13:04 -> 00:13:05] and that. [00:13:05 -> 00:13:07] I mean, the same things we're hearing about AI right now. [00:13:07 -> 00:13:08] It didn't come true. [00:13:08 -> 00:13:12] We humans just got more productive, did more cool things and created a bigger economy.

[00:13:12 -> 00:13:15] More productivity is the productivity increases that were incredible. [00:13:15 -> 00:13:16] But. [00:13:16 -> 00:13:16] Yeah. [00:13:16 -> 00:13:17] There were lots of winners and lots of losers.

[00:13:18 -> 00:13:23] I think the AI thing is maybe the biggest of all of these events because they're building [00:13:23 -> 00:13:25] on top of one another, but it's going to be the same thing. [00:13:25 -> 00:13:30] We're going to figure out where AI really fits into the human equation and there'd be [00:13:30 -> 00:13:31] winners and losers. [00:13:31 -> 00:13:36] Well, we had my dad and I, we had a family reunion this last week and we were up in the [00:13:36 -> 00:13:39] middle of, uh, the forest and a hike.

[00:13:39 -> 00:13:42] And we were just, our, our topic of conversation was like, at what point do we think AI is [00:13:42 -> 00:13:44] going to take over the world? [00:13:44 -> 00:13:46] And we basically boiled it down to. [00:13:46 -> 00:13:51] That they have to, uh, have infinite access to energy to be able to supply to themselves, [00:13:52 -> 00:13:56] to take over the human race and the doomsday doomsday types talking. [00:13:56 -> 00:14:00] But obviously there's a ton of excitement around AI.

[00:14:00 -> 00:14:04] There is a lot of productivity output and product output. [00:14:04 -> 00:14:10] Um, there's more capital than ever, ever flowing into this new product and this new, [00:14:10 -> 00:14:15] the, these new innovations of AI, but at the same time, the. [00:14:15 -> 00:14:22] The core principles of startup building and foundational, the startup has to be good [00:14:22 -> 00:14:26] and has to be, the idea has to be good. [00:14:26 -> 00:14:27] The product, the team, everything has to be good.

[00:14:27 -> 00:14:34] And that will transition me to what I wanted to bring the topic of today's podcast of, which [00:14:34 -> 00:14:40] is what makes a good startup, what makes a good startup idea and starting out with in [00:14:40 -> 00:14:45] today's world, in today's world, but starting that out with a very recent article from. [00:14:45 -> 00:14:49] From Steve Blank that I think, did I send to you? [00:14:49 -> 00:14:53] I sent it to you and he's done a follow-up to that now, and now he has even done a follow-up [00:14:53 -> 00:14:54] to it, blank, the father of lean startup.

[00:14:54 -> 00:14:58] So the lean startup was brought to the world by Steve Blank. [00:14:58 -> 00:15:05] So on AI on June 16th of this year, Steve Blank put out and published an article titled [00:15:06 -> 00:15:11] lean launch pad, 2026 at Stanford lessons learned presentations. [00:15:12 -> 00:15:15] And for anyone who does not know who Steve Blank is, we talk about. [00:15:15 -> 00:15:15] Yeah.

[00:15:15 -> 00:15:20] He's one of the most influential thinkers around lean startup and customer development [00:15:20 -> 00:15:21] and the whole lean startup movement. [00:15:22 -> 00:15:28] But he has established this idea that startups are not just large companies to operate. [00:15:29 -> 00:15:31] They're actually their own smaller beast. [00:15:31 -> 00:15:40] And he runs a class at Stanford and he wrote an awesome article about the lean launch pad [00:15:40 -> 00:15:45] class that he teaches at Stanford in 2011 and the 2026 class.

[00:15:45 -> 00:15:51] Was it 16th year that he had ran this startup class, this lean, what's it called? [00:15:51 -> 00:15:53] The launch pad class at Stanford. [00:15:53 -> 00:16:01] And during this 2026 quarter, eight student teams collectively spoke with 978 potential [00:16:01 -> 00:16:02] customers. [00:16:02 -> 00:16:07] And the most interesting part of this article is he was talking about and analyzing how [00:16:07 -> 00:16:14] AI has impacted the ease of the lean startup movement, how it has changed since 2000.

[00:16:14 -> 00:16:20] 11 to 2026 in the 15 years or 16th year now that he's been running this class at Stanford [00:16:20 -> 00:16:26] and how it's changed the whole strategy around MVP development, product development. [00:16:26 -> 00:16:34] But he continues to say in this article that he wrote back in June that it's the first [00:16:34 -> 00:16:41] time he's fully seen his class implement AI in this product building ease and that the [00:16:41 -> 00:16:44] lean startup principles are more important now.

[00:16:44 -> 00:16:51] Now than ever, he's saying, because AI is making product building so easy to do and [00:16:51 -> 00:16:57] complete and accomplish that his students are getting lazier around lean startup principles [00:16:57 -> 00:17:03] saying, look, I don't need to talk to customers because I can just build it so easily that [00:17:03 -> 00:17:08] I can throw it away if at the end of the day, it doesn't make any sense or it's not [00:17:08 -> 00:17:10] working or I'm not hitting the nail right on the head.

[00:17:10 -> 00:17:12] And this is such a great read. [00:17:12 -> 00:17:14] And I wanted to set the table with. [00:17:14 -> 00:17:18] This going over this article, did you have any thoughts on this article? [00:17:19 -> 00:17:22] I think it's a landmark article in case they Steve Blank shared.

[00:17:23 -> 00:17:28] The bottom line is I'm seeing it every day just because you can whip up an MVP in a [00:17:28 -> 00:17:34] weekend and product is no longer really the mode it used to be, does not mean that you [00:17:34 -> 00:17:39] should have built the product and that there's any customers that care about that product. [00:17:39 -> 00:17:44] You still have to validate customer demand and that a customer feels [00:17:44 -> 00:17:48] that you're solving their problem and they'll part with money for you.

[00:17:48 -> 00:17:54] And there's a psychosis going on, in my opinion, that when an entrepreneur vibe codes a [00:17:54 -> 00:17:58] product over a weekend to an MVP level, that feels really good. [00:17:58 -> 00:18:06] They are somehow conjecturing to themselves that they have validated the business [00:18:06 -> 00:18:09] model that they've gone out and talked to customers. [00:18:10 -> 00:18:12] I asked them, what customers did you talk to? [00:18:12 -> 00:18:14] Did you validate that with them?

[00:18:14 -> 00:18:14] Will they partner? [00:18:14 -> 00:18:15] Will they part with money for this? [00:18:15 -> 00:18:17] And they haven't talked to anybody. [00:18:17 -> 00:18:18] They just had an idea.

[00:18:20 -> 00:18:24] They've maybe identified the problem, haven't validated the problem, haven't [00:18:24 -> 00:18:26] validated that the customer will pay money for it to, for the solution. [00:18:26 -> 00:18:28] And that's really interesting. [00:18:28 -> 00:18:32] So it used to mean, you know, that an MVP proved a technical ability. [00:18:34 -> 00:18:38] Um, but really it's just proven that, you know, how to vibe code over a weekend.

[00:18:38 -> 00:18:38] Right. [00:18:38 -> 00:18:45] I don't, I don't think product pro progress is the same thing as like business progress or [00:18:45 -> 00:18:45] business. [00:18:46 -> 00:18:46] Model progress, right? [00:18:47 -> 00:18:49] That there's, those are two separate things just because you can build it [00:18:49 -> 00:18:51] quickly, doesn't mean that it's good.

[00:18:51 -> 00:18:52] And I think, and it could be impressive. [00:18:53 -> 00:18:57] You might be able to build something really impressive, but that doesn't mean [00:18:57 -> 00:18:58] there's a customer that cares about it. [00:18:58 -> 00:18:59] Yeah. [00:18:59 -> 00:19:02] And just because you prove it and just because you have a finished looking [00:19:02 -> 00:19:06] product, it doesn't mean that it's market ready or that it's a good, that it [00:19:06 -> 00:19:10] actually is a, uh, uh, uh, product market fit product.

[00:19:10 -> 00:19:16] We used to say before AI's vibe coding capabilities that in lean startup, [00:19:16 -> 00:19:22] principles, we would say building a product without validating customers first is a form [00:19:22 -> 00:19:23] of waste. [00:19:24 -> 00:19:31] So just because we can build something much faster now, doesn't mean it's still not a [00:19:31 -> 00:19:34] form of waste, especially if it tricks you into thinking you're validating when you're [00:19:34 -> 00:19:35] really not.

[00:19:35 -> 00:19:39] That's the thing had the speed of which you build a product does not change that. [00:19:39 -> 00:19:41] Maybe you shouldn't have built that product. [00:19:41 -> 00:19:47] So, I mean, you've lived through and you just talked about it previously through the internet, [00:19:47 -> 00:19:54] through SaaS, through mobile, through cloud, through now AI, is this just the same movie [00:19:54 -> 00:19:55] over and over? [00:19:55 -> 00:20:05] Like, are we entranced with this AI quick to build phenomenon that, you know, we are [00:20:05 -> 00:20:07] being tricked that AI is as impactful as it is?

[00:20:07 -> 00:20:09] Well, first of all, let's look at the $510 billion. [00:20:09 -> 00:20:10] Okay. [00:20:10 -> 00:20:15] We have to remember during the COVID era, the governments of the world printed more money in [00:20:15 -> 00:20:16] two years than had been created. [00:20:17 -> 00:20:17] Yeah.

[00:20:17 -> 00:20:21] Created more money in two years than had been created in the previous 200 years. [00:20:21 -> 00:20:22] I think I saw the stat. [00:20:22 -> 00:20:26] It was like the dollars lost like 40% of worth since that time. [00:20:26 -> 00:20:26] Yeah.

[00:20:26 -> 00:20:29] So there's just so much more money in circulation. [00:20:29 -> 00:20:35] So the fact that venture capital investment has increased by a huge percentage. [00:20:36 -> 00:20:37] It's actually 40% not increased. [00:20:37 -> 00:20:39] The available money in the world has increased by a few percentage.

[00:20:40 -> 00:20:41] So inflation. [00:20:41 -> 00:20:46] So that means that $510 billion spent this six months of 2026. [00:20:47 -> 00:20:51] If we go back 20 years ago, how much would that have been equivalent there? [00:20:51 -> 00:20:52] It's inflation.

[00:20:52 -> 00:20:53] It's just so we have to remember. [00:20:54 -> 00:20:59] And so, yes, I think this is just the same movie, but with different characters and a [00:20:59 -> 00:20:59] different timeframe. [00:20:59 -> 00:21:03] For instance, the Gartner hype cycle, Tyler, which you know about, and we've talked about, [00:21:03 -> 00:21:05] if you don't know what the Gartner hype cycle, you should look it up. [00:21:05 -> 00:21:10] It means there's a disruptive technology and then the disruptive technology goes up to a [00:21:10 -> 00:21:16] peak of inflated expectations and falls into a trough of disillusionment, then goes through a [00:21:16 -> 00:21:17] slope of enlightenment.

[00:21:17 -> 00:21:19] And finishes on a plateau of productivity. [00:21:20 -> 00:21:23] This has been the pattern over all disruptive technology. [00:21:23 -> 00:21:28] AI may be the most disruptive technology we've ever seen, but it's going to go through the same [00:21:28 -> 00:21:28] thing. [00:21:29 -> 00:21:30] And we're seeing that.

[00:21:31 -> 00:21:33] I think people are already learning. [00:21:33 -> 00:21:36] AI is not going to wipe out the human race in two years. [00:21:36 -> 00:21:41] AI is not going to wipe out all business and commerce in the next three years. [00:21:42 -> 00:21:43] It's just not going to happen.

[00:21:44 -> 00:21:46] They said the same things with personal computers. [00:21:47 -> 00:21:48] They said the same thing with AI. [00:21:48 -> 00:21:48] They said the same thing with the internet. [00:21:48 -> 00:21:49] And this is what happens.

[00:21:49 -> 00:21:50] We overreact. [00:21:50 -> 00:21:52] Humans just do this type of thing. [00:21:52 -> 00:22:02] So the Gartner hype cycle is going to continue to be true, but this could be one of the most greatest cases of disruption. [00:22:02 -> 00:22:03] Yes.

[00:22:03 -> 00:22:13] So it's no doubt that AI makes things easier to build, but it does not make the customers care any more than before. [00:22:13 -> 00:22:13] No. [00:22:13 -> 00:22:14] Like. [00:22:14 -> 00:22:17] Especially if the customer can do some of the things you're building for themselves.

[00:22:17 -> 00:22:18] Yeah. [00:22:18 -> 00:22:30] So if AI has empowered you as the entrepreneur to bring this value to the market, I'm pretty sure the customer themselves can tap into that same AI power and build that value for themselves, right? [00:22:30 -> 00:22:30] Yes. [00:22:30 -> 00:22:40] That's the whole, the whole problem, you know, is SaaS dead or not that we've talked about a bunch on this podcast, but then again, also a lot of people aren't going to want to build their own stuff, so there'll be some market for it.

[00:22:40 -> 00:22:40] Right. [00:22:40 -> 00:22:47] But that leads me exactly into a great transition to, into the topic of today's podcast, which is how do you know? [00:22:47 -> 00:22:55] So whether your startup idea is actually good or not in today's era, right? [00:22:55 -> 00:23:11] How do we not experience this Steve blank experience in his class that he's been teaching for 16 years that we have this fallacy of, because I can build it so easily and fast that it is good and ready.

[00:23:11 -> 00:23:16] So how do we know whether your startup idea is actually good? [00:23:16 -> 00:23:18] And that's what we want to. [00:23:18 -> 00:23:20] Talk about today, because most founders begin with an idea. [00:23:21 -> 00:23:25] Every founder has an idea and they see something they could build.

[00:23:25 -> 00:23:28] They see maybe a potential market that they could bring it to. [00:23:28 -> 00:23:33] They can, they they've identified a new technology that they could bring to a market. [00:23:33 -> 00:23:44] But the thing is just because there's an idea, it doesn't really necessarily mean that there is an opportunity or a startup opportunity around that idea. [00:23:44 -> 00:23:46] So I have a question for you.

[00:23:46 -> 00:23:46] Yep. [00:23:46 -> 00:23:47] Dad. [00:23:47 -> 00:23:48] Okay. [00:23:48 -> 00:23:56] Hey, John, what separates a legitimate startup opportunity from an interesting product idea?

[00:23:57 -> 00:24:05] Like what, what is separates a good idea or an interesting idea to an actual opportunity, a startup opportunity. [00:24:05 -> 00:24:11] So a good startup idea is not just something that can be built just because you can build, it doesn't automatically make it good. [00:24:11 -> 00:24:15] It is a piece of it, but doesn't mean that it's automatically good. [00:24:15 -> 00:24:16] So has to be.

[00:24:17 -> 00:24:28] There's a customer out there that has the problem you think they have, and they're willing to part with money for your solution to help them overcome that problem. [00:24:29 -> 00:24:39] So they have an obstacle, your service or product will help them get over that obstacle and they'll pay you money for that, that, that truly exists. [00:24:39 -> 00:24:44] You hypothesize it, then go through a series of experiments to find out if it's true. [00:24:44 -> 00:24:46] Then it becomes a great idea.

[00:24:46 -> 00:24:47] Yeah. [00:24:47 -> 00:24:51] Just because it can be built, does not make it have those elements. [00:24:52 -> 00:24:57] So for instance, I think, I think an idea sits at an intersection, right? [00:24:57 -> 00:25:06] Where you have, um, a customer, um, that has a, uh, a pain or a problem, right?

[00:25:06 -> 00:25:08] We've all talked about our need or a need, right? [00:25:09 -> 00:25:15] We've talked about good ideas usually exist around pains, problems, or needs of a customer base, right? [00:25:15 -> 00:25:16] And. [00:25:16 -> 00:25:33] There needs to be an, an urgency to satisfy that pain, problem, or need, and therefore you can solve that for the customer and they have a willingness to, to pay for that solution for that solving of a pain, problem, or need.

[00:25:33 -> 00:25:41] And if you can find something that fits in that kind of intersection, usually there's a meaningful business behind there somewhere. [00:25:41 -> 00:25:44] Usually you can work out some kind of business model. [00:25:44 -> 00:25:46] You build out, you know, all of that. [00:25:46 -> 00:25:57] All the factors of a business model in that area somewhere in that kind of trifecta or quad quadrant of where the intersection of all those things come together.

[00:25:57 -> 00:25:57] Right. [00:25:57 -> 00:26:06] That's, that's where I think good ideas start and actually evolve from not just a good idea, but into a actual startup opportunity. [00:26:06 -> 00:26:07] Yeah. [00:26:07 -> 00:26:15] And, you know, you've got to have all the fundamentals, like you gotta, you basically have to have a lot of pain, the more pain, the better.

[00:26:15 -> 00:26:16] Yeah. [00:26:16 -> 00:26:16] And you're solid. [00:26:16 -> 00:26:17] And you're solving a big problem. [00:26:17 -> 00:26:18] So then it'll be a bigger opportunity.

[00:26:19 -> 00:26:25] And, you know, all the things, the buyers or the customers have to have the budget and the availability to pay for it. [00:26:25 -> 00:26:28] You got to make it so it's a profitable, good unit economics. [00:26:28 -> 00:26:33] All the things that we talk about, market size, distribution, all that has to come present. [00:26:34 -> 00:26:46] The bottom line is this, talking in the spirit of vibe coding and what it's leading to, technology can make it possible to build it, but that does not make the problem important to anybody.

[00:26:46 -> 00:26:47] So you have to have a customer. [00:26:47 -> 00:26:55] You have to have verified, validated that there's a customer with the problem and they will pay for the solution. [00:26:55 -> 00:26:56] Then you build it. [00:26:56 -> 00:26:59] You don't build it and hope that's going to happen.

[00:26:59 -> 00:27:01] That's the fundamental principles of lean startup. [00:27:01 -> 00:27:06] And obviously the fundamental principles of founder of product market fit. [00:27:06 -> 00:27:07] Yes. [00:27:07 -> 00:27:07] Right.

[00:27:07 -> 00:27:08] It's synonymous with. [00:27:08 -> 00:27:08] Yeah. [00:27:09 -> 00:27:14] And so I guess one of the things we're saying, Tyler, and I hope the entrepreneurs are getting this because we're running into it every day. [00:27:14 -> 00:27:14] That.

[00:27:14 -> 00:27:21] That basic business principles, basic entrepreneurial principles, basic lean startup methodologies and principles do not go away. [00:27:22 -> 00:27:27] They become more important when technology is enabling you to build products so fast. [00:27:27 -> 00:27:33] I think, I think there's a mindset that founders need to maybe switch a little bit. [00:27:33 -> 00:27:38] It's not like a question of what can I build or, you know, what can I do?

[00:27:38 -> 00:27:43] It's more like, uh, who urgently needs something solved? [00:27:44 -> 00:27:44] Like who. [00:27:45 -> 00:27:55] Um, you know, who, who can I impact by changing the way that they do something today to bring them value and solve something for them? [00:27:55 -> 00:27:59] So don't just sit around and think, what, what, what can I tinker and build?

[00:27:59 -> 00:28:08] It's like, no, go, go identify a customer that has a problem and solve it for them. [00:28:08 -> 00:28:10] That's where good ideas usually start. [00:28:11 -> 00:28:15] Don't just sit around in your four bedroom, four wall bedroom. [00:28:15 -> 00:28:15] And.

[00:28:15 -> 00:28:18] And say, what's something cool I can do. [00:28:18 -> 00:28:24] You, you really do have to do what Steve Blank says, the author of the article back in June, talking about how AI has actually. [00:28:25 -> 00:28:32] Exacerbated the problem of a product market fit and lean startup that it's even more prevalent in today's era. [00:28:32 -> 00:28:36] But Steve Blank literally says his famous quote is get out of the building, right?

[00:28:36 -> 00:28:38] Don't just sit in your room and think, okay, what can I do? [00:28:38 -> 00:28:43] No, go find a customer with a pain, but Tyler, I don't like talking to humans. [00:28:43 -> 00:28:43] Yeah. [00:28:43 -> 00:28:45] See, that's, that's something we.

[00:28:45 -> 00:28:50] We run up against it's, it's funny, but maybe you got to think about what kind of entrepreneur that you are. [00:28:50 -> 00:29:01] Like, are you the kind of person that you need motivation to get out of the building and you need to take your time and think about how you're going to have conversations with, with people? [00:29:01 -> 00:29:04] Or are you the kind of entrepreneur that maybe is like, I'm just to go do it. [00:29:04 -> 00:29:06] I'm going to go, I'm going to go and do it.

[00:29:06 -> 00:29:06] I'm a doer. [00:29:06 -> 00:29:08] I'm just going to get off my butt and do it. [00:29:08 -> 00:29:15] So I, I do think there are people that experience that kind of painful, it's like pulling teeth to go and talk to people. [00:29:15 -> 00:29:36] Or interact and get face to face, which is totally fine, but you do at some point need to build up the confidence to say, okay, if I want to push ahead this idea or build my startup or become a business owner and actually have a good idea, what makes a good idea is a good business opportunity to, to find that you have to get out of the building.

[00:29:36 -> 00:29:36] You really do. [00:29:36 -> 00:29:37] Yeah. [00:29:37 -> 00:29:40] There's so many thoughts going through my head right now, but I want to share this one. [00:29:40 -> 00:29:42] Let's take a case in point with us.

[00:29:42 -> 00:29:44] We, uh, we're from Utah. [00:29:45 -> 00:29:51] Utah has been one of the great bastions of the world for, uh, in the cloud B2B SAS type services. [00:29:51 -> 00:29:58] And there's been a lot of talk about SAS again and the demise of SAS and all that, but here's what's happening. [00:29:58 -> 00:30:02] We're seeing, I like to say this way, part of a good idea, Tyler.

[00:30:03 -> 00:30:15] And I think that's part of your question today is if you can take a workflow, meaning how somebody gets something done, how a group, a team, an individual gets something done. [00:30:15 -> 00:30:29] And take a workflow and change the economics of the workflow so that the one conducting that workflow saves money or makes more money, then you've got a great business. [00:30:29 -> 00:30:29] Yeah. [00:30:29 -> 00:30:30] So that's the key.

[00:30:30 -> 00:30:41] So if AI and vibe coding and this new era of rapid product development can help you just get there faster, then it's fantastic. [00:30:41 -> 00:30:46] But just because you can do something, you have to say, have I changed? [00:30:46 -> 00:30:53] I changed the workflow truly and being compelling that it's a compelling economic opportunity for the person that needs to do that workflow. [00:30:53 -> 00:30:57] And is that workflow just a nicety or is it a must have workflow?

[00:30:57 -> 00:31:14] So like what you and I are looking for right now, Tyler, and anybody out there that has a solution is if there's a must have workflow where there's a business that cannot survive without that workflow and you can drop the cost of that workflow by 90% or you can improve the outcome revenue from that workflow by 100%. [00:31:15 -> 00:31:15] Please come. [00:31:16 -> 00:31:16] Talk to us. [00:31:16 -> 00:31:16] Right.

[00:31:16 -> 00:31:17] That's a good idea. [00:31:18 -> 00:31:21] Well, that goes back to validation, too. [00:31:21 -> 00:31:27] Like, I don't think the purpose of validation is to prove that your idea is right. [00:31:27 -> 00:31:33] It's to discover which parts of your idea are wrong and where you're getting it wrong.

[00:31:33 -> 00:31:42] Like the whole principle behind lean startup and customer discovery and idea validation is starting with a hypothesis. [00:31:42 -> 00:31:44] What you think is right. [00:31:44 -> 00:31:45] What you think is a good idea. [00:31:46 -> 00:31:54] Validating it over time with people, with subjects, asking them what they think about it, and then concluding, OK, was I right or was I wrong?

[00:31:54 -> 00:32:05] So I think it's not so much like proving that your idea is right as much as like finding what's wrong and pivoting from there to perfect it into a great opportunity. [00:32:05 -> 00:32:08] So so we've covered customer. [00:32:08 -> 00:32:09] We've covered workflow. [00:32:11 -> 00:32:14] And we also like to use the word hair on fire.

[00:32:14 -> 00:32:15] Like the customer. [00:32:15 -> 00:32:17] Customer has to have some urgency in this. [00:32:17 -> 00:32:21] You don't want it to take two years for them to fiddle around and make a decision. [00:32:21 -> 00:32:29] You need to identify a kind of hair on fire use case that they there's some urgency involved here or your startup won't get off the ground.

[00:32:29 -> 00:32:29] Yeah. [00:32:29 -> 00:32:30] So that's a piece. [00:32:30 -> 00:32:32] And then I'll finish three other things. [00:32:32 -> 00:32:33] So customer.

[00:32:34 -> 00:32:37] The workflow we talked about urgency in the mind of the customer. [00:32:37 -> 00:32:40] And what's the behavior of the customer right now? [00:32:40 -> 00:32:45] And what and is there a workaround or something that you can improve? [00:32:45 -> 00:32:59] And do and is there a commitment you can get out of the customer like, for instance, a lot of people are starting companies these days and they're getting free beta testers or whatever, and they never come out of that free beta tester.

[00:33:00 -> 00:33:06] It's not great to spend a year or two of your life and you only get a beta customer try for free, but they'll never pay you for it. [00:33:06 -> 00:33:10] Yeah, yeah, that's happening in some companies we're seeing and we want to see them get to that. [00:33:10 -> 00:33:12] And last, just can you create a business around this? [00:33:12 -> 00:33:13] Can it be profitable?

[00:33:14 -> 00:33:15] Remember, you have to. [00:33:15 -> 00:33:19] Operate a profit, your expenses need to be less than your revenue eventually at some point. [00:33:19 -> 00:33:22] And so is there a real business here and look at it? [00:33:22 -> 00:33:27] So we we have a very we spend most of our time evaluating ideas, don't we, Tyler?

[00:33:27 -> 00:33:33] Because if we don't start with a good idea, you can't precede, invest in it. [00:33:33 -> 00:33:36] And the idea is more than just saying, here's the problem, here's the solution. [00:33:37 -> 00:33:38] There's a lot of other elements to it anyway. [00:33:39 -> 00:33:39] Yeah.

[00:33:39 -> 00:33:45] So I like those those things that you're listening about how to find and and massage. [00:33:45 -> 00:33:48] An idea or at least find an idea that's that's a good business opportunity. [00:33:48 -> 00:34:01] But I think a lot of times founders start a little bit too broadly when they go out and do this founders often try to please everybody and be something for everybody. [00:34:01 -> 00:34:15] I think actually narrowing down your customer is one of the best things you can do and then see if there's an opportunity with that smaller customer of that smaller segment instead of going out and saying, I'm going to be.

[00:34:15 -> 00:34:19] You know, I think narrowing it down to me, you know, some kind of product for everybody in the world. [00:34:19 -> 00:34:24] I think narrowing it down to know this product is specifically for this subset of U.S. [00:34:24 -> 00:34:35] Citizens that are male, that are 18 to 24, that like to be online and play this type of word game is like the best concentration and narrowing that you can do.

[00:34:36 -> 00:34:45] You it's a huge self-service to say, OK, I know exactly who I need to talk to, where I need to go and what this needs to be and what kind of questions I need to ask rather than just saying. [00:34:45 -> 00:34:46] than being something super, super broad. [00:34:46 -> 00:34:47] So I love those points, [00:34:47 -> 00:34:49] but I think narrowing it down [00:34:49 -> 00:34:53] into a more concentrated effort [00:34:53 -> 00:34:54] will be really helpful for founders.

[00:34:54 -> 00:34:55] We coach all the time on this, don't we? [00:34:55 -> 00:35:01] Because narrowing doesn't mean that it's a small idea. [00:35:01 -> 00:35:04] It just means you know that in the next six to 12 months [00:35:04 -> 00:35:04] as a startup, [00:35:05 -> 00:35:08] you need to find a narrower use case customer [00:35:08 -> 00:35:10] that can really get behind you [00:35:10 -> 00:35:12] and buy your product or service. [00:35:12 -> 00:35:13] And we call that a wedge.

[00:35:13 -> 00:35:16] So just because Tyler's saying [00:35:16 -> 00:35:17] we got to narrow things down [00:35:17 -> 00:35:20] doesn't mean that it's a small idea or insignificant. [00:35:21 -> 00:35:23] And also we need to find a wedge. [00:35:23 -> 00:35:24] We can't say, oh, in five years from now, [00:35:24 -> 00:35:26] I'm going to have all this revenue [00:35:26 -> 00:35:27] and I'm going to take care of all these customers. [00:35:28 -> 00:35:30] Well, I want to know in the next six to 12 months, [00:35:30 -> 00:35:32] what customers are you going to get [00:35:32 -> 00:35:34] that'll help you survive that first year?

[00:35:35 -> 00:35:36] Yeah, that's important. [00:35:36 -> 00:35:40] And I think it gives the startup a clearer place to begin. [00:35:40 -> 00:35:42] It gives a better picture [00:35:42 -> 00:35:45] and an easier task list to tackle [00:35:45 -> 00:35:48] if they say, well, an example that we had [00:35:48 -> 00:35:49] even just today, this morning, [00:35:49 -> 00:35:50] we had a pitch this morning [00:35:50 -> 00:35:57] from a software that is in the dog space [00:35:57 -> 00:35:59] where they were saying, [00:35:59 -> 00:36:01] oh, and we could go here, we could do this.

[00:36:01 -> 00:36:03] We could be something for groomers. [00:36:03 -> 00:36:06] We could be something for trainers. [00:36:06 -> 00:36:08] We could be something for veterinarians. [00:36:08 -> 00:36:10] Yeah, on boarding houses and all this stuff.

[00:36:10 -> 00:36:12] And I think our feedback, [00:36:12 -> 00:36:15] our feedback was, no, you need to narrow in. [00:36:15 -> 00:36:16] You need to say, okay, [00:36:16 -> 00:36:19] you can't be the same thing for a groomer and a trainer. [00:36:21 -> 00:36:24] It's better to be master of one than master of none. [00:36:24 -> 00:36:24] Right.

[00:36:24 -> 00:36:28] So I think even that pitch this morning, [00:36:28 -> 00:36:29] our feedback to them was, [00:36:29 -> 00:36:32] I actually think you should go after your lowest hanging fruit. [00:36:32 -> 00:36:35] You should go after the subset of the market [00:36:35 -> 00:36:37] that you think you could tackle and know the best about [00:36:37 -> 00:36:40] and go and master that one first. [00:36:40 -> 00:36:42] And I think if you take that, [00:36:42 -> 00:36:44] kind of concentration of efforts [00:36:44 -> 00:36:46] across all of your validation [00:36:46 -> 00:36:48] from ideation all the way up into execution, [00:36:49 -> 00:36:51] you'll be way more on the ball of, [00:36:51 -> 00:36:53] I know exactly where I need to be.

[00:36:53 -> 00:36:55] I know exactly who my customer is. [00:36:55 -> 00:36:56] I know exactly the features I need to build. [00:36:56 -> 00:36:59] I know exactly what kind of questions [00:36:59 -> 00:37:00] and market validation I need to be doing [00:37:00 -> 00:37:02] rather than being all over the place [00:37:02 -> 00:37:03] and starting super broad. [00:37:03 -> 00:37:05] How about for a pitch deck example?

[00:37:05 -> 00:37:06] So some tips. [00:37:06 -> 00:37:10] If you're pitching to a pre-seed or seed venture fund [00:37:10 -> 00:37:12] or angel investors, [00:37:12 -> 00:37:14] instead of saying, [00:37:14 -> 00:37:15] here's my grand idea [00:37:15 -> 00:37:17] and I'm going to have a hundred million revenue [00:37:17 -> 00:37:19] and this is where it's going to be in five years. [00:37:20 -> 00:37:22] That's not what we want to hear as much as you say, [00:37:23 -> 00:37:23] okay, that's great.

[00:37:24 -> 00:37:25] What I want to hear is, [00:37:26 -> 00:37:29] what is, how am I going to get a beachhead? [00:37:29 -> 00:37:32] What's the hair and fire use case in my customer's need? [00:37:32 -> 00:37:33] And how am I going to, [00:37:33 -> 00:37:35] how are you going to create a beachhead [00:37:35 -> 00:37:37] and get that wedge into the market [00:37:37 -> 00:37:38] and find your position in the market [00:37:38 -> 00:37:40] and take care of those customers [00:37:40 -> 00:37:42] and get to where you're generating revenue [00:37:42 -> 00:37:43] and you can do it profitably.

[00:37:43 -> 00:37:46] And then where are you going to end up five, seven, [00:37:46 -> 00:37:47] 10 years from now? [00:37:47 -> 00:37:48] Fantastic. [00:37:48 -> 00:37:50] But where are you at a year from now? [00:37:50 -> 00:37:50] Yeah.

[00:37:50 -> 00:37:52] An even better example, [00:37:52 -> 00:37:55] an actual example is a really hot thing [00:37:55 -> 00:37:56] that we've come across over the last year [00:37:56 -> 00:37:58] is AI in sales. [00:37:58 -> 00:38:01] And there's so many people building platforms, [00:38:01 -> 00:38:06] tools and software for AI implementation in sales. [00:38:06 -> 00:38:08] But that's such a broad category. [00:38:08 -> 00:38:11] You're going to be an AI for any and all sales.

[00:38:11 -> 00:38:12] We don't know. [00:38:12 -> 00:38:13] We'd rather you come to us and say, [00:38:13 -> 00:38:16] I want to build an AI for HVAC installers [00:38:16 -> 00:38:20] to follow up with lost estimate leads [00:38:20 -> 00:38:22] and help them within 15 minutes. [00:38:22 -> 00:38:23] If you come and tell us that, [00:38:23 -> 00:38:25] that's way better than saying, [00:38:25 -> 00:38:27] well, I'm going to be an AI for sales [00:38:27 -> 00:38:28] for every single category, [00:38:28 -> 00:38:29] every single service, [00:38:29 -> 00:38:31] every single sales department everywhere.

[00:38:32 -> 00:38:33] That's way too broad. [00:38:33 -> 00:38:34] Here's where we sit right now. [00:38:35 -> 00:38:36] This horizontal versus vertical, [00:38:37 -> 00:38:39] hopefully this stands the test of time [00:38:39 -> 00:38:40] because this is being recorded. [00:38:40 -> 00:38:41] But right now, [00:38:41 -> 00:38:44] what we're seeing is horizontal solutions [00:38:44 -> 00:38:48] are really under threat from the frontier LLMs.

[00:38:48 -> 00:38:51] The AI companies could easily create [00:38:51 -> 00:38:53] an embedded service, [00:38:54 -> 00:38:55] just like Microsoft's old days [00:38:55 -> 00:38:58] where they would build into the operating system [00:38:58 -> 00:38:58] new release [00:38:58 -> 00:39:01] and kill a bunch of vertical companies [00:39:01 -> 00:39:04] because they could easily add that in there [00:39:04 -> 00:39:06] because those companies were being horizontal [00:39:06 -> 00:39:07] with their vertical approach [00:39:07 -> 00:39:09] and they were killed by the horizontal play [00:39:09 -> 00:39:11] that Microsoft would release a new.

[00:39:11 -> 00:39:11] Now, [00:39:11 -> 00:39:12] where it is, [00:39:12 -> 00:39:14] I wouldn't want to have invested in [00:39:14 -> 00:39:16] or start a company that's very horizontal [00:39:16 -> 00:39:19] and have open AI or Anthropic or Google [00:39:19 -> 00:39:22] release that in their next LLM version [00:39:22 -> 00:39:23] that makes it so easy [00:39:23 -> 00:39:24] that they don't need me anymore. [00:39:24 -> 00:39:26] But a hyper verticalized one, [00:39:26 -> 00:39:28] I was at a VC meeting recently [00:39:28 -> 00:39:29] and I'm just going to say [00:39:29 -> 00:39:30] one of the VCs [00:39:30 -> 00:39:32] when we were having the same type of discussion [00:39:32 -> 00:39:33] came out and said, [00:39:33 -> 00:39:37] hey, my father-in-law's a big earning orthodontist, [00:39:37 -> 00:39:39] makes a lot of money putting in kids' braces.

[00:39:41 -> 00:39:42] He is not going to vibe, [00:39:42 -> 00:39:44] his own practice management software [00:39:44 -> 00:39:46] for his orthodontist practice. [00:39:46 -> 00:39:48] He's not going to hire somebody [00:39:48 -> 00:39:51] to vibe code his custom practice management software. [00:39:51 -> 00:39:54] He's going to use the best practice management software [00:39:54 -> 00:39:55] to run an orthodontist office [00:39:55 -> 00:39:56] and that's what he's going to do [00:39:56 -> 00:39:59] so he can continue making lots of money doing that.

[00:39:59 -> 00:40:01] Highly verticalized software like that [00:40:01 -> 00:40:02] is not going to go away. [00:40:02 -> 00:40:04] Now, he does expect [00:40:04 -> 00:40:07] that somebody is going to make a better product [00:40:07 -> 00:40:09] for maybe a lower price point for himself [00:40:09 -> 00:40:10] as an orthodontist. [00:40:10 -> 00:40:11] There's going to be pricing pressure [00:40:11 -> 00:40:12] and competition [00:40:12 -> 00:40:14] and competition on that [00:40:14 -> 00:40:15] but he's not going to vibe code that for himself [00:40:15 -> 00:40:18] because that's core to his business [00:40:18 -> 00:40:19] and he's not going to do that.

[00:40:19 -> 00:40:23] But if you're making a sales tool [00:40:23 -> 00:40:26] that's for 10 million different types of businesses [00:40:26 -> 00:40:28] and in thousand different verticals, [00:40:28 -> 00:40:32] that's where OpenAI, Gemini, and Anthropic [00:40:32 -> 00:40:33] could easily crush you. [00:40:33 -> 00:40:34] Yeah, so again, [00:40:34 -> 00:40:37] I think the learning principle here [00:40:37 -> 00:40:41] is narrowing in and concentrating in [00:40:41 -> 00:40:42] doesn't mean something.

[00:40:42 -> 00:40:45] We don't mean go for small markets. [00:40:45 -> 00:40:47] We just mean narrow in [00:40:47 -> 00:40:49] and concentrate your efforts [00:40:49 -> 00:40:51] into a lowest hanging fruit, [00:40:51 -> 00:40:52] the hair on fire customer [00:40:52 -> 00:40:55] where you can really provide a solution for [00:40:55 -> 00:40:59] and then go and tackle next to markets [00:40:59 -> 00:41:02] or other kinds of features [00:41:02 -> 00:41:03] or adding on whatever it is.

[00:41:04 -> 00:41:05] Let's tell a story without naming names. [00:41:05 -> 00:41:06] We have a portfolio company [00:41:06 -> 00:41:09] that was doing pretty well [00:41:09 -> 00:41:11] and then they found a feature [00:41:11 -> 00:41:12] that got them some good stuff. [00:41:12 -> 00:41:13] Good sales, some good sales. [00:41:13 -> 00:41:14] I was going based on that feature.

[00:41:14 -> 00:41:16] They had something other competitors didn't have. [00:41:17 -> 00:41:21] But recently they embedded an AI service [00:41:22 -> 00:41:24] into their offering, their platform. [00:41:25 -> 00:41:29] And that changed a workflow for their customer [00:41:30 -> 00:41:33] that basically saved 99% of the cost of that workflow. [00:41:33 -> 00:41:36] And they are on fire [00:41:36 -> 00:41:38] and they are literally on fire [00:41:38 -> 00:41:41] to the point where they are signing up stuff [00:41:41 -> 00:41:42] we never imagined they would sign up.

[00:41:43 -> 00:41:46] Okay, so we've talked about all of these, [00:41:46 -> 00:41:48] what makes a good idea, [00:41:48 -> 00:41:50] a good idea versus a bad idea [00:41:50 -> 00:41:52] or what actually makes an idea [00:41:52 -> 00:41:53] an actual business opportunity. [00:41:53 -> 00:41:55] You went over a couple of bullet points. [00:41:55 -> 00:41:57] We then talked about narrowing in [00:41:57 -> 00:41:59] and helping concentrate your efforts. [00:41:59 -> 00:42:00] What else?

[00:42:00 -> 00:42:02] What else can we talk about [00:42:02 -> 00:42:03] with the viewers and listeners today [00:42:04 -> 00:42:06] about what makes a good idea [00:42:07 -> 00:42:11] and a good opportunity in today's AI era? [00:42:12 -> 00:42:13] Piggybacking off of Steve Blank's, [00:42:13 -> 00:42:17] article piggybacking off of our methodologies. [00:42:17 -> 00:42:20] What else could we share with the viewers and listeners? [00:42:20 -> 00:42:22] Well, as a long time teacher of Lean Startup, [00:42:22 -> 00:42:25] I would say use AI to increase [00:42:26 -> 00:42:29] and speed up your validation [00:42:29 -> 00:42:32] and discovery of customer problems [00:42:32 -> 00:42:34] and their desire for your solution [00:42:34 -> 00:42:35] and their ability to pay.

[00:42:35 -> 00:42:38] Use that to speed up Lean Startup [00:42:38 -> 00:42:40] to get to the validation [00:42:40 -> 00:42:43] and the scientific proof of product market fit, [00:42:43 -> 00:42:46] not just to go build a product that's invalidated, [00:42:46 -> 00:42:47] that hasn't been validated. [00:42:47 -> 00:42:49] Okay, so I get what you're saying. [00:42:49 -> 00:42:53] So you're saying don't use AI to build product faster [00:42:53 -> 00:42:55] that could be bad or the wrong product.

[00:42:55 -> 00:42:59] Use AI to speed up your validation efforts. [00:42:59 -> 00:43:02] Utilize it to assist you in that whole endeavor. [00:43:03 -> 00:43:05] We like to say it this way, Tyler, [00:43:05 -> 00:43:07] you still need to earn the right to build. [00:43:07 -> 00:43:08] Right.

[00:43:08 -> 00:43:10] But the good news is you can use AI [00:43:10 -> 00:43:12] to speed up the earning of the right [00:43:12 -> 00:43:13] to build. [00:43:13 -> 00:43:16] So imagine using AI first to speed up [00:43:16 -> 00:43:17] finding product market fit [00:43:18 -> 00:43:22] and then using AI to build your first validated product. [00:43:22 -> 00:43:23] This sounds like a great time [00:43:23 -> 00:43:25] to plug the Startup Ignition Tool Suite. [00:43:25 -> 00:43:25] Yeah.

[00:43:26 -> 00:43:28] And that's not the purpose of this conversation at all. [00:43:28 -> 00:43:30] Yeah, we built a tool suite to help with that, right? [00:43:30 -> 00:43:31] But yeah, again, [00:43:31 -> 00:43:34] I go back to the point that I shared earlier [00:43:34 -> 00:43:34] in this podcast, [00:43:34 -> 00:43:36] which is that this whole, [00:43:37 -> 00:43:41] the whole point of validation is to find [00:43:42 -> 00:43:45] what's wrong with your first stab at an idea.

[00:43:46 -> 00:43:48] And the quicker you can do that, [00:43:48 -> 00:43:51] the more tools, the AI assistance [00:43:51 -> 00:43:53] that can get you through that process faster [00:43:54 -> 00:43:57] will ultimately get you to what is the end goal, [00:43:57 -> 00:43:58] which is a great business model, [00:43:58 -> 00:44:00] which is a flourishing startup, [00:44:01 -> 00:44:04] which is a product that customers actually want to buy. [00:44:04 -> 00:44:07] So can I bring up one point too?

[00:44:07 -> 00:44:07] Yeah. [00:44:07 -> 00:44:08] It's kind of like that. [00:44:08 -> 00:44:11] Steve Blank in the article you started this podcast on, [00:44:11 -> 00:44:12] this episode, [00:44:12 -> 00:44:15] he brought up something really important. [00:44:15 -> 00:44:18] He has concluded as one of the leading, [00:44:18 -> 00:44:20] if not the leading educator in lean startup [00:44:20 -> 00:44:21] and entrepreneurial education, [00:44:22 -> 00:44:25] he brought up that he discovered this last semester [00:44:25 -> 00:44:26] at Stanford, [00:44:26 -> 00:44:29] that he would change the lean startup diagram [00:44:29 -> 00:44:31] of the product development model [00:44:31 -> 00:44:35] and bring together the lean startup process itself [00:44:35 -> 00:44:36] is getting compressed.

[00:44:36 -> 00:44:37] So it's like I said, [00:44:37 -> 00:44:39] use AI to speed up lean startup [00:44:39 -> 00:44:41] and product market fit discovery. [00:44:41 -> 00:44:42] So what he said, [00:44:42 -> 00:44:44] literally in that article, [00:44:44 -> 00:44:47] as he concluded was you're going to now involve the customer [00:44:48 -> 00:44:50] as a co-designer of the product [00:44:51 -> 00:44:53] because product can be done so fast [00:44:53 -> 00:44:54] and you can involve the customer.

[00:44:54 -> 00:44:58] Used to be a company would disappear in a room [00:44:58 -> 00:45:01] and the engineers would be sitting at their cubicle desk [00:45:01 -> 00:45:04] and create product, not involving the customer. [00:45:04 -> 00:45:06] But now all along the way, [00:45:06 -> 00:45:07] you can involve the customer [00:45:07 -> 00:45:08] because you can vibe code so fast. [00:45:09 -> 00:45:11] And like I did this pickleball app I said, [00:45:11 -> 00:45:12] I've had tons of feedback.

[00:45:12 -> 00:45:13] I got feedback from that group [00:45:13 -> 00:45:15] and I add the features they want [00:45:15 -> 00:45:17] and they're co-developing the product with me. [00:45:17 -> 00:45:18] That's what it is. [00:45:18 -> 00:45:19] And so literally, [00:45:19 -> 00:45:21] I think that's a really important thing [00:45:21 -> 00:45:25] is that we can now involve the customer more also [00:45:25 -> 00:45:27] in the building of the product. [00:45:27 -> 00:45:28] They're co-building it with us.

[00:45:28 -> 00:45:29] It's fascinating. [00:45:29 -> 00:45:31] Something we always tell investments, [00:45:32 -> 00:45:34] mentees, people who have come through our bootcamp [00:45:34 -> 00:45:37] and startups that are just beginning, [00:45:37 -> 00:45:40] we tell them to go find that customer base [00:45:40 -> 00:45:41] that you're talking about. [00:45:41 -> 00:45:42] We say, go find, one, two, three, four, five, six, seven, [00:45:42 -> 00:45:45] one, two, three, up to maybe five customers [00:45:45 -> 00:45:48] that you can use basically as your laboratory [00:45:48 -> 00:45:50] to figure things out, [00:45:50 -> 00:45:55] to go and draw experiments and run against them and say, [00:45:56 -> 00:45:57] is this good or is this bad?

[00:45:58 -> 00:46:00] Validation doesn't just stop in a conversation [00:46:00 -> 00:46:03] in a conference room, asking them survey questions. [00:46:04 -> 00:46:05] It goes through product development [00:46:06 -> 00:46:08] and staying and having those kinds of customers [00:46:08 -> 00:46:12] where you can ask and ping multiple times a week, [00:46:12 -> 00:46:17] even through the day, every day is a way that you end up [00:46:17 -> 00:46:19] with a really, really good polished product [00:46:19 -> 00:46:22] that people or that customer base will actually want.

[00:46:22 -> 00:46:25] So what you're saying is instead of going out [00:46:25 -> 00:46:28] and signing up 40 customers and promising them [00:46:28 -> 00:46:30] that a product be ready by a certain time, [00:46:30 -> 00:46:33] and you can onboard them in six weeks, [00:46:33 -> 00:46:37] why don't you just get five that you say [00:46:37 -> 00:46:40] they really are interested, they really want it, [00:46:40 -> 00:46:41] they believe in what you're doing, [00:46:41 -> 00:46:43] and you work with those five, [00:46:43 -> 00:46:46] and you iron out all the wrinkles, how you service them, [00:46:46 -> 00:46:48] how you take care of them, what the pricing should be, [00:46:48 -> 00:46:52] and you get those five over a few months really nailed down, [00:46:53 -> 00:46:55] then go sign up the next 35, [00:46:55 -> 00:46:57] and you know exactly what you're doing [00:46:57 -> 00:46:58] and you can take care of them.

[00:46:59 -> 00:47:00] That's what we kind of say. [00:47:00 -> 00:47:01] Yeah, that's what we do say, [00:47:01 -> 00:47:02] but that's because that's usually [00:47:02 -> 00:47:04] the typical experience of a founder. [00:47:04 -> 00:47:08] There are a lot of founders and products and ideas [00:47:09 -> 00:47:12] that you can go rush out and sign up a ton of customers, [00:47:13 -> 00:47:13] and that's what we do. [00:47:13 -> 00:47:15] We're kind of talking B2B a little bit.

[00:47:15 -> 00:47:16] Yeah, there's B2C that you can do that on. [00:47:16 -> 00:47:19] Yeah, there's B2C, but even sometimes B2B, [00:47:19 -> 00:47:24] but where the product solution is so valuable or so great [00:47:25 -> 00:47:27] that the customer base is just clawing for it, [00:47:27 -> 00:47:31] and they're willing to work through kinks and mistakes [00:47:31 -> 00:47:33] because they need it so badly. [00:47:33 -> 00:47:35] So I don't think the message there should say, [00:47:35 -> 00:47:38] oh, if you can go sell this to 40 people, you shouldn't.

[00:47:41 -> 00:47:43] I'm saying, what we're saying is, [00:47:43 -> 00:47:44] if you're not at that point yet [00:47:44 -> 00:47:47] where your product is flushed out and market ready, [00:47:47 -> 00:47:49] yes, put the brakes on, [00:47:49 -> 00:47:52] but if your market is willing to, [00:47:52 -> 00:47:55] in a mass volume and high numbers, [00:47:55 -> 00:47:59] sign up and pay you money and be forgiving [00:47:59 -> 00:48:02] because they want it that badly, that's not a bad thing.

[00:48:02 -> 00:48:04] It's a little bit back to the elephant versus unicorn. [00:48:05 -> 00:48:07] Just getting a pile of money, [00:48:07 -> 00:48:09] going out and trying to sign up as many people, [00:48:09 -> 00:48:10] and hopefully it all turns out well [00:48:10 -> 00:48:11] and works as a hard business. [00:48:11 -> 00:48:12] That changes the story. [00:48:12 -> 00:48:15] If you're spending money to get those customers [00:48:15 -> 00:48:18] and you're burning through cash to do that, that's very bad.

[00:48:18 -> 00:48:21] If you are getting that organically [00:48:21 -> 00:48:23] where word of mouth is spreading [00:48:23 -> 00:48:25] or the customer base is telling more people [00:48:25 -> 00:48:26] in the customer base, [00:48:26 -> 00:48:28] and it's just growing like a snowball effect, [00:48:29 -> 00:48:29] that's a great thing. [00:48:29 -> 00:48:31] But more often than not, we're gonna say, [00:48:31 -> 00:48:33] get a few customers, iron out the wrinkles, [00:48:33 -> 00:48:34] figure things out.

[00:48:34 -> 00:48:38] Yes, and those five customers are literally your laboratory. [00:48:38 -> 00:48:40] This is not a celebratory, [00:48:40 -> 00:48:42] hey, we've made it, a victory lap. [00:48:42 -> 00:48:43] This is, no, you are still learning, [00:48:44 -> 00:48:45] asking questions and experimenting. [00:48:46 -> 00:48:47] Music to my ears.

[00:48:47 -> 00:48:47] Right. Yes. [00:48:48 -> 00:48:48] I like that. [00:48:48 -> 00:48:52] Okay, now we've gone over all the way up [00:48:52 -> 00:48:57] from what makes a good idea versus a business, [00:48:57 -> 00:48:59] a real true business opportunity.

[00:48:59 -> 00:49:03] We've gone through validation, Steve Blank's article, [00:49:04 -> 00:49:05] narrowing in on your customer, [00:49:06 -> 00:49:08] talking more in your validation, [00:49:08 -> 00:49:12] using AI not to product build so much as to speed up [00:49:12 -> 00:49:12] your business. [00:49:12 -> 00:49:13] We've gone through your validation efforts, [00:49:13 -> 00:49:17] and all the way down to getting your first couple [00:49:17 -> 00:49:17] of customers on.

[00:49:18 -> 00:49:19] What else? [00:49:19 -> 00:49:21] What else can we share with them [00:49:21 -> 00:49:25] that makes a good idea in today's AI era? [00:49:25 -> 00:49:26] What other learnings can we part with [00:49:26 -> 00:49:29] with the few minutes that we have left for this episode? [00:49:30 -> 00:49:33] Well, I wanna make sure and caution everybody [00:49:33 -> 00:49:35] to not misinterpret what we're saying.

[00:49:35 -> 00:49:38] We're not saying that you should go slow [00:49:38 -> 00:49:41] and plotting as a startup in all respects. [00:49:41 -> 00:49:44] No, because you don't wanna also take four years [00:49:44 -> 00:49:47] to get to where you could be in six months. [00:49:47 -> 00:49:48] Hold on, before you finish that thought, [00:49:48 -> 00:49:51] because we did have a call with another startup guru [00:49:51 -> 00:49:57] right before this filming of this podcast with Ash Mora, [00:49:57 -> 00:50:00] we had a awesome conversation with him.

[00:50:00 -> 00:50:02] We're very close to him and talk shop with him [00:50:02 -> 00:50:05] and connect on Lean Startup Principles and Methodology. [00:50:05 -> 00:50:07] He's doing great things over in his ecosystem [00:50:07 -> 00:50:08] as well as here in Startup Ignition. [00:50:09 -> 00:50:11] But I do think sometimes we, [00:50:11 -> 00:50:15] kind of take the route of a little bit more surety [00:50:16 -> 00:50:19] and we do pause a little bit more [00:50:19 -> 00:50:23] to make sure that the entrepreneur has a lot of their T's [00:50:23 -> 00:50:25] crossed and their I's dotted, [00:50:26 -> 00:50:28] where I felt like a little bit from Ash, [00:50:28 -> 00:50:31] he's like, I don't wanna slow down the entrepreneur.

[00:50:31 -> 00:50:34] And so I like what you're saying is that [00:50:35 -> 00:50:38] don't misinterpret all of this messaging as slow down [00:50:38 -> 00:50:41] and go slow and be super methodical, cause no, [00:50:41 -> 00:50:42] part of being a startup [00:50:42 -> 00:50:43] and part of being an entrepreneur and a founder [00:50:43 -> 00:50:49] is moving fast and getting out to market and being nimble. [00:50:49 -> 00:50:54] But we definitely take the slower methodical route sometimes.

[00:50:54 -> 00:50:57] What Ash was saying is if there's somebody that says, [00:50:57 -> 00:50:58] oh, I know what I'm doing [00:50:58 -> 00:51:00] and I'm not gonna slow down for this Lean Startup Process. [00:51:01 -> 00:51:03] He says, he just lets them go forward [00:51:03 -> 00:51:07] and then they're sure enough gonna run into something [00:51:07 -> 00:51:09] and have to come back and fix things. [00:51:09 -> 00:51:11] Where I think my dad and I's approach, [00:51:11 -> 00:51:13] Startup Ignition's approach is a little bit slower [00:51:13 -> 00:51:16] because we've been down those paths personally.

[00:51:17 -> 00:51:19] I've been down those paths as an entrepreneur. [00:51:20 -> 00:51:22] You've been down those paths where you've gotten burned [00:51:22 -> 00:51:25] to millions of dollars burned. [00:51:25 -> 00:51:27] And myself with projects being burned [00:51:27 -> 00:51:30] and whole ideas being burned because I've moved too quickly. [00:51:30 -> 00:51:35] And so I think our intention is we see what happens.

[00:51:35 -> 00:51:37] So let's just stop and prevent that pivot [00:51:37 -> 00:51:41] and then do it correctly from the jump where Ash is like, [00:51:41 -> 00:51:43] you know, approach might be, let them go. [00:51:43 -> 00:51:45] I'm not here to slow down an entrepreneur. [00:51:45 -> 00:51:47] They're gonna come back and realize that they were wrong. [00:51:47 -> 00:51:50] So over the last few years of being venture capitalist, Tyler, [00:51:50 -> 00:51:52] one of the, and I refer to this quite a bit.

[00:51:52 -> 00:51:55] There's a few companies that we really liked, [00:51:55 -> 00:51:57] even the team and the idea and everything, [00:51:57 -> 00:52:00] but they wanted to raise more money [00:52:00 -> 00:52:01] than we thought they needed. [00:52:01 -> 00:52:03] And they went out and raised that money. [00:52:03 -> 00:52:04] Yeah, many times. [00:52:04 -> 00:52:06] Three companies I can think of [00:52:06 -> 00:52:08] within about a nine month period that that happened on.

[00:52:09 -> 00:52:11] And in checking up with them later, almost to a T, [00:52:11 -> 00:52:11] Yeah. And in checking up with them later, almost to a T, [00:52:11 -> 00:52:14] they burned about two thirds of their money. [00:52:15 -> 00:52:17] And one of the founders leaves [00:52:17 -> 00:52:21] and they pivot to a new, basically a brand new start. [00:52:22 -> 00:52:22] Brand new idea.

[00:52:22 -> 00:52:25] And so let's say, you know, [00:52:25 -> 00:52:27] so our thing is saying, [00:52:27 -> 00:52:29] if you would have just followed [00:52:29 -> 00:52:31] a little bit more disciplined principles, [00:52:31 -> 00:52:34] you wouldn't have had to squander the two thirds [00:52:34 -> 00:52:35] of the capital you raised [00:52:35 -> 00:52:36] before you realized you needed to pivot. [00:52:37 -> 00:52:41] It's just a lot cheaper to pivot earlier than later. [00:52:41 -> 00:52:42] I think.

[00:52:42 -> 00:52:45] I think we agree on fundamentals there, [00:52:45 -> 00:52:48] but I do think we disagree a little bit [00:52:48 -> 00:52:51] of how quickly founders can be moving from discovery [00:52:51 -> 00:52:53] into building a little bit. [00:52:53 -> 00:52:55] Like, for example, [00:52:55 -> 00:52:57] do you think founders today [00:52:57 -> 00:52:59] are building too quickly in general? [00:53:01 -> 00:53:04] Like, do you think today's typical founder [00:53:05 -> 00:53:07] are jumping the gun and building too quickly?

[00:53:07 -> 00:53:11] Do I think that, okay, I'm interpreting the question as, [00:53:11 -> 00:53:16] do I think that founders are building too quickly [00:53:16 -> 00:53:18] without having validated first? [00:53:18 -> 00:53:21] And I'm saying, yes, I do think that. [00:53:21 -> 00:53:21] Yeah, yeah, yeah. [00:53:21 -> 00:53:21] Yeah.

[00:53:22 -> 00:53:25] But do you think there is a founder that has [00:53:26 -> 00:53:28] or can validate quickly and build quickly? [00:53:28 -> 00:53:31] But that's probably the exception, not the rule. [00:53:31 -> 00:53:31] Yeah, it's the exception. [00:53:31 -> 00:53:33] Also, their opportunity might be fleeting.

[00:53:33 -> 00:53:35] Like for instance, I don't like, [00:53:35 -> 00:53:37] like there is the story of the one guy [00:53:37 -> 00:53:41] that created the GLP online e-commerce solution. [00:53:41 -> 00:53:43] And he's making hundreds of millions of dollars [00:53:43 -> 00:53:45] and it's just him with a vibe coated. [00:53:45 -> 00:53:45] Oh yeah, the peptide guy. [00:53:46 -> 00:53:47] Yeah, whatever it is, right?

[00:53:47 -> 00:53:49] And there's stories like that out there. [00:53:49 -> 00:53:50] I think those opportunities are fleeting. [00:53:50 -> 00:53:55] So are we at risk of slowing down the entrepreneur [00:53:55 -> 00:53:58] and slowing the founders down too cautiously? [00:53:58 -> 00:54:01] It depends if what you- [00:54:01 -> 00:54:02] Because I do think- [00:54:02 -> 00:54:05] If we feel raising more money than you need as a, [00:54:05 -> 00:54:11] if raising a ton of money is a symbol of success [00:54:11 -> 00:54:13] and that's the success in and of itself, [00:54:13 -> 00:54:16] then we are slowing them down from that point of success.

[00:54:16 -> 00:54:18] No, but I think Ash's comments today [00:54:18 -> 00:54:20] were very eyeopening for me where he's like, [00:54:20 -> 00:54:21] no, I'm not here to slow down an entrepreneur. [00:54:21 -> 00:54:23] If they want to run, let them run. [00:54:23 -> 00:54:23] Yeah, let them run. [00:54:23 -> 00:54:26] But he also said in the same concluding breath [00:54:26 -> 00:54:28] that he knows they're going to come back [00:54:28 -> 00:54:29] and run into problems because of it.

[00:54:29 -> 00:54:30] And I do think we let entrepreneurs run. [00:54:30 -> 00:54:32] People that have come through, [00:54:32 -> 00:54:33] again, we've mentored thousands. [00:54:33 -> 00:54:35] I'm not even kidding you when I say thousands [00:54:35 -> 00:54:37] and we've had thousands come through our bootcamp. [00:54:38 -> 00:54:40] We let entrepreneurs run, but we probably, [00:54:40 -> 00:54:44] probably heed a lot more than your typical mentor, right?

[00:54:44 -> 00:54:47] We say, no, no, no, stop, stop, stop, stop, stop, stop. [00:54:47 -> 00:54:49] Oh, you're going to still do it? [00:54:49 -> 00:54:50] No, no, no, stop, stop, stop. [00:54:50 -> 00:54:51] Oh, you're still going to do it?

[00:54:51 -> 00:54:54] Okay, I've told you three times, you go do it. [00:54:54 -> 00:54:56] And hopefully this doesn't come across wrong, [00:54:56 -> 00:54:57] but nine out of 10 times we're right. [00:54:57 -> 00:55:00] Yeah, we're not trying to say that. [00:55:00 -> 00:55:02] It's just because it's principles based.

[00:55:02 -> 00:55:07] I mean, the stories out there, it's hard to be successful. [00:55:07 -> 00:55:09] That's not overconfident or boisterous. [00:55:09 -> 00:55:11] That's just coming from evidence, people. [00:55:11 -> 00:55:13] Hopefully don't take that in the wrong way.

[00:55:13 -> 00:55:16] We do have a lot of evidence that that's usually the case. [00:55:16 -> 00:55:17] But when we're wrong, we admit it. [00:55:17 -> 00:55:18] Yeah, we do. [00:55:19 -> 00:55:22] Okay, so hopefully this has shed some light [00:55:22 -> 00:55:25] on what makes a good idea so that when you're [00:55:25 -> 00:55:30] in your apartments, in your home, sitting on your couch, [00:55:30 -> 00:55:31] saying, I want to be an entrepreneur, [00:55:31 -> 00:55:34] I need to be a founder, I need to start something, [00:55:34 -> 00:55:37] that you have a little bit more of an actual recipe [00:55:37 -> 00:55:39] of what makes a good idea.

[00:55:39 -> 00:55:43] Even in today's AI building era. [00:55:43 -> 00:55:47] And I don't know what else we can conclude with other than. [00:55:48 -> 00:55:49] Hey, if you need help, contact us. [00:55:50 -> 00:55:50] Yeah.

[00:55:50 -> 00:55:52] We'd love to talk to people that are struggling [00:55:52 -> 00:55:55] with these issues because it's an exciting time [00:55:55 -> 00:55:55] and exciting era. [00:55:55 -> 00:55:57] This is, I mean, I'm an old guy. [00:55:58 -> 00:56:01] I wish I was, you know, Tyler's age or even younger [00:56:01 -> 00:56:04] and all the opportunity before that's coming. [00:56:04 -> 00:56:06] It's an exciting time to be an entrepreneur.

[00:56:07 -> 00:56:09] Yeah, and if you're someone listening right now, [00:56:09 -> 00:56:13] that has a startup idea, reach out, go through this episode, [00:56:13 -> 00:56:16] go through the bullet point items that we've listed today [00:56:16 -> 00:56:20] about how to make an idea a really good business opportunity [00:56:21 -> 00:56:22] and seek us out. [00:56:22 -> 00:56:23] We want to help you with it. [00:56:23 -> 00:56:25] But for today, that's all we have. [00:56:26 -> 00:56:27] Thank you so much for tuning in.

[00:56:27 -> 00:56:28] This is episode 58. [00:56:30 -> 00:56:33] We hope to keep continuing to do this. [00:56:33 -> 00:56:35] We'll do this for as long as it makes sense, [00:56:35 -> 00:56:36] but let us know in the comments. [00:56:36 -> 00:56:37] Are you liking these?

[00:56:37 -> 00:56:39] Do you want to talk about something different? [00:56:39 -> 00:56:39] Are we doing this? [00:56:39 -> 00:56:40] Are we doing a good job? [00:56:40 -> 00:56:41] Doing a bad job?

[00:56:41 -> 00:56:42] Do we talk too much? [00:56:42 -> 00:56:43] Do we talk too little? [00:56:43 -> 00:56:44] Do you want certain guests? [00:56:44 -> 00:56:45] Let us know.

[00:56:45 -> 00:56:47] And we will try to make this as beneficial [00:56:47 -> 00:56:49] and valuable to you as possible. [00:56:50 -> 00:56:52] So any final parting words from you? [00:56:53 -> 00:56:55] Nope, you're doing a great job moderating. [00:56:55 -> 00:56:57] So world's greatest moderator right here.

[00:56:57 -> 00:56:58] Okay, so we are signing out. [00:56:58 -> 00:56:59] Thank you so much for listening [00:56:59 -> 00:57:01] to the Startup Ignition podcast. [00:57:01 -> 00:57:02] We are out.