What is money and why do humans decide to spend it? Money is fundamental to a successful startup, yet I’ve mentored many founders without a meaningful point of view.

For instance, last year I ran a series of workshops where I asked the workshop participants, “As a consumer, what does money mean to you? What does a dollar in your pocket mean to you?” Here are some of their answers:

• “I don’t know. I can’t quite put my finger on it.” This type of response was pretty common.

• “I’m purchasing something that I feel will bring value to my life.” This is true, but not actionable.

• “[Money is] a tool — instead of hungry, I get full; instead of cold, I feel warm.” This describes an emotional transformation, a critical unlock that startups require.

Overall, most workshop participants didn’t have specific, thoughtful opinions about money, despite hoping that their startups would make lots of it. Even when I studied business at Berkeley, we never really got into the essence of money. I think it’s crucial for founders to have a strong, thoughtful point of view.

As a benchmark, Wikipedia defines money as “payment for goods and services,” which is true but useless to entrepreneurs. It’s like saying that “planes fly because they stay in the air.” We need to understand why this happens. Just like pilots need to understand lift, founders need to understand the equivalent force in business, which I believe is based in money and Pain.

To that end, Nascent actually has two definitions for money:

• Money is a metric for Pain, and

• Money is liquid Pain relief

Not all problems are equal. In fact, most problems are worth pennies but there are rare, special problems that are worth millions or billions of dollars. Nascent is all about prioritization. I want you to be clear about what a good problem looks like. You want to solve expensive problems.

What I mean by “liquid” is that money is easily exchanged as opposed to a gold bar or real estate.

Essentially, I want you to think about Pain as a potential that a product can release, similar to the build-up of water behind a dam. The more, the better. Our goal is to transform that potential energy into something useful. The dam allows water to flow, creating kinetic energy. This is similar to how a product relieves Pain. More importantly, the dam also generates electricity. Similarly, a product delivering Pain relief outputs cash money.

The big idea is that people have Pain and they want their Pain to be relieved. Most of the time, they can do it themselves. Occasionally, something special happens, and people can’t relieve their own Pain. That’s when there’s this huge build-up of Pain that’s just dying to get released. So the other option for Pain relief comes from buying a product. In other words, People in Pain™ pay money for the Pain relief they expect a product to deliver.

If you want to think deeply about money, I highly recommend the writings of Lars Doucet. Most importantly, understanding the relationship between products, money and Pain will give you a better chance at identifying People in Pain with the potential to be the first customers for your startup.

Mike supports founders of pivoting startups who want to avoid wasting another year on a bad idea. Book a call with me at NascentIdea.com.

For the past 10 years, I’ve been building Nascent as the strategy for quantifying product discovery. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular newsletter posts and podcast episodes. This is Post 031.2 📬, a deep dive into the concept that money is a metric for pain discussed in Ep031 🎧 (15 mins). Read the rest of the deep dives: 031.1: products imply hidden pain and 031.3: other people’s pain is your opportunity.

The perspective of Nascent is that the essence of business is transforming a Person in Pain™ into a paying customer. This is true for businesses that make products that you’re already familiar with and for the products you hope to create with your startup. Understanding this concept enables founders to distinguish between people who will never become customers and others who just might.

For instance, you might see someone hiking in the woods and think to yourself, “yeah, they look fine”. You’re probably correct — but they were not always fine. Before the journey, the hiker was scared of getting lost in the woods and worried about the burden of lugging gear by hand. These negative emotions drove the hiker’s actions: they bought a compass and a backpack to get Pain relief. The compass relieved their fear of getting lost. The backpack relieved their burden of carrying equipment. Those products are Pain-relief devices, which is why, in the end, the hiker feels fine.

How can we tell that they went from feeling scared and worried to being ok? The compass and backpack are visible clues. But we’re not mind readers. So, most importantly, we have a conversation and they tell us in their own words how they felt before the hike and then after buying products.

Their journey of using products had a beginning, middle and end. At first, the hiker was a Person in Pain who was hurting. Then they bought products to get Pain relief. The compass. The backpack. Whatever else they needed for the hike. And that’s why now they’re doing fine.

As entrepreneurs, we want to deeply understand this transformation. What matters is that the Person in Pain paid for the product to take them along that journey. Without that initial condition of hurting, the Person in Pain does not buy a product.

Our challenge is that it’s easy to envision money and products, but it’s difficult to articulate the hidden Pain that those products imply. As you navigate the world, I encourage you to try to say aloud the Pain implied by the products around you. Right now you’re probably somewhere with a door nearby. 🚪 You could look at the door and say it implies a fear of revealing sensitive information, of not wanting to be overheard. You might also say that the door implies a worry about disturbing others with loud noises.

I’d love for you to try to develop this skill of articulating the relationship between products and Pain. Look at two or three objects in your life and try to articulate the Pain that they imply. After you’ve done that for some existing products, repeat it with your startup idea. What are the fundamental Pains that you want your startup to solve? Let me know what you find. I’d love to hear about it.

Mike supports founders of pivoting startups who want to avoid wasting another year on a bad idea. Book a call with me at NascentIdea.com.

For the past 10 years, I’ve been building Nascent as the strategy for quantifying product discovery. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular newsletter posts and podcast episodes. This is Post 031.1 📬, a deep dive into the concept of hidden pain discussed in Ep031 🎧 (15 mins). The deep dives continue in 031.2: money is a metric for pain and 031.3: other people’s pain is your opportunity.

Founders want customers, but ironically, the best way to get customers is by seeing the world in reverse. What kind of people are customers before they buy? Why do people pay money in the first place? Answering these questions will help you avoid the most common problem in startups: wasting a year on a bad startup idea.

The whole reason that a Person in Pain™ might become your customer is for your product to take them on an emotional journey with a beginning, middle and end. First, a person starts with meaningful Pain — they’re “hurting”. This motivates them to pay money for a product to feel better.

The perspective of Nascent is that humans make decisions in a 3-part system: a Person in Pain who is hurting decides to pay money for a product to get Pain relief. Most importantly, money and products are visible, but Pain is invisible. This means that we can only see the end of the journey, not the beginning. For instance, a customer at a shop might pay a dollar (the middle of the journey) to buy ibuprofen (the product) to relieve a headache (the end of the journey). We can see the money and the packet of ibuprofen. But we cannot see the headache — the Pain at the beginning of their journey. The Pain is invisible. This perspective on Pain applies to every product within the built world, including the products you hope to make with your startup.

Here’s the journey of a Person in Pain becoming a customer. It starts with a person who is hurting. Then they buy a product for Pain relief so they’ll feel fine.

Looking at this journey in reverse reveals who will not become a customer for your startup. People who are already fine will not buy your product — they’re already at the end of the journey. People who are joyous are even worse — they’d ask you to pay them. Only People who are hurting might become customers.

As a founder of a startup with no customers, your most important task is searching for people who are hurting. The more hurting People you find, the bigger your opportunity.

Over the coming posts, I’ll expand on the big ideas in this episode: why products imply hidden Pain, Nascent’s two definitions of money, and Pain as a signal of opportunity.

Mike supports founders of pivoting startups who want to avoid wasting another year on a bad idea. Book a call with me at NascentIdea.com.

For the past 10 years, I’ve been building Nascent as the strategy for startups with no customers. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular newsletter posts and podcast episodes. This newsletter summarizes podcast Ep031. For a deeper dive, check out the podcast on Spotify, Apple Podcasts and YouTube.

You may have noticed something different lately with the Nascent podcast and newsletters. Here are the details.

I first published the Nascent newsletter in January 2024 followed by my first podcast in February 2024, as part of an effort to build in public. Throughout 2024 and 2025, I published only 18 times because I focused on running workshops instead. These workshops showed me that some (but not all) founders of startups with no customers are “hurting” and a dedicated strategic playbook could provide “pain relief”. My challenge was that I kept having one-off conversations about this, which felt frustrating since they didn’t generate any lasting assets.

To that end, in March 2026, I resumed publishing Nascent with Episode 019 and announced my plan to publish a weekly podcast along with a companion summary newsletter for the next 100 weeks. Little did I know that a 1:1 ratio of podcast to newsletter would be brutal. I did this for 10 weeks, through Episode 029, and found it to be like sprinting a marathon in marketing that left no time for my true passion: supporting founders directly, not just publishing guidance from the sidelines.

So starting with Episode 030, I’ve got a new plan. At least for now, every podcast episode will have an accompanying series of newsletters — an initial summary, followed by deeper dives into key points from the podcast. A ratio of roughly 1:4, one podcast with four newsletters. To hopefully make it easier to follow, I’m using a numbering system that shows the relationship between the podcast and newsletters. When I publish a new podcast, it comes with a summary (e.g., Episode 030). Then the following week I’m publishing 030.1 as the first deep dive, the next week 030.2 as the second deep dive and so on.

So if you’re new to Nascent, I recommend that you start by reading/listening to Episode 019 and work forward from there. As always, I welcome your feedback and look forward to continuing to support founders of startups with no customers. Nascent is especially useful for founders of funded startups that are pivoting — if that’s you, let’s talk. Schedule time with me here: https://nascentidea.com/

Ok, founders. You got this!

For the past 10 years, I’ve been building Nascent as the strategy for startups with no customers. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular newsletter posts and podcast episodes. For more, check out Spotify, Apple Podcasts and YouTube.

No, founders cannot innately generate meaningful analyses of discovery interviews, but it’s a skill they can learn. Running discovery interviews and interpreting the results is a type of data transformation. We can measure the reliability of this data transformation using Krippendorff’s Alpha, which I measured for Nascent. The takeaway: I saw a dramatic increase in founders’ reliability after training. Here’s how the measurement worked.

Back in Episode 028, I described a case study where a founder named Flora used Nascent to evaluate her idea for a startup called BundleShop — an app for moms to shop for bundles of stuff for their kids. Flora recorded interviews with a bunch of moms and we analyzed the interviewees’ emotions.

The BundleShop case study was the focus of my content analysis for Nascent. Specifically, I ran workshops where participants analyzed Flora’s conversations using Nascent’s data transformation scheme, the Yardstick of Pain™. Nascent categorizes an interviewee’s emotions as either hurting, fine or joyous. I instructed workshop participants to listen to brief audio clips from Flora’s five interviews and categorize the interviewees’ emotions.

I used the workshops as an opportunity both to train founders and to measure K-Alpha. I was careful to measure K-Alpha both before and after training for 79 participants. I gave the workshop participants general guidance (“search for Pain”) for the first two interviews, which resulted in a K-Alpha = 0.1, meaning that participants’ ratings were essentially random. They might as well have flipped a coin to decide whether an interviewee was hurting, fine or joyous.

To train the participants, I pointed out key details in the first two interviews, such as how an interviewee’s tone and word choice relate to the level of emotional Pain. After the first two interviews, I considered the participants trained and let them categorize the final three interviews without me interrupting. For these post-training clips, Krippendorff’s Alpha jumped to 0.8, indicating much more reliability.

I want to be clear that I consider this measurement just the beginning of what I hope to accomplish with Nascent, since it comes from just 79 raters evaluating 5 interviews for 1 startup. Still, this dramatic increase from randomness to reliability has huge implications for founders of startups with no customers. As much as founders are told to run interviews and make inferences, this is not something that founders can do inherently. But the jump from 0.1 to 0.8 shows that it’s a skill founders can learn.

Founders need to be aware of content analysis but don’t need to be experts, in the same way that a baker uses a thermometer but doesn’t need a PhD in physics. If you’re a founder interpreting a discovery interview, ask yourself what data transformation scheme you’re using and whether you measured it with content analysis or something similar. If not, be skeptical of the takeaways.

Many thanks to Paul Tepper for letting me know about content analysis and providing feedback on how I’m applying it to Nascent.

Mike supports founders of pivoting startups who want to avoid wasting another year on a bad idea. I offer personalized workshops that train your team to reliably analyze discovery interviews. Book a call with me at NascentIdea.com.

For the past 10 years, I’ve been building Nascent as the strategy for startups with no customers. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular newsletter posts and podcast episodes. This is Post 030.3 📬, a deep dive into how I measured K-Alpha for Nascent’s data transformation, as discussed in Ep030 🎧 (17 mins). Read the rest of the deep dives: 030.1: analyzing interviews as data transformation and 030.2: content analysis techniques.

Entrepreneurs have a huge opportunity to avoid fooling themselves. Founders already “get out of the building” to run interviews and get feedback on their startup idea. For conventional customer discovery, this means validating assumptions about a business model. For Nascent, this is characterizing the emotions of People in Pain™. Whatever the approach, we can use content analysis techniques to measure how reliably we reach conclusions.

Analyzing discovery interviews is a form of data transformation where founders go from unstructured interview transcripts to specific categories, like “potential customer” and “not a customer”. Analyzing interviews is part of a field of study called content analysis, developed by Klaus Krippendorff, which has been largely focused on the social sciences, at least until now. I believe it unlocks huge opportunities in entrepreneurship, specifically to limit how much founders fool themselves into pursuing bad startup ideas.

I’m fascinated by the breadth of content analysis, so I want to offer a quick history and then apply it to tech startups.

Back in the 1700s, there was a scandal in Sweden about whether certain religious hymns were “dangerous” or safe. The whole debate was about categorizing religious hymns. A few hundred years later, a similar challenge arose with categorizing newspapers: How do we really know the New York Times is liberal or the Wall Street Journal is conservative? These diverse situations prompt a fundamental question: when people analyze unstructured text — hymns, newspapers, transcripts of discovery interviews — how can we know if our analysis is meaningful and reliable?

Before I share how Krippendorff solved this challenge, first I’ll share the easiest and silliest scheme for transforming raw data into categories. First, you take the unstructured text and just throw it in the trash. Then you simply flip a coin to generate a category. Of course, this is a joke, but what matters is that randomly flipping a coin will generate results. It’s just that the results will be meaningless. This joke reveals a core concept that leads to founders fooling themselves: It’s easy to accidentally invent a fancy coin-flipping machine and not realize it.

A core insight of content analysis is to measure how a data transformation scheme compares to random chance. Specifically, Krippendorff’s idea was to train human raters to apply categorization rules (“a coding manual”) to categorize texts — and then to compare the humans’ results to random chance. Essentially asking: How do the raters compare to coin flips?

One way to make that comparison is a metric called Krippendorff’s Alpha. K-Alpha goes from 0.0 where the categorization scheme is completely random up to 1.0 indicating perfect reliability — all the raters are in perfect alignment. Roughly speaking, high inter-rater reliability is a K-Alpha of 0.8 or higher, whereas a K-Alpha below 0.6 indicates that the scheme is not reliable, i.e., it might as well be a coin-flipping machine.

Content analysis empowers founders to go from asking the wrong question, “Do we have a process for analyzing interviews?” to instead ask the more meaningful question: “How reliable is our process?”

Every time a founder speaks with someone about a startup idea, they’re making inferences. Content analysis just lets us do it reliably. In future posts, I’ll show you how I used these tools to measure the reliability of Nascent itself.

Many thanks to Paul Tepper for letting me know about content analysis and providing feedback on how I’m applying it to Nascent.

Mike supports founders of pivoting startups who want to avoid wasting another year on a bad idea. I offer personalized workshops that train your team to reliably analyze discovery interviews. Book a call with me at NascentIdea.com.

For the past 10 years, I’ve been building Nascent as the strategy for startups with no customers. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular newsletter posts and podcast episodes. This is Post 030.2 📬, a deep dive into the concept of content analysis discussed in Ep030 🎧 (17 mins). Read the rest of the deep dives: 030.1: analyzing interviews as data transformation and 030.3: how I measured the jump in Krippendorff’s Alpha.

Analyzing discovery interviews, going from conversations to conclusions, is a form of data transformation. When you consider customer discovery from this perspective, it unlocks an opportunity. Founders can use content analysis techniques to measure the reliability of how they reach conclusions.

An entrepreneur has just one priority when they have a startup idea: search for a signal about their startup’s likelihood to get customers. And the best way to do that is through discovery interviews, by speaking with people who might become the startup’s first customers.

As a mentor, I’ve seen that founders often struggle with discovery interviews. In terms of data gathering, founders have told me that they’re unsure what questions to ask. And then with data analysis, founders also say that they don’t know how to make sense of the answers that they get.

Nascent addresses the data-gathering challenge by offering founders a mental framework: a startup is a project to create new, valuable knowledge about People in Pain™. For data analysis, Nascent provides founders with a tool called the Yardstick of Pain™ to characterize the emotions of an interviewee. All this to say, founders’ challenges around data gathering and data analysis are important, but there’s an even bigger issue with the reliability of our analysis. How do we know that the conclusions we draw are reliable?

At a high level, analyzing interviews is a data transformation. Founders take a raw, unstructured interview transcript and reduce it down to something like Category A and Category B. Specifically, Nascent has founders use the Yardstick of Pain to categorize interviewees as “hurting, fine or joyous”. Similarly, conventional customer discovery has founders categorize assumptions about a business model as “valid or invalid”. Even in a quick chat, when a founder says to a friend, “I’ve got an idea for a startup -- let me know what you think”, the founder is transforming data from the conversation into takeaways about the startup idea. In all of these cases, founders tell themselves stories about what they learned in the conversations.

The Nobel Prize winner Daniel Kahneman says in his book Thinking, Fast and Slow:

High confidence means that we’ve structured a coherent story, not that the story is true.

For instance, when a gambler in a casino blows on their dice, it means that they’ve told themselves a coherent story that blowing cool air brings good luck. As founders, it’s easy to tell ourselves a coherent story about our takeaways from a discovery interview. Data transformation based on vibes is a recipe for fooling ourselves.

What we really need is to analyze interviews reliably. The good news is that there are tools from other fields that we can apply to our challenge, specifically content analysis and a metric called Krippendorff’s Alpha.

Many thanks to Paul Tepper for letting me know about content analysis and providing feedback on how I’m applying it to Nascent.

Mike supports founders of pivoting startups who want to avoid wasting another year on a bad idea. I offer personalized workshops that train your team to reliably analyze discovery interviews. Book a call with me at NascentIdea.com.

For the past 10 years, I’ve been building Nascent as the strategy for startups with no customers. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular newsletter posts and podcast episodes. This is Post 030.1 📬, a deep dive into the concept of data transformation discussed in Ep030 🎧 (17 mins). The deep dives continue in 030.2: content analysis techniques and 030.3: how I measured the jump in Krippendorff’s Alpha.

Yes, founders trick themselves when they analyze interviews, even though interviews are the most effective way to evaluate a startup idea. The catch is that founders struggle to analyze interviews reliably. In fact, until now, founders have never measured the reliability of their interview analysis so we have every reason to believe that the analyses are no better than randomly rolling dice. This drives founders’ most common outcome: a year wasted on a bad startup idea. The entire goal of Nascent is to provide founders with a toolkit that dramatically reduces that time down to days. Measurement of both interviews AND reliability is the key to better outcomes.

Judgments based on vibes result in lots of wasted effort. Founders today are kind of like medieval bakers sticking their hands in an oven to judge the heat. Sometimes the bread is burnt. Sometimes it’s raw, uncooked dough. Either way, the result was often a mess, at least until bakers began measuring temperature. Measurement unlocks improvement.

To that end, I’m excited to share two concepts that will do for startups what Celsius and Fahrenheit did for baking: content analysis and Krippendorff’s Alpha. Most founders have never heard of these tools but they desperately need to.

Fundamentally, content analysis frames founders’ process of analyzing interviews as a data transformation challenge. Founders go from raw, unstructured interview transcripts to specific, defined categories. Founders typically use interviews to decide whether the interviewee is a potential customer (Category A) or not a customer (Category B), but this approach is ad hoc. Klaus Krippendorff developed content analysis as “a research technique for making replicable and valid inferences from texts.” What this means for founders is that we can structure and measure our analysis of discovery interviews. Specifically, Krippendorff’s Alpha measures how reliably founders execute the data transformation (“the inter-rater reliability”) from completely random (K-Alpha = 0) to perfect reliability (K-Alpha = 1). Krippendorff’s Alpha measures how much founders are tricking themselves, when the interview analysis feels meaningful but is no better than rolling dice. 🎲

As far as I can tell, I am the first person to apply content-analysis techniques to customer discovery interviews to evaluate startup ideas. Specifically, last year I measured reliability of 79 “human raters” analyzing discovery interviews. Before training, their analysis was essentially random — their K-Alpha was 0.1. They didn’t really know what they were searching for, even though I told them to look for emotional pain (i.e., interviewees who might care about the startup idea). After I trained them, their K-Alpha jumped dramatically to 0.8, meaning their analysis was much more reliable.

When someone tells a baker that the oven is hot, they don’t accept it at face value. The baker asks for the temperature. In that same way, as a founder, if someone tells you that an interview means something, I hope you’ll ask them: How did you measure it? And if they didn’t use content analysis or something similar, it’s likely that they’re tricking themselves.

Over the coming posts, I’ll expand on the big ideas in this episode: 030.1: analyzing interviews as data transformation, 030.2: content analysis techniques and 030.3: how I measured the 0.1 → 0.8 jump in Krippendorff’s Alpha. The Ep030 video (17mins) tells the whole story.

Many thanks to Paul Tepper for letting me know about content analysis and providing feedback on how I’m applying it to Nascent.

Mike supports founders of pivoting startups who want to avoid wasting another year on a bad idea. I offer personalized workshops that train your team to reliably analyze discovery interviews. Book a call with me at NascentIdea.com.

For the past 10 years, I’ve been building Nascent as the strategy for startups with no customers. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular newsletter posts and podcast episodes. This newsletter summarizes podcast Ep030. For a deeper dive, check out the podcast on Spotify / Apple Podcasts / YouTube.

The recipe for success that works for legendary founders won’t work for you because it relies on their intuition. It’s unfortunate that founders look to advice from Paul Graham, Reid Hoffman and Peter Thiel because these legends cannot explain their innate sense for spotting good startup ideas. As for the rest of us, we can’t mimic intuition — repeat founders and pivoting founders have learned this the hard way. The good news is we can replicate intuition with measurement.

Reid Hoffman says to jump off a cliff and assemble the plane on the way down. This advice works for him because he has an innate sense for whether the plane will fly. The rest of us don’t so Hoffman’s advice is a recipe for disaster.

Peter Thiel lists seven questions every business must answer, including “Have you identified a unique opportunity that others don’t see?” He recognizes finding a high-value opportunity is critical but Thiel doesn’t explain how to know when you have one.

Paul Graham has “an internal compass” for recognizing good startup ideas — but he never articulated how it works:

I seem to have some sort of internal compass that helps me out. Maybe I could come up with some heuristics for recognizing genuinely interesting ideas. That’s important enough to write a whole essay about and I don’t know the answer. I probably should write something about that, but I don’t know.

If your first attempt at a startup failed, the bug was likely with your intuition, not your ability or effort. For normal founders without an innate sense for good startup ideas, Nascent is a toolkit, strategy and measurement system to overcome this challenge. Specifically, Nascent offers you frameworks for understanding startups with no customers along with discrete, actionable steps for evaluating a startup idea. The legendary founders get to skip this and barely realize it. The rest of us need to vet startup ideas explicitly. And if we don’t, then we’ll likely waste a year on a bad idea.

Why is this so hard? The most challenging type of business to create is a startup discovering a new type of customer with an unmet need. And the most challenging moment for that customer-breakthrough startup is before the startup has customers. A founder of a customer-breakthrough startup needs to create knowledge about (1) the problem, (2) the people with a problem and (3) the technology solution. And at the beginning, when a startup has no customers, the founder has the least amount of knowledge so they face the biggest challenge.

Ultimately, a successful customer-breakthrough startup will be based on knowledge that comes from customers. Founders of startups with no customers face a Catch-22: How can they get customers so they can create knowledge to get more customers? This question is insidious and misleading because most startups will never meaningfully get customers and kick off that virtuous cycle. The better question is: What are the chances of the startup ever getting customers? To answer this, the legendary founders leverage their intuition. The rest of us need to begin by identifying People in Pain™.

Anyone who’s ever been a customer of anything ever, always began as a Person in Pain. The first and most crucial step is searching for People in Pain who emotionally resonate with the problem that the startup will solve. Founders need to search for these People in Pain who are hurting as the first signal that the startup might someday have customers. The catch is that customers are visible (you can see them paying money) whereas People in Pain are invisible (you cannot see their feelings). Most people in this world are Blockers who will never care about the startup. However, if you’re lucky, somewhere buried in the Blockers are a few People in Pain. Your job as a founder is to find a few of those hidden People in Pain before you waste a year.

Want to put this into practice? Your first step is to record one conversation with someone who might benefit from your startup and categorize the Pain. In the coming posts, I’ll detail how to take these inputs and turn them into Estimated Revenue Next Year, Nascent’s metric for evaluating a startup idea with no customers.

Mike supports founders of pivoting startups who want to quickly decide a new direction using structure, not intuition. Book a call with me to protect your remaining runway by calculating Estimated Revenue Next Year for your pivot ideas.

For the past 10 years, I’ve been building Nascent as the strategy for startups with no customers. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular podcast episodes. This is the companion newsletter that summarizes the podcast. For a deeper dive, check out the podcast on Spotify, Apple Podcasts and YouTube.

I believe that speaking with people is the best way to vet a startup idea, but only when founders know what they’re looking for. Unfortunately, most founders aren’t sure what to search for, which is why it’s so common for founders to waste a year pursuing a bad startup idea.

What’s most important? Founders need to understand interviewees’ feelings about the problem the startup will solve. Nascent is a strategy for founders of startups with no customers that includes a tool called the Yardstick of Pain™ to characterize interviewees’ emotions.

Here’s a case study with a real founder named Flora who came to me to vet an idea for her startup. She only wanted to work on it if there was a good chance it would get customers. We applied Nascent to vet her startup idea in days, not years, beginning with characterizing emotions.

As an entrepreneur and a mom, Flora noticed that shopping for kids is overwhelming and wanted to solve this problem with “BundleShop”, an app for moms to shop for bundles of stuff for their kids. The idea for the app doesn’t matter -- only that it implies overwhelmed moms — People in Pain™ who might become customers. So our plan was for Flora to interview moms and categorize each interviewee’s emotions using the Yardstick of Pain as either hurting, fine or joyous.

Side note before I share takeaways from the case study: Normally, this newsletter is a summary of the podcast for folks who don’t have time to listen. In this case, I strongly encourage you to at least listen to the interview clips, starting here.

This case study was the focus of workshops that I ran last year, so I want to share some of the lessons learned. One recurring theme was that a number of participants’ biases led them to misinterpret the interviews. For instance, in one interview a mom talked about all the many places she went to shop for her kid’s birthday party. Her tone was completely indifferent. Nonetheless, a participant was convinced that the mom must be hurting because traveling to all of those places is clearly a pain. Yes, going around town is a pain for the workshop participant, but that’s not the question. The goal of the exercise was to categorize the experience for the interviewed mom, and that interviewee was fine. This type of mischaracterization is a driving factor that leads founders to believe that their startup is going to get customers when the chances are actually doubtful.

After training, participants began to identify interviewees’ emotions. For instance, they latched on to the audio clip of another mom who said, “that [shopping] sometimes makes me anxious.” These types of negative emotions -- anxiety, stress, worry -- are exactly what founders need to search for.

As a founder, your ultimate goal is to create a product that moves customers along the Yardstick of Pain. People who are joyous have nowhere to go. People who are fine theoretically could move up to joyous, but the chances are so low that it’s not worth trying. Only people who are hurting and want to become fine might be your startup’s first customers.

Want to put this into practice? Over the past few posts, I’ve asked you to record conversations with people who might benefit from your startup. The next step: listen to those recordings and categorize the pain of each interviewee using the Yardstick of Pain. This is the first step towards quantifying a startup idea in dollars with an ERNY™ value (Estimated Revenue Next Year).

Mike supports founders of pivoting startups who want to quickly decide a new direction using structure, not intuition. Book a call with me to protect your remaining runway by calculating Estimated Revenue Next Year for your pivot ideas.

For the past 10 years, I’ve been building Nascent as the strategy for startups with no customers. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular podcast episodes. This is the companion newsletter that summarizes the podcast. For a deeper dive, check out the podcast on Spotify, Apple Podcasts and YouTube.

Most founders don’t know what they’re looking for in discovery interviews so they don’t know if they found it. Founders need a meaningful, structured way to make sense of interview data. I believe this is possible. Moreover, with the right tools, founders can be decisive in days (not years!) about choosing a startup idea worth pursuing.

If an architect told you, “we eye-balled the dimensions of your house; we didn’t use a ruler,” you’d expect the house to collapse. But in entrepreneurship, when a founder speaks with a potential customer about their startup idea they often conclude, “Yeah, that was validating,” and their co-founder agrees: “Sounds about right.” They’re falling into the trap articulated by Richard Feynman: “The first principle is that you must not fool yourself, and you are the easiest person to fool.”

I spent my early career building test systems for consumer products where I learned that test systems must have consistency and repeatability. The way founders analyze interviews today is inconsistent and ad hoc. The bug is with the approach to data, not the founders. Previously, we talked about Nascent’s four-part approach to data in discovery interviews:

1. Gather data by “Getting Out of the Building” 🏢

2. Capture data with audio recordings 🎤

3. Categorize data like a nurse searching for Pain 👩‍⚕️

4. Iterate like a wildcatter making incremental investments 🛢️

The first step in categorization is applying a tool I call the Yardstick of Pain™. During the interview founders ask questions centered around: “When was the last time you had this experience? How did it feel?” Founders then categorize the interviewee’s emotions into exactly one bin: hurting or fine or joyous.

Most interviewees will reply to these emotional questions with something like “Yeah, I did it and it was okay.” -- they’re fine. Occasionally, an interviewee might say “Oh, that happened to me last week and it was fantastic” -- they’re joyous. And if we get lucky, someone says “Ugh. I did that and it was horrible.” That person is hurting. And that’s the first sign that a Person in Pain™ might someday become a customer.

How many interviews do you need? Conventional discovery programs typically require 100 interviews over the course of months, such as NSF I-Corps. With Nascent, our goal is to work in batches of five interviews over a few days, like a wildcatter prospecting for oil. Wildcatters don’t go a mile deep before deciding; they drill a few feet at a time, look for signal, then decide whether to keep going.

Nascent is the strategy that I wish I would have had for every time I had an idea for a startup. I’ve run hundreds of discovery interviews but still wasted years pursuing bad ideas. Nascent would have clarified what I was searching for (People in Pain!) and the Yardstick of Pain would have let me categorize my interviewees so that I could make a quick decision.

Want to put this into practice? Look around you right now. Every product you see in this world implies People in Pain. Tylenol implies people with headaches. Chairs imply people who have a sore back from standing up. Pick a product near you and try to articulate aloud: What is this product? And what Pain does it imply? Once you can do that with existing products, you can apply it to the products that don’t yet exist, i.e., the product you want to build with your startup. In the coming posts, I’ll detail how to go from categorizing interviewees using the Yardstick of Pain bins to quantifying them in dollars with an ERNY™ value (Estimated Revenue Next Year).

Mike supports founders of pivoting startups who want to quickly decide a new direction using structure, not intuition. Book a call with me to protect your remaining runway by calculating Estimated Revenue Next Year ($) for your pivot ideas.

For the past 10 years, I’ve been building Nascent as the strategy for startups with no customers. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular podcast episodes. This is the companion newsletter that summarizes the podcast. For a deeper dive, check out the podcast on Spotify / Apple Podcasts / YouTube.

Why do founders often waste a year on a bad startup idea despite running “customer-discovery interviews”? Most founders accept low-quality data that they’d NEVER accept elsewhere. Specifically, founders “capture” data using their memory and their notes -- self-reported data that’s a recipe for getting fooled. Instead, they need recordings to actually capture what interviewees say. I believe that with the right structure and focus, founders could be decisive in days about investing time in their startup idea.

If someone told you that they met a person who is 20-feet tall, you’d probably reply: “Prove it. Show me the guy and bring a tape measure.” But I’ve worked with so many teams of founders where one says “I interviewed a customer” and their co-founder says “Yup, sounds about right.” No asking for proof, just blind acceptance. They’re falling into the trap articulated by Richard Feynman: “The first principle is that you must not fool yourself, and you are the easiest person to fool.”

Humans are wonderful people, but we’re horrible at data capture. Our memories are faulty. Our notes require interpretation, which mixes accurate and erroneous data. Fundamentally, a startup is a project in creating new, valuable knowledge. The data that a founder gathers is the basis of that knowledge. This means that a faulty process for running interviews leads to a chain of events: bad data = misunderstandings = wasted year.

The bug is with the approach to capturing data, not the founder. You can use Nascent as a strategy to avoid fooling yourself, beginning with this four-part structure:

1. Gather data by “Getting Out of the Building” 🏢

2. Capture data with audio recordings 🎤

3. Categorize data like a nurse searching for Pain 👩‍⚕️

4. Iterate like a wildcatter making incremental investments 🛢️

Recordings are the foundation of your project. Historically, recorded conversations have been taboo, but that changed in 2020 with COVID. That year most of us spent our lives online and accepted recordings. It’s now become normal to record Zoom meetings with a note-taker bot like Otter.ai. It can still be awkward to record in-person conversations, but I’ve found that interviewees now often agree to recordings. The unlock is that interviewees want to be helpful (that’s why they talk with founders in the first place!) so founders secure consent by highlighting that recordings make interviewees even more helpful. I’ve found this statement works about 80% of the time:

What you’re saying is helpful. I don’t wanna be distracted taking notes.

Would you mind if I recorded our conversation?

Want to put this into practice? Go record one conversation with one person who might benefit from your startup. That’s your first step to build a solid foundation for your knowledge-creation project. In the coming posts, I’ll detail how to analyze those recordings to get a meaningful understanding of the potential for your startup to get customers.

Mike supports founders of pivoting startups who want to quickly decide a new direction using structure, not intuition. Book a call with me to protect your remaining runway by calculating Estimated Revenue Next Year ($) for your pivot ideas.

For the past 10 years, I’ve been building Nascent as the strategy for startups with no customers. As of 2026, I’m publishing Nascent, a few ideas at a time, in regular podcast episodes. This is the companion newsletter that summarizes the podcast. For a deeper dive, check out the podcast on Spotify / Apple Podcasts / YouTube.

A subscriber asked: Isn’t searching for People in Pain just marketing? Nope.

In Episode 022, I said that the only thing that matters for founders of startups with no customers is to search for invisible People in Pain™, which I illustrated using the People-to-Prospect Funnel™. Then I walked through an example applying this to a food-cart pod where the prospects and customers are visible. Meanwhile outside the pod, the people walking by are mostly blockers (people who won’t become customers) as well as rare, special People in Pain -- they’re hungry but don’t realize the food carts want to serve them.

This framework in Episode 022 prompted a comment on YouTube:

the people outside the fence are possible customers. Prospects. You can put a sign that says come get some hot dogs. Isn’t that called marketing? Therefore, Finding those people in pain is marketing .

Nope. Marketing is a project to deploy existing knowledge. Searching for People in Pain is a project to decide whether to try to get that knowledge in the first place. This seemingly simple question is about a conventional hot-dog stand business where all the components are visible. The distinction is even more important for a customer-breakthrough tech startup where all the components are invisible.

To see the difference, imagine a data disaster where a marketer wakes up one day with no customer data. All of their databases were somehow wiped out but at least the business itself is still running. So the marketer can get more customer data, turn the data into knowledge and use that to make marketing decisions. As a benchmark, advertisements typically have a 1% conversion rate and cost about $10 for 1,000 ad impressions. In other words, even when a marketer has knowledge about their target audience, 99% of their advertisements are just spam wasted on blockers in an effort to send a message to the few, special People in Pain.

Now, think about the founder of a startup with no customers. Every day is a data disaster for founders. Every morning begins with a full cup of coffee and an empty database. Even worse, there’s no clear starting point because there are no customers to learn from. There is no knowledge to create a targeted marketing campaign. Today, most founders tackle this challenge by using assumptions, not knowledge. Then, after a year, the founders recognize that the startup will never get customers and that they have nothing to show for all their effort. This sucks.

To respond to the question directly: Yes, any hot-dog stand owner can just put up a sign and, yes, that could be called marketing. However, the effectiveness of the marketing campaign is completely dependent on the invisible, underlying knowledge. Without knowledge, marketing is useless: the ad spend gets absorbed completely by spamming blockers, not messaging the People in Pain. Without knowledge, marketing cannot drive new prospects and customers.

Founders of startups with no customers face a cold-start problem. For these founders only one question matters: If you pursue a startup and embark on a knowledge-creation project, how valuable might that knowledge be and for whom? Nascent is a strategy for answering this question by quantifying a startup idea in dollars ($). Until you have a signal that there might be any value to creating knowledge, then putting up a sign or running any other marketing campaign is a distraction.

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As of 2026, I’m publishing Nascent, a few ideas at a time, in regular podcast episodes. This is the companion newsletter that summarizes the podcast. For a deeper dive, check out the podcast on Spotify / Apple Podcasts / YouTube.

Reid Hoffman was WRONG when he said:

“Willingness to jump” is not even Reid Hoffman’s most valuable asset! His most valuable asset is his ability to know whether the plane might fly. Only then is willingness to jump valuable, not disastrous. The only thing that matters for a founder of a startup with no customers is whether the plane might fly, whether there’s a possibility of success for their startup. Hoffman’s intuition lets him take this for granted; the rest of us need a toolkit that approximates his intuition.

In entrepreneurship, we focus on startups with huge exits, where the founders jumped off a cliff and their plane flew. But if you add up all the startups with exits over $10M, they still make up less than 1% of all startups. The other 99% of founders shut down their startups with nothing, splat. I call this a “zero-dollar exit.”

I want to be clear: a 99% failure rate for startups is fine. It’s great that lots of founders pursue ideas, even if most startup ideas fail. We cannot control the RATE of failure. I’m a contrarian because I don’t accept the DURATION of the projects. Founders often waste a year on a bad startup idea. My goal with Nascent is to reduce time wasted down to days. It’s unfortunate when a startup fails, when the plane won’t fly — but we can’t control that. We can control how we allocate our time. Founders need a way to predict whether a project has a chance of success.

The Chain of Success™ is a framework that articulates everything that needs to go right for a startup to succeed: paying customers, team, product, marketing, sales, legal. Each of these is a link in the Chain of Success. For those top 1% of successful startups with big exits, all of the links held in their Chain of Success. For the startups with zero-dollar exits, at least one link failed, so the whole Chain failed.

The Chain of Success reveals three strategic takeaways:

1. Fragility. It’s really easy for the Chain to break, for the startup to fail, and your work to come to nothing.

2. Signal. Therefore don’t invest heavily in creating a link — don’t build a product, recruit a team or write a marketing plan. Instead, get an early signal whether the Chain might hold.

3. Focus. Only prioritize the link most likely to break. Until you have reason to believe that link *might hold* none of the other links matter.

The data is clear and consistent over the last 20 years (CB Insights, Why Startups Fail): the biggest risk to a startup is whether it can get paying customers. That’s the riskiest link. Until you have a signal that paying customers might be possible, any work you put into any other aspect of your startup is a waste.

As of 2026, I’m publishing Nascent a few ideas at a time in regular podcast episodes. This is the companion newsletter that summarizes the podcast. For a deeper dive, check out the podcast on Spotify / Apple Podcasts / YouTube.

The biggest challenge in entrepreneurship 🏔️ is that founders of startups with no customers need a way to know if they’re about to “make something people want”. This motto from Y Combinator is a goal not a strategy. The question remains: How can founders know if their startup idea is something people want? More founders struggle with this challenge than any other and they often waste a year before recognizing that the startup was not making something people want.

Many founders try to overcome this challenge by mimicking the most successful entrepreneurs, which fails. The best entrepreneurs have an innate sense for a good startup idea, but they don’t know how it works. For instance, Paul Graham says that he has an internal compass for good startup ideas but he can’t explain it.

For the rest of us, instinct isn’t enough. Founders who use a gut-feel approach usually waste a year or more before realizing that their startup is not something people want. This painful outcome has happened to me repeatedly which is why I’m laser focused on solving the biggest challenge in entrepreneurship. I believe that measurement is the key to a meaningful solution. Specifically, I’ve created Nascent as a strategy for founders to quantify the price that their first customers might be willing to pay. This adds up to an ERNY™ value, the Estimated Revenue Next Year for a startup with no customers. In other words, Nascent replaces intuition with a metric in dollars ($) for how much people want what the startup is about to make. I want to tell you a bit about me so that you’ll have reason to trust Nascent.

Why am I the right guy to solve this challenge? Three reasons:

1. Measurement systems. I worked for years creating measurement systems for consumer products that had never been measured before. Specifically, I worked as a regulator at the US Department of Energy and Natural Resources Canada, creating energy efficiency standards and test procedures for power supplies, televisions and Christmas lights. My experience quantifying these products translates directly into my ability to measure startups with no customers.

2. Crossing borders. I’m drawn to the boundaries of things and combining seemingly different concepts. Conventional entrepreneurship strategies have not solved this challenge so we need to cross borders and bring in new ideas. This is why Nascent’s quantification frameworks include concepts from oil prospecting, nursing and behavioral economics.

3. Table stakes. I have decades of experience with the two pillars of Nascent: entrepreneurship and education. I’ve been a teacher my whole life — from a teaching assistant in college to mentoring 100 founders through the Haas School of Business at UC Berkeley. My superpower is explaining things and I’ve focused specifically on startups with no customers.

The spark for Nascent

When I did my MBA at Berkeley, the best class I took was Lean Launchpad with Steve Blank and Jerry Engel where I worked on my startup, Yaygo. The professors said that my idea for Yaygo sucked, but couldn’t explain why. They were correct, but I ignored them and wasted years because I couldn’t understand their reasoning. In the class, my team and I did everything right -- we ran 100 discovery interviews and iterated a business model canvas. But I never had a robust way to analyze the data, to see why my idea sucked, to know whether Yaygo was something people wanted.

Nascent is the strategy that I wish that I would have had. Quantifying those interviews in dollars would have immediately clarified why Yaygo wasn’t worth building. I wouldn’t have needed 100 interviews and I wouldn’t have wasted years.

Now I’m trying to share Nascent with founders. To begin using Nascent, here’s your first step: record a conversation with one person who might benefit from your startup. That’s it. In Nascent strategy only recordings count -- no memory, no notes. Let me know what you record at Podcast@NascentIdea.com.

If you’re a founder of a funded startup that’s pivoting, intuition isn’t enough to decide which new idea to pursue. Let’s get on a call and talk about how to kill bad ideas fast so that you can protect your remaining runway.

As of 2026, I’m publishing Nascent methodology, a few ideas at a time, in regular podcast episodes. This is the companion newsletter that summarizes the podcast. For a deeper dive, check out the podcast on Spotify / Apple Podcasts / YouTube.

In my last post, I argued not to chase customers because founders often waste years before realizing that their startup won’t get customers. You need an earlier signal so instead you should search for People in Pain. Insight: anyone who’s ever been a customer first began as a Person in Pain™.

Nascent is a strategy with the perspective that knowledge is what defines a business. Nascent categorizes businesses based on how they acquire their knowledge:

• Conventional businesses (e.g., pizza shop, car mechanic) - founders learn most of the knowledge because it already exists

• Breakthrough startups - founders create the knowledge because it doesn’t yet exist.

  • Technology breakthrough - a new solution to a valuable, obvious problem (e.g., Ozempic, teleportation)

  • Customer breakthrough - a new solution to a valuable, hidden problem (e.g., Airbnb, Uber)

Let’s talk through a few examples.

🍕 A pizza shop is a conventional business. To run a pizzeria, most of the knowledge exists already, such as making pizza and serving customers. Founders can learn this knowledge from books and by working at other pizzerias.

💊 Ozempic is a technology-breakthrough startup. The problem of weight loss was obviously valuable. Founders just needed to create the knowledge for the solution: a miracle drug that delivered weight loss and then they knew they’d have customers.

🏡 Airbnb is a customer-breakthrough startup. The problem of strangers staying at each other’s homes was not obviously valuable. It was hidden. Airbnb’s founders had to create the knowledge about both the problem and the solution. It was not obvious that solving the problem would result in paying customers.

What about you? Is your startup similar to a conventional business, like a pizza shop? A technology-breakthrough, like Ozempic? Or a customer-breakthrough startup, like Airbnb?

I expect that you’re pursuing a customer-breakthrough startup. You’re trying to create a new solution to a valuable, hidden problem — the opportunity is compelling to you, but most other founders don’t see it.

If you jump into building your product and your business, you’re likely to waste months or years. Instead be strategic. Your best first step is to use Nascent to find People in Pain with the hidden problem and quantify their Pain in dollars. Since your startup is a knowledge-creation project, begin by measuring the value of that knowledge using first-hand data from the People in Pain who could become your customers. To do this, you must overcome the challenge that People in Pain are invisible.

To clarify the distinction between hidden People in Pain and visible customers, Nascent has a framework called the People-to-Prospect Funnel™ to let you map the journey for your potential customers:

1. Blockers: There are 8 billion people and your startup is irrelevant to most of them

2. Distractions: People interested in your startup who will never become customers

3. People in Pain: Invisible people with the potential to become customers

4. Prospects: Visible people who want what your startup provides

5. Customers: Visible people who’ve paid money to your startup

To see the People-to-Prospect Funnel in action, picture a food cart pod filled with chefs eager to serve customers.

At the more popular food carts, you can see a line of prospects waiting, cash-in-hand, ready to pay the chef. You can see a customer paying money to the chef. Here’s what you cannot see: the invisible People in Pain nearby. There are hungry people walking by who don’t realize that the chef is right there and wants to serve them.

As a founder of a startup with no customers, of course, you ultimately want customers. But if your first step is chasing customers then you’ll likely waste years. Instead, get an earlier signal. Before anyone ever becomes your customer, they’re first going to be a prospect, and before that a Person in Pain. In other words, for your startup to have a chance of ever getting a customer, first you must find People in Pain with an expensive, excruciating problem.

Over the coming posts, we’ll get into how to search for those People in Pain and how to quantify their Pain in dollars so you can quickly get a signal whether your startup might ever get a customer.

As of 2026, I’m publishing Nascent methodology, a few ideas at a time, in regular podcast episodes. This is the companion newsletter that summarizes the podcast. For a deeper dive, check out the podcast on Spotify / Apple Podcasts / YouTube.

“How can founders get customers for a startup?” is a question with many wrong answers. The answers are all wrong because the question is wrong. The most likely outcome from trying to get customers is that you waste months or years seeking customers in vain.

Most startup ideas don’t get customers and pursuing a startup idea is a huge time investment. So the right question is “What are the chances of my startup ever getting customers?” -- a question you can answer in days.

When you’ve got a startup with no customers, your first step should not be to try to get customers. It’s too tedious and takes too long. Statistically, the most likely outcome is that you invest a year or more trying to get customers, with nothing to show for it. I can attest to this personally. Instead, you should look for an earlier signal.

A metaphor: Think about creating a successful startup like another complex goal: playing baseball for the Yankees. These goals have high failure rates and require huge investments of time. So your best first step is to get a small reason to believe that success might be possible. To play for the Yankees, you should first answer the question: Can you get a bat to hit a ball? ⚾️ If you can, there’s a chance you could become a Yankee. If not, then you probably want to pursue a different sport. Of course, there’s lots more work to do beyond hitting the ball, but at least you have a reason to believe the time investment might be worthwhile.

As a first step for your startup, seeking an initial signal of a paying customer is too difficult and time consuming. I believe that anyone who’s ever been a customer of anything ever, always starts as a Person in Pain. So instead of trying to get customers, the best early signal is searching for People in Pain. If you can find people with expensive, excruciating Pain, then there’s a possibility your startup could get customers. If you can’t, the chances are doubtful and you probably want to pursue a different idea.

Searching for People in Pain is easier than trying to get paying customers, but it’s still really hard. Customers are easy to identify because their action (payment!) is visible. By contrast, People in Pain are invisible -- it’s not obvious who exactly is a Person in Pain. Another challenge is that a startup is fundamentally a knowledge-creation project -- and that knowledge is also invisible. As a founder of a startup with no customers, you’ve got two invisible challenges: you’re searching for an invisible component in a knowledge-creation project. This is the big idea we’ll unpack next.

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As of 2026, I’m publishing Nascent methodology, a few ideas at a time, in regular podcast episodes. This is the companion newsletter that summarizes the podcast. For a deeper dive, check out the podcast on Spotify / Apple Podcasts / YouTube.

Startups with customers face different challenges than startups with no customers — but conventional startup strategies don’t make this distinction. There’s no Playbook A for startups with customers and Playbook B for startups with no customers. Even The Lean Startup, one of the canonical texts of conventional entrepreneurship, begins with the premise that the author’s startup had customers: “We really did have customers in those early days.” (Eric Ries on Page 4)

Conventional entrepreneurship strategy has a glaring gap. Today, there’s no single resource dedicated to quickly determining (in days!) whether a startup idea is an opportunity worth pursuing. There’s no straightforward way to distinguish between ideas where success is possible versus ideas where success is doubtful. So founders often waste a year or more pursuing a startup idea before giving up.

This is the most important problem in entrepreneurship because it’s the most common problem: more founders face this challenge than any other. This is also the most limiting: until a founder can identify a meaningful opportunity, all of their other work (building prototypes, recruiting team members, etc.) is likely wasted effort.

If evaluating startup ideas truly is the biggest problem in entrepreneurship, then why does this challenge even exist? Why hasn’t this been solved by now? After all, so many of the world’s greatest entrepreneurs have written extensively about their approaches to startups, such as Marc Andreessen’s blog and Ben Horowitz’s “The Hard Thing About Hard Things” and Peter Thiel’s “Zero-to-One”. Why can’t founders just use these playbooks?

I believe that, by definition, the most successful founders inherently have spent very little time working on bad ideas. In other words, if successful founders had been distracted for years working on bad ideas then they wouldn’t have had the time to be successful. They’re not well-versed in the challenge of wasting time on bad ideas.

Additionally, I believe that the most successful founders have an innate ability to evaluate a startup idea that most of us lack. When I’ve talked with some of these special founders they told me their evaluation method is: “I know it when I see it.” And this actually works for them! Unfortunately, this gut-feel approach doesn’t work for the rest of us, the majority of founders. To be clear, our limitation isn’t our lack of innate ability -- it’s our lack of toolkit. It’s like the difference between the lucky few who have 20/20 vision and the rest of us who wear glasses. It’s not that we can never see; we just need the right tool — and without it we stumble around and get hurt. Most of us lack “20/20 vision” for startups so applying “I know it when I see it” results in frustration and 1+ years of wasted effort.

I found a great parallel in YouTube cooking videos. For a while, I followed celebrity chefs who said to ‘get the pan hot’ and ‘season to taste’ -- instructions that work for them because they have an innate ability. For me, their recipes failed because I’m normal -- I don’t have innate cooking ability. Another instructor, Helen Rennie, articulates the challenge perfectly:

“They are trying to teach you to make pasta … by touch and feel. Think of these chefs as native speakers of pasta. Intuitive pasta making is not for people learning from books and screens. You need a lot of details and accurate measurements if you want to make quick progress.”

The gut-feel and innate ability of the most successful chefs has a direct parallel with the most successful entrepreneurs. When Paul Graham tried to articulate his innate ability to identify good startup ideas, he said:

“I seem to have some sort of internal compass that helps me out.”

Most founders lack that internal compass, that innate ability, that gut feel. Instead, we need details and measurements. And this is my goal with Nascent methodology™ -- a playbook for founders of startups with no customers to measure their idea in dollars and drive decisiveness in days. Essentially, Nascent allows you to take an idea for a startup and boil it down to a few core metrics like the ERNY value™ (Estimated Revenue Next Year) to get a sense of whether success is doubtful or possible. All without writing a single line of code, without building any product. I’ll be discussing the mind-shift and mechanics of Nascent over the coming weeks.

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As of 2026, I’m publishing a few ideas at a time from Nascent methodology in regular podcast episodes. This is the companion newsletter that summarizes the podcast. For a deeper dive, check out the podcast on Spotify / Apple Podcasts / YouTube.

A good idea is the foundation of a successful startup. But today there’s no way to measure a startup idea, to determine if it’s an opportunity worth pursuing. Consequently, most startups fail and the most common reason they fail is lack of customers. What’s worse is that founders often waste a year before realizing they’re pursuing a bad idea.

This is true for the 1 million startups launched each year as well as the 7,000 startups that get seed funding. Founders can’t control whether their startups succeeds or fails, but founders can control how much time they invest pursuing an idea. I’m obsessed with the challenge of founders wasting time on bad ideas, because I’ve done it so many times myself. For instance, with my last startup Creyon, my co-founder and I worked for two years before we pulled the plug.

Recognizing a bad idea should not take years.

The closest thing I’ve found to a “tool” for evaluating startup ideas comes from a lecture that Paul Graham (co-founder of Y Combinator) gave at Stanford:

“History is full of examples of young people who are working on problems that no one else at the time thought were important... On the other hand, history is even fuller of examples of parents who thought their kids were wasting their time and who were right. So, how do you know if you’re working on real stuff? ... Well I know how I know: real problems are interesting... My life is full of case after case where I worked on things just because I was interested and they turned out to be useful later in some worldly way... So I seem to have some sort of internal compass that helps me out.”

Founders desperately need a version of Paul Graham’s “internal compass”, a faster way to identify whether they’ve identified a problem worth solving. In other words, founders need to distinguish between startup ideas where getting customers is possible versus doubtful. In that lecture, PG struggled to clarify his approach so others could use it:

“But how do you tell what is a real problem? I don’t know. That’s like important enough to write a whole essay about and I don’t know the answer. I probably should write something about that, but I don’t know. I don’t know.”

Another framework for distinguishing startup ideas that are opportunities from distractions comes from The Mom Test by Rob Fitzpatrick, though he seems to have moved on to other challenges.

As far as I know, I’m the only person actively trying to solve this problem by developing novel tools to reduce the time wasted on bad ideas from years down to days. To that end, I’ve created a Nascent methodology as a version of Paul Graham’s internal compass. In the simplest sense, Nascent methodology takes a batch of discovery interviews as input and produces what I call the ERNY value — Estimated Revenue Next Year in dollars — as output. ERNY (pronounced “Ernie”) is based on first-hand data gathered by founders, as opposed to TAM/SAM/SOM, which are top-down market estimates. If a startup’s ERNY value says revenue next year could be $1,000,000, that might be an opportunity worth pursuing. If it’s $0.09, it’s probably a distraction. This simplified metric drives decisiveness so founders can evaluate an idea in days and avoid wasting years.

Although the ERNY metric is simple, the shift in mindset to understand it requires a rethinking of conventional entrepreneurship and a new toolkit for founders focused on startups with no customers. This is why I’m relaunching Nascent with a goal of publishing 100 podcast episodes in 50 weeks. Each episode will present a few big ideas or tools in Nascent methodology. I expect the methodology to improve as more founders apply it and give me feedback.

If you’ve ever wasted time on a bad idea, I want to hear your story. Add a comment below or email me at newsletter@nascentidea.com.

Subscribe to the podcast on Spotify / Apple Podcasts / YouTube so you don’t miss the next episode.

After publishing 18 podcast episodes in 2024 and 2025, I went quiet. I spent most of 2025 running workshops with founders and refining my ideas. Starting on Monday March 30th 2026, I’ll be publishing much more regularly.

I’m relaunching Nascent 🪺

I’m Mike Vladimer, the founder of Nascent -- the methodology for startups with NO CUSTOMERS.

Today, founders often waste a year or more pursuing a startup idea before giving up, when they could have come to that same decision more quickly. I believe founders are using flawed tools: conventional startup strategies are for startups with customers. Nascent is tailored for startups with no customers, which enables founders to decide within days (not years!) whether their idea is an opportunity worth pursuing. I’m publishing because I’ve made progress worth sharing and I expect to iterate as more founders use Nascent.

What’s changing

• The podcast is back with a goal of 100 episodes over the next 50 weeks, roughly 2 per week. In addition to the podcast, I’ll publish a companion newsletter and video shorts

• Each podcast episode and companion newsletter will cover a few ideas in the methodology, real case studies and what I’m learning as I go.

• The podcast is on Spotify, YouTube and Apple Podcasts. The newsletter is staying on Substack.

• Funded founders struggling with a pivot can embed me in their team, details on the new website: https://nascentidea.com/

• I’m simplifying the previous nomenclature (e.g., Nascent Startups → Nascent methodology; nascent-stage startup → Nascent uncertainty)

What to expect

I’ll soon publish Episode 019 where I lay out the core problem that Nascent focuses on: founders waste years on bad ideas. I believe that founders with no customers can still generate an Estimated Revenue Next Year, in dollars $, a metric I’m calling the “ERNY value” (pronounced “Ernie value”). ERNY is based on first-hand data that founders gather through discovery interviews. Measuring a startup idea using ERNY will enable founders to shrink the time wasted on bad ideas from years down to days. After Episode 019 sets up this challenge, the following episodes will dig into the mindset shift that founders need to understand the ERNY value and the mechanics to implement ERNY.

You can always reach me at podcast@nascentidea.com. Ok founders, let’s find some opportunities worth pursuing.

You’ve got this!
Mike