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: analyzing interviews as data transformation, content analysis techniques and the details of how I measured the 0.1 → 0.8 jump in 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 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

Shout out to Paul Orlando at USC for all the support 🙌
https://www.marshall.usc.edu/personnel/paul-orlando

Links we referenced in the show:

• https://robbiekellmanbaxter.com/

• https://www.linkedin.com/in/robbiekellmanbaxter/

• https://subsummit.com/

• https://www.strava.com/

• https://review.firstround.com/how-superhuman-built-an-engine-to-find-product-market-fit/

• https://pmfsurvey.com/

• https://boldcommerce.com/

• https://www.linkedin.com/in/lauren-pienta-15a8298/

• https://www.linkedin.com/in/paulcchambers/

There was initial data showing this could work! Adara’s friend Susie used Adara’s TENS technique to increase milk production 5x in just a few days :

In this podcast, Adara walks us through her journey:

• Feeling inspired by other “delusional” founders in Silicon Valley / San Francisco Bay Area

• Deciding to create Believe in Breast Milk in summer 2019

• Struggling to determine her first steps

• Incorporating the startup into a business

• Taking out a personal loan of $5,000 to pay engineers to create a CAD drawing of a prototype of the smart TENS unit

• Avoiding paying another $5,000 to build the prototype.

  • Adara used the Nascent Startups methodology to focus on “creating initial value”. Instead of the expensive and tedious IoT TENS, Adara quickly and cheaply created similar value for her first users by paying less than $100 for a conventional TENS and using a free Google Form.

• Recruiting 6 people to use the TENS and measure milk production

• Shutting down the startup informally when it “fizzled out” in summer 2020