Google’s Former Innovation Agitator Shares the Pretotyping Method That Separates Ideas Destined to Succeed From the 80% Destined to Fail
Alberto Savoia had just turned a $3 million investment into a $100 million exit.
Eighteen months. Load testing technology for websites during the internet boom. Sequoia Capital backing. World-class team.
He thought he was the Italian Steve Jobs. Stefano Jobini.
So he raised $25 million for his next startup. Spent five years building exactly what customers said they wanted. The product worked perfectly. Everyone who saw it said, “Alberto, this is amazing. We will buy it.”
Very few people bought it.
The company sold for pennies on the dollar.
Same guy. Same caliber team. Same quality execution. Opposite outcome.
That failure led Alberto to Google, where he became their Innovation Agitator and developed something that might save you from the same fate: pretotyping.
Meet Alberto Savoia: From Google AdWords to Innovation Agitator
As Google’s first Director of Engineering, Alberto Savoia led the team that launched Google AdWords—the platform that now generates over $300 billion annually. Later, in his role as Google’s Innovation Agitator, he developed pretotyping—a rigorous data-based system for validating new product ideas.
Prior to Google, Alberto was a successful serial entrepreneur and the first Director of Software Technology Research at Sun Microsystems Laboratories, where he played a key role in the development of Java technology and tools. His work has garnered The Wall Street Journal Technical Innovation Award, InfoWorld’s Top 25 CTOs Award, and InfoWorld’s Technology of the Year Award.
Today, he’s highly sought-after as a speaker, teacher, and coach, renowned for helping organizations unlock their full potential for innovation and growth. His latest book is The Right It—Why So Many Ideas Fail and How to Make Sure Yours Succeed, published by HarperCollins.
What’s in it for You:
Why 80% of new ideas fail in the market even with perfect execution by world-class teams, and how Alberto’s $100 million success followed by complete failure led to the pretotyping method that helps you avoid the same fate
The XYZ hypothesis formula that transforms fuzzy business ideas into testable assertions you can validate in days instead of years, giving you a one-line mini business plan that goes directly from concept to revenue projection
Why focus groups, surveys, and expert opinions have zero skin in the game and how the Skin in the Game Caliper reveals which validation methods actually predict market success versus those that waste your time and money
The YODA framework that teaches you to collect Your Own Data instead of relying on Other People’s Data, because just because 5 million people buy birdwatching equipment doesn’t mean they’ll buy your birdwatching app
How hyperzooming lets you use local experiments to validate global assertions, minimizing time to data, dollars to data, and distance to data so you can break the ice with the market as quickly and cheaply as possible
Why contact with the market is the number one thing entrepreneurs fear but the number one thing they must do, and how Jeff Hawkins used a block of wood and one week to validate the Palm Pilot before spending two years building it
The 80% Problem Nobody Talks About
Here’s what Alberto discovered at Google: 80% of new ideas fail in the market, regardless of execution quality.
The very same team that created Gmail and Google Maps also worked on products that completely flopped. Google Glass. Google Groups. Same brilliant people. Same resources. Different results.
The problem isn’t execution. It’s building the wrong thing.
And you believe you’re building the right thing because everybody told you they’d buy it. Your focus groups loved it. Your surveys came back positive. Industry experts validated your concept.
But you’re about to waste months or years building something nobody wants because you’re relying on what Alberto calls “focus fictions.”
Why Focus Groups Are Worthless (And What Actually Predicts Success)
McDonald’s runs focus groups about new menu items.
One result always comes up: “You should have more healthy items on the menu, like salads.”
So McDonald’s adds salads. Maybe 20% of people in the focus group said they’d eat salad.
Then you walk into the actual store. Nobody orders salad.
Because once you smell the fries, you’re done.
That’s the gap between stated preference (“I’d order the salad”) and revealed preference (“Give me a Big Mac with fries”).
Focus groups have zero skin in the game. It costs nothing to give an opinion.
Same with surveys. Expert opinions. Social media likes. Your friend telling you “I would totally buy that.”
All worthless.
The Skin in the Game Caliper: What Actually Matters
Alberto developed the Skin in the Game Caliper to measure real commitment:
- Opinions, focus groups, surveys: 0 points
- Valid email address: 1 point
- Phone number: 2 points
- 10 minutes of their time: 10 points
- Money: Highest points
Only commitment with consequences reveals truth.
When we validated the Story Cycle Genie, we didn’t rely on statistics about the AI market or SaaS adoption rates.
We got 20 beta users who each invested $500. They spent 1-2 hours using the genie. Then another 1-2 hours on Zoom giving us feedback.
That’s YODA with serious skin in the game.
The XYZ Hypothesis: From Fuzzy Dreams to Testable Reality
Alberto was doing office hours at Stanford when students pitched him an air pollution monitor idea.
They kept saying: “A lot of people in very polluted cities will pay a fair amount for a portable pollution device.”
He asked: Who are these people? How many is “a lot”? What’s “a fair amount”?
On the whiteboard, math students had left equations with X, Y, Z.
Flash of insight.
He created the XYZ hypothesis: At least X% of Y will do Z.
Where:
- Y = Your target market
- Z = The specific action you expect
- X% = The minimum percentage you need for viability
Example: “At least 1% of US birdwatchers will download Alberto’s app and pay $5 for it.”
One line. Mini business plan. Directly from idea to revenue.
And most importantly: immediately testable.
Because the job of a hypothesis is simple. It exists to be tested and falsified.
YODA vs. OPD: Why Your Market Research Is Lying to You
You tell Alberto you have data.
“There are 5 million birdwatchers in the US who spend an average of $400 a year on equipment.”
He says: That’s Other People’s Data.
Just because a birdwatching book sold a million copies doesn’t mean your app will sell.
You need YODA—Your Own Data. Data you collect about your idea, with your specific product, in your market, using your influence and reach.
With skin in the game.
And here’s what the market told us with the Story Cycle Genie: Our hypothesis was backwards.
We thought small-to-medium businesses would be our primary market. Turns out ad agencies and marketing consultants saw it as their “wealth generation tool.”
The market will always tell you the truth. But only if you actually make contact.
The One Thing Entrepreneurs Fear Most (And Must Do First)
Contact with the market is terrifying.
Your product is your baby. You’re afraid the market will reject it.
So you prep. Delay. Procrastinate. Stay in the safe planning mode.
But Alberto’s research is clear: The number one thing you can do is have the courage to put something in front of the market in some form.
Jeff Hawkins spent three years and $50 million building the GridPad. Engineering success. Market failure. Too heavy, too bulky, too expensive.
For his next product, he took a block of wood, put paper sleeves over it with the interface he imagined, and used a chopstick as a stylus.
For one week, he carried it in his pocket and pretended it worked.
“Are you free for lunch Tuesday?” Pull out the block of wood. “Great. Tuesday lunch with Park and Sean.” Put it back in pocket.
Nothing happened. It’s just paper.
But he was testing whether he’d actually use it.
One week. Zero dollars. Complete validation.
Then he spent two years building it. That became the Palm Pilot—the form factor for every smartphone you’ve ever owned.
One week of courage saved years of potential waste.
Make Sure You’re Building the Right It Before You Build It Right
That’s Alberto’s slogan. His life’s work.
Because we’re very good at building it right. Engineers are brilliant. Developers are skilled. Designers are talented.
But 80% of the time, we’re building the wrong thing.
And the world needs entrepreneurs and innovators more than ever. We can’t afford to waste 80% of our most valuable resource on ideas that are going to flop.
So before you spend another month building, ask yourself:
Do I have YODA or OPD?
Can I state my idea as an XYZ hypothesis?
How much skin in the game do I actually have?
Have I made contact with the market, or am I still procrastinating in planning mode?
Because if you’re not embarrassed at the time you launch your product, you’ve launched too late.
The market is waiting to tell you the truth.
You just have to have the courage to listen.
Links:
- Alberto Savoia on LinkedIn
- albertosavoia.com
- The Right It book on Amazon
- Free Pretotype It PDF download
- The Math of Success for Product Managers (YouTube)
- Craft your vibrant brand story with the StoryCycle Genie™
- What users are saying about the StoryCycle Genie™
Related Episodes You’ll Love:
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• Why AI Makes Your Agency More Valuable, Not Cheaper – Drew McLellan shares research on what clients really expect from AI adoption and how agencies should respond
• The REST Method: Turning Leadership Vulnerability Into Engagement – Julie Lancaster on why failure stories create deeper connection than success stories
Alberto Savoia’s Conversation with Park Howell and Sean Schroeder on The Business of Story Podcast
PARK: Alberto, welcome to the Business of Story.
ALBERTO: Thank you Park, and hi Sean. Great to be here.
PARK: Sean is joining me today. He’s one of our co-creators of the Story Cycle Genie. I asked him to co-host because he’s the one who introduced me to your amazing book, The Right It: Why So Many Ideas Fail and How to Make Sure Yours Succeed. Sean, welcome to the show.
SEAN: Thank you for having me. I’m a big fan of your book. I’ve done multiple ventures over the years, and what I love about your book is how accessible it is. It’s not just a digital-first approach—you talk about analog ways to do pretotyping. I’m curious: can you tell us a little background about how you got there?
Why Most New Product Ideas Fail (Even With Perfect Execution)
ALBERTO: By nature, I’m an entrepreneur. I did my first startup when I was 22. My father loaned me $5,000 to buy an IBM PC, and I started building video games, selling them through newspaper ads for $29.95. That was successful.
Then I was lucky to join companies like Sun Microsystems in the ’80s as a startup. I did my own startup during the internet boom—a technology for load testing websites. In 18 months, we turned a $3 million VC investment into a $100 million exit.
Then I joined Google in the early days. I led the engineering team that launched AdWords, which now makes around $300 billion a year. I got lucky. I started thinking I was the Italian Steve Jobs—Stefano Jobini. Everything I touched turned to gold.
So I left Google and did another startup. I figured if I raised $3 million and exited at $100 million, then raising $30 million would mean a $1 billion exit. Of course, the math doesn’t work that way. For my next startup, I raised $25 million. Over five years, we built this product. Everybody told me, “Alberto, if you build it, it will be amazing. We will buy it.”
We built it. It worked exactly as we said it would. Very few people bought it. We lost the investment. The company was sold for pennies on the dollar.
If you like stories, this is the classic arc: Success goes up. Bang. You get hit on the head with failure.
I asked myself: WTF—why the failure? I had great VCs, Sequoia Capital, a fantastic team. Everybody I hired was later hired by Google. Yet it failed.
Google took me back and said, “Alberto, we’ve had our own string of failures—Google Glass, Google Groups. Why don’t you work on innovation? Why does it fail?”
I started this process and asked: How can successful teams with everything in place generate something as successful as Google Ads or Gmail, yet the very same team works on products that are complete flops?
I realized: You don’t wake up thinking you have a terrible idea. We all wake up thinking we have a great idea. There’s no such thing as good ideas and bad ideas. There are ideas that, if competently executed, will succeed. And ideas that, even if competently executed, will fail.
As an engineer, I wanted a definition. That’s how I came up with pretotyping. My slogan: Make sure you’re building the right it before you build it right. We’re very good at building it right. But so many times we build it right and there’s no market for it.
What Is Pretotyping? (The Palm Pilot Block of Wood Story)
SEAN: What was your first pretotype of your pretotype?
ALBERTO: I have props because I know you like stories. You read the yellow book, right? We started pretotyping things internally at Google. I have NDAs, so I can’t talk about most of them. But I can talk about my first personal pretotype: my pretotyping booklet.
I know 99% of books are not bestsellers. Maybe 5% make any money. So I thought: If I want to write a book about pretotyping, maybe I should pretotype the book.
A pretotype is an artifact—something you can touch—that you use to test the desirability of a product. On the cover of this booklet is my favorite pretotype: the Palm Pilot pretotype. Can I give you that story?
PARK: Please do.
ALBERTO: Jeff Hawkins was an amazing inventor. His previous product was super successful. He spent three years and $50 million to build something called the GridPad—an early version of an iPad. It was an engineering success and a market failure. Too heavy, too bulky, too expensive.
When he started his next project, he thought: I want something that fits in my pocket, like the form factor of today’s smartphones. But he wondered: Will I actually use it?
He did something amazing. He took a block of wood, put plastic and paper sleeves over it with the user interface he had in mind, and used a chopstick to pretend it was a stylus. For a week, he carried it in his pocket and pretended it worked.
He’d ask people, “Are you free for lunch next week on Tuesday?” They’d say yes. He’d pull out the block of wood: “Okay, great. Tuesday lunch with Park and Sean.” Then put it in his pocket. Of course, nothing happened—it’s just a piece of paper.
What he was testing: whether he would actually use it. He realized he would use it for just four things: calendar, notepad, to-do list, and a couple of other things. Very minimal functionality.
Once he proved he would carry it, then he went to build it. That took two years. This experiment took one week. It proved very successful and became the form factor for all smartphones.
A pretotype is any artifact you use to test the desirability of a product. Because if you’re not going to use it yourself, if people aren’t going to buy it, you’re wasting your time.
Pretotype vs. Prototype: What’s the Difference?
PARK: That’s the main difference between a pretotype and a prototype?
ALBERTO: Excellent question. People get confused. I got flack about inventing a new word. First, it’s cool to invent a new word. Second, our language has to be precise. Imprecise language leads to trouble.
Imagine you go to the doctor and say, “I’m not feeling well.” The doctor says, “Well, Park, you are sick.” Could you be a little more specific? Is it a cold, flu, pneumonia, tuberculosis? You want precision.
When people use the word “prototype,” some take two days and cost $20. Some cost millions of dollars and last years.
A pretotype is something you do much more quickly. More importantly, it tests the desirability of a product, not the viability.
What the Wright brothers built for the airplane—those were prototypes. They asked: Will it fly in the air? A pretotype asks: Will it fly in the market?
Sloppy language leads to sloppy actions and sloppy results. That’s the distinction.
How Alberto Savoia Pretotyped His Pretotyping Book in One Week
ALBERTO: I thought: I want to write a book. I don’t want to invest a lot of time. I want to see if people are interested in this concept of pretotyping. Very meta—I pretotyped pretotyping.
I asked my boss at Google: “Can I have a week to write a book about this thing I developed while I was here?” He said okay. I rented a cabin in the woods with no internet. Whatever I wrote in one week, that would be it.
This is it. 72 pages. I stapled it at Google and started handing it out to colleagues to see what happens. A lot of them came back: “Can I have another copy?” Then: “Can I have the PDF?”
I knew people were interested. Once I put it in digital form, it escaped. It landed at Stanford, which was near Google. They asked me to teach these things at Stanford. Then it exploded.
When I wanted to write a book, I could tell publishers: “I know people are interested because I wrote this booklet. It’s been translated into seven languages, most by people who didn’t even ask my permission.”
I was able to get the book deal because I proved the desirability. Fortunately, my book was a success—in that 2-5% that sells more than 2,000 copies and makes money for everybody involved.
Is Vibe Coding Good for Pretotyping or Building Products?
SEAN: We’re hearing a lot about “vibe coding”—people spinning up products very quickly. You can get ideas out there fast. But in my experience, they’re not necessarily ready for prime time, although the internet would love to tell you they are. How should we think about this?
ALBERTO: We’ve been leading toward vibe coding for the past 60 years since we started programming. I started programming in assembly language, where it would take days. Then we had higher-level languages like BASIC and Java, then more tools. Vibe coding is the process of going from speaking to computers in binary—zeros and ones—to assembly language, to now speaking in natural language.
Vibe coding democratizes technology development. One of the big obstacles for people with ideas was needing a technical team—a technical co-founder. Those were very hard to find. If you weren’t one of them, you were stuck.
Vibe coding is a great way of building pretotypes and testing market viability. I don’t know how well it extends to building it right. You have to worry about scalability, security. I don’t think we’re there yet.
PARK: So it’s good for pretotyping, not necessarily for prototyping.
ALBERTO: Exactly. At this particular point in time. But if you can spend two hours and whip up an app that would take two weeks to code by hand, my examples in the book become much more accessible to everyone.
SEAN: So you see this as a net benefit—you don’t have to allocate resources like we did even three years ago. You don’t need a technical co-founder spending weeks to months building out the first idea.
ALBERTO: Whether it’s vibe coding or offshore development, make sure you first develop something very basic and see if anybody’s interested. As is true for most podcasts, most apps in the store—99% don’t make any money. They just languish there. You want to make sure you don’t spend time doing that.
YODA Framework: Your Own Data (Not Other People’s Data)
PARK: In your book, you talk about YODA—doing your own research versus using other people’s data.
ALBERTO: Two phrases I learned at Google in the very early days: Data beats opinion and Say it with numbers. If you’re too fuzzy, you get into trouble.
When I told people “data beats opinion,” they’d say, “I have this birdwatching app idea. Here’s my data: In the US alone, there are 5 million birdwatchers who spend an average of $400 a year on equipment and cameras. Here’s a giant market.”
I’d say: That’s other people’s data. Just because a book on birdwatching sold a million copies doesn’t mean your app will sell.
You need YODA—Your Own Data. Data you collect about your idea, with your specific idea, within your area, with your personal influence and marketing reach. Most importantly, it must come with skin in the game.
The Skin in the Game Caliper: Why Opinions and Focus Groups Are Worthless
ALBERTO: I have a skin in the game caliper. I use this in my classes.
You tell me: “Alberto, I have an idea for an app. I’ve got data.”
I say: “Tell me about the data.”
“I asked my friends and they told me what they think of it.”
I call this opinion. Zero skin in the game. It costs nothing to give an opinion. People telling you “I would buy it”—no skin in the game. Polls, surveys—whether politics or products—just a waste of time.
Focus groups? I call them focus fictions. They’re good for one thing: getting insights. You can ask, “What’s the problem with this Coca-Cola?” They say, “It’s too sweet.” So maybe you make it less sweet or fewer calories. But then they tell you one thing and do completely the other.
Example: You’re McDonald’s. You run a focus group about new menu items. One result that always comes up: “You should have more healthy items on the menu, like salads.”
You put salads on the menu. Maybe 20% of people say they’d eat salad. Then you put them in the store. Nobody orders salad. Because once you smell the fries, you’re done.
That’s what marketers call the difference between stated preference (“Yes, I would have the salad”) and revealed preference (“Give me a Big Mac with fries”).
So:
- Focus groups: Zero skin in the game
- Expert opinion: Zero
- Views on social media: Zero
- Likes: Zero
The first piece of skin in the game that has one point: a valid email address. Not your made-up one like hotguy@hotmail.com. Your real work email. I don’t give my email address to just everybody.
Then you go to the next one: phone number. Even more skin in the game.
Then: time. If I tell you, “Park, I want to discuss my idea with you. Do you have 10 minutes?” And you say yes, that’s 10 skin-in-the-game points.
But for most people, since they want money, the ultimate one is: Will they pay for it? If you give me a preorder for $20, that’s a lot of skin in the game.
YODA has to be data collected about your idea. I don’t care if 300 million people buy frozen pizza. It doesn’t mean they’ll buy your frozen pizza. Give me your YODA with skin in the game.
How the Story Cycle Genie Used Skin in the Game to Validate Market Demand
PARK: We followed that precisely with the Story Cycle Genie. We got 20 beta users. They gave us financial skin in the game—each invested $500 to participate. They gave us their time—an hour or two on the genie, then a Zoom session with me for another hour or two. We also added value on that Zoom because we got their input on the genie, and I provided them branding and story advice. They got more value than just running the product.
The third thing is reputation. Are they willing to put their reputation behind what you’ve built? We had overwhelming excitement. Not one person said, “This is ridiculous.” They were more like, “When are you going to launch it?”
I told Sean and Matt Levine, our other co-creator: My biggest concern is the feedback is too positive. Have you ever had that happen?
ALBERTO: Yes. If feedback is too positive, it means there’s an initial level of interest, which doesn’t always translate into ongoing level of interest. You can get that enthusiasm and then it goes away. Usually you get the opposite because enthusiasm is very easy to get 100% of.
But if they’re willing to write an endorsement or review, that’s skin in the game. If there is skin in the game, it’s not too much of a good thing.
One of my favorite pieces of skin in the game is where you take something away from the market. I built an electronic product last month and sold it to the first 10 people for $250. They were all happy and gave great reviews.
But I wanted to really test it. Do they really want it? So I told the people who paid $250: “Thank you for the review. I’m glad you bought my gizmo. Look, this was a test. If you want to give it back to me, I’m happy to give you back the money. It was just fun for me.”
They said: “Over my dead body.”
I thought: Okay, they really like it. Even trying to take it away and them complaining is great feedback because it means they’re using the product.
When I build something and get 50 complaints about something not working, I say: That’s fantastic. They’re actually using it.
The XYZ Hypothesis: At Least X% of Y Will Do Z
PARK: That leads to the market engagement hypothesis. You’ve got an idea of what you want, back it up with numbers, then test against those numbers.
ALBERTO: The sequence is: Idea → Market engagement hypothesis (high-level, fuzzy) → XYZ hypothesis (focused and testable).
These students at Stanford had an idea for a portable air pollution monitor. They told me: “A lot of people in very polluted cities are concerned about air quality and would pay a lot for a portable air pollution monitor.”
It was very fuzzy. Who are these people? How many is “a lot”? How much would they pay?
I was doing office hours at Stanford in the engineering building. On the whiteboard, math students had left equations with X, Y, Z. I had a flash of insight: Let me speak your language.
I created the XYZ hypothesis: At least X% of Y will do Z.
This is the clearest formulation you can have for any idea. It beats the famous elevator pitch. It beats business plans, which are usually works of fiction. It beats 40 PowerPoint slides. It’s as concise as possible and impossible to forget.
Using our birdwatching app:
- Y is your target market: birdwatchers
- Z is the action you expect them to take: download Alberto’s birdwatching app and pay $5
- X% is the minimum percentage of birdwatchers you need for the idea to be viable
Let’s say there are 1 million birdwatchers. You could say: At least 1% of US birdwatchers will download the app and pay $5 for it.
In one line, you’ve got a mini business plan. If there are 1 million birdwatchers, 1% is 10,000. They pay $5 per year. You have $50,000. You go directly from idea to revenue.
It also gives you something to test. You need at least 1% to download it. The job of a hypothesis is simple: It exists to be tested and to be falsified.
Hyperzooming: How Local Experiments Validate Global Assertions
ALBERTO: The other part is hyperzooming. You start with a hypothesis that’s broad—your expectation that eventually 1% of all people in the market will adopt. But you can do local experiments to validate global assertions.
My favorite example: the world’s biggest hypothesis we know of—gravity. Einstein’s general relativity says gravity bends space and therefore bends light. That’s a big hypothesis. How do you test it through the entire universe?
They discovered conditions great for one experiment that could prove or disprove it. There was an eclipse and a star in the sky. If at the time of the eclipse, when the light from the sun is obscured, we see this light shifted by two degrees, it means relativity works. The light was bent by the gravity of the sun.
They took this great big idea and hyperzoom to this specific case: If it bends space-time in the universe, it must bend it in this particular case.
Same with your idea. If your goal is to reach all birdwatchers, I ask: How can you minimize time to data, dollars to data, and distance to data?
Is there a group of birdwatchers in your town? The Silicon Valley Birdwatchers Group? Go there. Show them the design for the app. Say: “I’m going to release a pretotype of this app in a month.” Give them business cards: “Go to the website, sign up, and be one of our beta customers.”
If nobody picks up the card, nobody signs up or gives you their email, you know it’s going to be pretty hard to reach a broader mass. But you’ve done the experiment. You got your first piece of data very early.
The number one thing entrepreneurs and innovators are afraid of: contact with the market. Contact with the market is scary.
It’s like approaching someone and asking for a date. It’s terrifying because we’re afraid of rejection.
The same happens with your product. Your product is your baby. You put it on the market, you’re afraid the market rejects it. So you prep it, delay, procrastinate.
Instead, the number one thing you can do: Go to the market in some form. Have the courage. The market will tell you what to do. From then on, everything becomes easy because you’ve broken the ice with the market.
How to Pretotype a Physical Product or Service (The Dirty Soda Example)
SEAN: We’ve talked a lot about digital products. But one of the things I love about your book is you have several examples like day-old sushi and the bookstore. My daughter who’s 12 wants to create a pop-up dirty soda stand. What pretotyping would you recommend for her?
ALBERTO: First, I’m embarrassed—I don’t know what a dirty soda is.
SEAN: You take regular soda, put syrups in it, different things. One of my favorites is Coke Zero with lime and coconut.
ALBERTO: Okay. Let’s assume your daughter is 22 and says, “Dad, I want to go into the dirty soda business. Can you give me $50,000 to buy a taco truck and convert it to dirty soda?”
I would say: “Listen, unfortunately for you, Dad’s read this book. As much as I love you, before I give you a lot of skin in the game, let’s make sure there’s a market for this.”
Time to data, dollars to data, distance to data. Who would you expect to buy this dirty soda?
“Students like it a lot.”
Well, you’re in college. Why don’t you do this? Colleges and universities are pretty free about people putting up tables. It doesn’t require a lot of permission. Go put up a table with your dirty soda. “$2 for dirty soda.” See how many you sell.
When you do it, make sure you collect data. Maybe as a dad, you follow her. Look at how many people passed by the dirty soda stand. Out of 100 people who passed, two decided to buy the dirty soda. You start to have metrics.
That shows you the initial level of interest in the concept. You prove that 2% of university students, if they have to choose between a regular Coke and a dirty Coke, will choose the dirty.
That’s terrible branding, by the way—dirty soda.
PARK: It works for martinis. It should work for sodas.
The One Night Stand Pretotype: Leverage What Already Exists
ALBERTO: What’s the quickest way to validate your hypothesis? With the book, you have all the pretotypes with memorable names. I have the One Night Stand: Before you buy the taco truck for $50,000, maybe you can find Jose’s taco truck.
This is one of my favorites: Leverage something that already exists.
Go to Jose’s taco truck: “Hey Jose, I’m an entrepreneur like you. I’d love to have my own food truck. Can I pay you $100 to run a little experiment? Will you allow me to put ‘Dirty Soda – $3’ right under ‘Coke or Pepsi – $2’? Every time somebody comes and says they’d like a Coke, ask them: ‘Would you like to try a dirty Coke?'”
That way, you use a place where there’s already traffic. You spend very little money compared to a focus group. You get real data.
At the end of the day: “Okay Jose, what was the data?”
“200 people came by. 100 wanted soda. I offered dirty soda to all of them. Only two went for it.”
That already gives you a calibration of the market—a very quick way to get market data.
Why Research Doesn’t Have to Cost a Fortune Anymore
PARK: You underscore in your book that research shouldn’t cost a lot of money in this day and age of the internet.
ALBERTO: Especially if you’re an entrepreneur, you can take risks. One example I have a video about is what I call the Infiltrator Pretotype using IKEA.
The Infiltrator Pretotype: How to Test Products in Retail Stores (The IKEA Wall Hub Story)
These people came up with a gizmo they thought would be perfect for IKEA: the Wall Hub. Something you put on the wall for your keys and mail. They wondered: Would people buy it? Where would people buy it? They thought IKEA would be the perfect place.
What did they do? They went on eBay and bought an IKEA employee t-shirt—the big blue shirt with the IKEA logo. They could enter the store and people thought they were IKEA employees.
They had a handful of 3D-printed wall hubs. They created fake IKEA tags, changed the name to “Valhub” (because IKEA has all those strange names), put a fake IKEA tag on it, and put it in the store. Then they stood back and filmed.
There’s a video if you look for “IKEA Valhub example.” They filmed people walking by: “Oh, look, interesting.” They put the Valhub in their shopping cart and happily went to checkout.
Of course, since it’s a fake tag, the IKEA staff didn’t know what to do. But what you’ve proven: If you take an item for 19 bucks and put it in your cart, that is skin in the game. That’s the ultimate skin in the game. People are willing to pay for it.
They validated there was a market for it. IKEA probably wasn’t too happy about that. But they’re just entrepreneurs—they wouldn’t get in trouble.
People always tell me: “Alberto, we’re a big corporation. We can’t do something like that.”
I say: “You’re right. But because you’re a big corporation, you can pay a mom-and-pop store $1,000 to run the experiment for you.”
If you’re an entrepreneur, you have to take some risk. If you don’t want to take any risks—the risk of rejection or getting your hand slapped by IKEA—maybe you shouldn’t be an entrepreneur.
Having said that: Don’t do anything immoral, unethical, or illegal. But it’s okay to push the envelope once in a while. Maybe be ready to pay some fines.
By the way, Airbnb started by renting an air mattress in a room in San Francisco without a hospitality license. Uber started in New York City with just three cars operating like limousines or taxis without the proper service license. Those things were illegal.
I’m not saying you should break the law. But at some point, if people don’t take chances—and don’t harm anybody—push the envelope a little bit.
“Ignore the Law”: What Entrepreneurs Must Understand About Innovation and Regulation
Another rule for entrepreneurs and innovators: You’ve heard the expression “Ignorance of the law is no excuse.” I have another expression: Ignore the law.
I have a video about that. It doesn’t mean you do illegal things. What it means: If your idea doesn’t conform to current laws, but the market wants it, pursue it. Eventually it will change the laws.
Perfect example: self-driving cars. Waymo started at Google about 12 years ago. I was still there. At the time, do you think it was legal to have a car with no driver on the road? Absolutely not.
But we thought: Eventually, when this technology proves itself, we’ll get there. So you ignore the law—not that you break it, but if this works, it will change the law.
Right now I live in Mountain View. My neighbor works for Waymo. Every day I see a driverless car picking him up and driving him to work. I took my first Waymo ride a few months ago. They are fantastic.
Entrepreneurs must ignore the law as it is written today. Just like Uber was illegal—it was illegal at airports, a lot of towns refused to have it. Now it’s everywhere.
PARK: Our son Parker is a technologist and moviemaker in Austin. He wrote me the other day: “Hey Dad, I took my first Waymo ride.” I said, “How was it?” He said, “Ridiculously inefficient. It made every possible wrong turn to get me to my destination and ultimately dropped me off in the Waymo recharging parking lot.”
ALBERTO: That was one bad experience. Mine was actually amazing. There are some growing pains at the beginning. But ultimately, you know exactly where that’s going. I see the future nice and clear. I’m glad that when I’m old and can’t drive, I won’t have to worry about that.
How AI Validates Product Ideas in 6 Minutes (Story Cycle Genie Assessment)
PARK: Alberto, it’s been absolutely fascinating to have you here. Like we do with all our guests, we ran your brand through our Story Cycle Genie. I sent you the brand assessment and the longer brand narrative strategy document that builds the brand brain in the Genie. That took about six minutes. How did it land with you? Accuracy, intelligence, interest?
ALBERTO: It was very impressive. I’m not just saying that to be nice, because I’m not nice when it comes to business. Being nice is like being mean. Grandma being nice and feeding you at Thanksgiving so you gain four pounds—there’s nice.
My being nice to entrepreneurs is not giving them any BS. I’ll give you honest feedback.
I was very impressed. Six minutes—that’s a very good example of how focused AI can deliver something of value. Every day I’m impressed by how AI can produce content that, with some human moderation, is very high quality. It didn’t feel slapped together.
That’s the area where you want to be careful with AI. The very same thing—I received your thing, which I know was curated. You didn’t just ask random things. I know there were the right prompts and the right editing.
I get emails that are so clearly AI-generated. “Hey Alberto, I read your book, great.” Then six long paragraphs that I can tell are 100% AI. This person has not read my book. There’s absolutely nothing real or genuine about it.
The secret: This is a tool that complements your insights and your understanding. It translates it for you. With that, it was effective. I opened it very skeptical. By the time I read down, I said: Yeah, this is actually pretty damn good and actionable. Well done. I was impressed.
I believe in the power of stories. All I told you was stories—the IKEA story, the Palm Pilot story. Those are so much more memorable than statistics or raw data.
Where to Learn More About Alberto Savoia and Pretotyping
PARK: We appreciate it. Thank you so much. Sean, any closing words or questions?
SEAN: No, I think we covered all my questions. The vibe coding thing was the big one—how to reconcile that and see if it’s a feature or a bug when it comes to pretotyping and launching products.
ALBERTO: It’s a great tool. It’s the future. It democratizes technology development, which right now requires you to be a super geek in very high demand charging $300,000 a year just to write an app. It’s great that it democratizes that.
PARK: Alberto, where’s the best place to send people to learn more about you and your work?
ALBERTO: Just type “Alberto Savoia” or “Pretotyping” and Google will steer you right.
Here’s my pitch: The book came out a while back. I make 50 cents per copy, so that’s not going to change my life. I’m more about changing the world. 50 cents won’t change my life. The book will change yours.
My passion is getting more people to do product management and come up with ideas in a more systematic way. I put a series of videos on YouTube for product managers and innovators called The Math of Success for Product Managers and Innovators, where I take the ideas of the book and formalize them a little more. I have a lot of material on YouTube that augments the book.
Also, Pretotype It is free. I developed it at Google, so it’s still free. There’s a 10th anniversary edition.
I don’t have anything to peddle except this: I don’t want to see entrepreneurs fail. The world needs entrepreneurs and innovators more than ever. If 80% of the things they work on fail because of the Law of Failure and because they haven’t pretotyped it, we’re taking our number one most valuable resource—innovators and entrepreneurs—and wasting 80% of it on ideas that are going to flop.
That’s how I want to help the world, myself, my kids, and everybody.
PARK: That’s awesome. Can I get a copy or PDF of your pretotype book? I’ll put it in the show notes so people can download it right there.
ALBERTO: Absolutely. I would love to.
PARK: You’ve got a great website: albertosavoia.com. I think it’s worth letting people know to go there as well.
ALBERTO: I don’t know how great it is because I never update it. It could use a refresh. But I love simple websites because it means people are busy doing stuff rather than maintaining websites.
Thank you, Sean. Thank you, Park. It’s been great. I always enjoy doing this. You had great questions. Congratulations on the Story Cycle Genie. I think it’s something very important. More people need to follow it. Thanks again.
PARK: Thank you.
SEAN: Thank you so much for joining us. That was awesome.
Alberto Savoia and Pretotyping FAQs:
What is pretotyping?
Pretotyping is the practice of testing the market desirability of a product idea before investing significant time and money in building it. A pretotype is any artifact you can use to test whether people will actually want and use your product. The philosophy: Make sure you’re building the right it before you build it right.
Alberto Savoia developed pretotyping at Google to help innovators avoid the Law of Failure, which states that most new ideas fail in the market regardless of execution quality.
How is pretotyping different from prototyping?
The key difference:
- Prototype tests whether it will fly in the air (technical viability)
- Pretotype tests whether it will fly in the market (customer desirability)
Prototypes answer: “Can we build this?” and “Does it work technically?” They can take years and cost millions.
Pretotypes answer: “Will people actually want this?” and “Will they pay for it?” They typically take days or weeks and cost very little.
As Savoia says: “Sloppy language leads to sloppy actions and sloppy results.” The distinction matters because precision in language creates precision in execution.
What is the XYZ hypothesis?
The XYZ hypothesis is a simple formula for expressing any business idea with testable precision:
At least X% of Y will do Z.
Where:
- Y = Your target market (who you’re targeting)
- Z = The action you expect them to take (download, purchase, subscribe, etc.)
- X% = The minimum percentage needed for your idea to be viable
Example: “At least 1% of US birdwatchers will download Alberto’s birdwatching app and pay $5 for it.”
This formula beats elevator pitches and business plans because it’s:
- Impossible to forget
- Immediately testable
- Forces you to “say it with numbers”
- Goes directly from idea to revenue projection
What does YODA mean in pretotyping?
YODA stands for Your Own Data—data you collect specifically about your idea, with your product, in your market, using your influence and reach.
YODA is different from OPD (Other People’s Data). Just because 5 million people buy birdwatching equipment doesn’t mean they’ll buy your birdwatching app. Just because a competitor’s book sold a million copies doesn’t mean yours will.
YODA must come with skin in the game—real commitment from potential customers, not just opinions or survey responses.
Two key principles from Google that drive YODA:
- Data beats opinion
- Say it with numbers
What is “skin in the game” in pretotyping?
Skin in the game measures real commitment from potential customers. It’s the antidote to worthless opinions and stated preferences.
Skin in the Game Hierarchy (from zero to highest):
- 0 points: Opinions, focus groups, surveys, social media likes, expert opinions
- 1 point: Valid email address (not throwaway)
- 2 points: Phone number
- 10 points: 10 minutes of their time
- Highest: Money (pre-orders, purchases, subscriptions)
The more skin in the game, the more reliable the data. People will tell you they’d eat the salad (stated preference), but they’ll order the Big Mac and fries (revealed preference). Only actual behavior with consequences tells the truth.
What is hyperzooming in pretotyping?
Hyperzooming is the practice of using local experiments to validate global assertions.
Instead of trying to test your hypothesis with your entire target market (expensive, slow, difficult), you zoom in on a small, accessible subset that can give you reliable early data.
Example: Instead of trying to reach all 1 million US birdwatchers, you find the Silicon Valley Birdwatchers Group in your town and test with them first.
The key is minimizing:
- Time to data: How quickly can you get real market feedback?
- Dollars to data: How cheaply can you test your hypothesis?
- Distance to data: How close/accessible is your test market?
Savoia uses Einstein’s theory of general relativity as the ultimate example: Instead of testing gravity across the entire universe, scientists used one eclipse to validate the theory through a specific, local experiment.
Why do focus groups fail to predict product success?
Focus groups suffer from the gap between stated preference and revealed preference.
Stated preference: What people say they’ll do (“I’d order the salad”) Revealed preference: What people actually do (orders the Big Mac and fries)
The McDonald’s example: Focus groups consistently say McDonald’s should add more healthy items like salads. When McDonald’s adds salads, almost nobody buys them. Once you smell the fries, stated preferences disappear.
Focus groups have zero skin in the game. It costs nothing to give an opinion. Savoia calls them “focus fictions” because they’re good for insights about problems but terrible at predicting actual buying behavior.
Only when people commit something of value—email, time, money, reputation—do you get reliable data.
What is the Law of Failure?
The Law of Failure states that most new ideas fail in the market, regardless of how well they’re executed.
Savoia’s research shows that even world-class teams with proper funding, great execution, and expert guidance fail 80% of the time. The very same Google team that created Gmail and Google Maps also worked on products that completely flopped (Google Glass, Google Groups).
The problem isn’t execution—it’s building the wrong thing. There’s no such thing as inherently good or bad ideas. There are:
- Ideas that, if competently executed, will succeed
- Ideas that, even if competently executed, will fail
Pretotyping exists to identify which category your idea falls into before you waste 80% of innovation resources building something nobody wants.
How do you pretotype a physical product or service?
Physical product pretotyping uses creative, low-cost methods to test desirability:
The One Night Stand: Borrow or rent existing infrastructure instead of buying your own. (Example: Pay Jose $100 to test dirty soda sales from his taco truck instead of buying a $50,000 truck)
The Infiltrator: Place your pretotype in an existing retail environment. (Example: IKEA Valhub—placed 3D-printed product on IKEA shelves with fake tags to test buying behavior)
The Simple Setup: Use a basic table or stand in high-traffic areas. (Example: College campus table with dirty soda to collect real purchase data)
Key principles:
- Leverage what already exists
- Minimize time to data, dollars to data, distance to data
- Collect actual behavioral data with skin in the game
- Test locally to validate globally (hyperzooming)
What role does vibe coding play in pretotyping?
Vibe coding democratizes technology development by allowing people to create functional apps and tools using natural language instead of traditional programming.
Benefits for pretotyping:
- Dramatically reduces time to create testable products (hours instead of weeks)
- Eliminates need for technical co-founder for initial market testing
- Makes pretotyping examples more accessible to everyone
- Lowers barriers to market contact
Current limitations:
- Great for pretotyping (testing market desirability)
- Not yet proven for “building it right” (scalability, security, production readiness)
The evolution: From binary code → assembly language → high-level languages → vibe coding with natural language. Each step democratizes who can test product ideas.
How much does pretotyping cost?
Pretotyping should cost very little compared to traditional market research:
Low-cost examples from the interview:
- $0: Carrying block of wood in pocket for a week (Palm Pilot pretotype)
- $100: Renting space on Jose’s taco truck to test dirty soda sales
- $1,000: Paying a mom-and-pop store to run an experiment for you
- Cost of materials: 3D printing a few samples, printing fake tags
Compare to traditional methods:
- Focus groups: Thousands of dollars, zero skin in the game, unreliable data
- Building a prototype: Weeks to years, $20 to millions of dollars
- Full product development: Months to years, significant capital investment
The goal: Minimize dollars to data, time to data, and distance to data. Get real market feedback as quickly and cheaply as possible before major investment.
What is market engagement hypothesis vs. XYZ hypothesis?
These represent two stages of idea clarity:
Market Engagement Hypothesis (broad, fuzzy): “A lot of people in very polluted cities are concerned about air quality and would pay a lot for a portable air pollution monitor.”
Problems: Who are “a lot of people”? How many is “a lot”? What’s “a lot” of money?
XYZ Hypothesis (focused, testable): “At least 5% of expectant mothers in Shanghai will purchase a portable air pollution monitor for $150 within the first year.”
The sequence:
- Idea: General concept
- Market Engagement Hypothesis: High-level, fuzzy expression
- XYZ Hypothesis: Specific, testable, numerical assertion
The XYZ hypothesis exists to be tested and falsified. If you can’t state your idea in XYZ format, you don’t understand it well enough yet.
How do you handle overly positive feedback during pretotyping?
Overly positive feedback can be a warning sign:
The problem: High initial enthusiasm doesn’t always translate to ongoing interest or actual purchasing behavior.
How to validate positive feedback:
- Increase skin in the game: Move from opinions to email addresses to money
- Test revealed preference: Don’t trust what they say—watch what they do
- Try to take it away: Offer refunds or the option to return the product. If they say “over my dead body,” the enthusiasm is real
- Look for reputation risk: Will they publicly endorse it? Write a review? Recommend to colleagues?
- Convert to ongoing engagement: Initial downloads mean nothing if nobody uses the product after a week
The Story Cycle Genie example: Park Howell’s team got overwhelmingly positive feedback but validated it with:
- $500 skin in the game per beta user
- 1-2 hours of usage time per user
- 1-2 hours on Zoom providing feedback
- Willingness to use it in their actual businesses
What does “ignore the law” mean for entrepreneurs?
“Ignore the law” means: If your idea doesn’t conform to current laws, but the market wants it, pursue it. Eventually it will change the laws.
This is NOT about breaking laws or doing anything immoral, unethical, or illegal. It’s about:
Not letting current regulations kill innovation:
- Self-driving cars were illegal when Waymo started
- Airbnb started by renting air mattresses without hospitality licenses
- Uber started operating without proper taxi/limousine licenses
The entrepreneurial principle: If your technology or business model proves valuable to the market and doesn’t harm people, pursue it. The laws will eventually adapt.
Contrast with traditional advice: “Ignorance of the law is no excuse” (you must know all regulations). Savoia’s version: “Ignore the law” (as it’s written today, because your innovation may change it tomorrow).
Boundaries: Don’t harm anybody. Be willing to push the envelope. Maybe be ready to pay some fines. But create value the market wants.
How do you minimize time to data, dollars to data, and distance to data?
Time to data: How quickly can you get real market feedback?
- Use existing infrastructure (borrow, rent, partner)
- Do local experiments before global rollouts
- Test with accessible groups first
- Example: One week carrying block of wood vs. two years building Palm Pilot
Dollars to data: How cheaply can you test your hypothesis?
- Leverage what already exists instead of building from scratch
- Use creative low-cost pretotypes (cardboard, 3D printing, temporary setups)
- Partner with existing businesses for $100-$1,000 instead of $50,000+ infrastructure
- Example: $100 to Jose’s taco truck vs. $50,000 for your own truck
Distance to data: How accessible is your test market?
- Start with local groups in your town/region
- Use communities you already have access to (college campus, local clubs, nearby businesses)
- Test with people you can easily reach before trying to reach nationwide markets
- Example: Silicon Valley Birdwatchers Group vs. all 1 million US birdwatchers
The goal: Break the ice with the market as quickly, cheaply, and locally as possible. The market will tell you what to do next.
Why is contact with the market so important?
Contact with the market is the #1 thing entrepreneurs fear but the #1 thing they must do.
Why entrepreneurs avoid it:
- Fear of rejection (like asking someone on a date)
- Product is their “baby”—afraid of market rejection
- Leads to prep, delay, procrastination
- Preference for staying in “safe” planning mode
Why it’s essential:
- The market will tell you what to do
- Everything becomes easier after you break the ice
- You get real data instead of assumptions
- You discover actual vs. stated preferences
- You find out early if you’re wasting your time
The courage principle: Have the courage to put something in front of the market in some form. Even if it’s embarrassing. Even if it’s incomplete. As Reid Hoffman says: “If you’re not embarrassed at the time you launch your product, you’ve launched too late.”
Once you make that first contact, you move from theory to reality. From assumptions to data. From fear to action.
What are some famous pretotype examples?
Palm Pilot (Jeff Hawkins): Carried a block of wood with paper interface drawings in his pocket for a week, pretending it worked. Tested whether he’d actually use it before spending two years building it. Proved he’d use it for just four functions. Became the form factor for all smartphones.
Pretotype It Book (Alberto Savoia): Wrote 72-page booklet in one week, stapled it at Google, handed it to colleagues. Demand proved market interest. Got translated into seven languages (mostly without permission). Used to secure book deal. Book became a success.
IKEA Valhub (Wall Hub creators): Bought IKEA employee t-shirt on eBay, created fake IKEA tags, placed 3D-printed wall hubs on IKEA shelves. Filmed customers putting items in shopping cart. Validated willingness to pay before building inventory.
Dirty Soda Test (Hypothetical): Pay existing taco truck $100 to add “Dirty Soda – $3” to menu and track sales. Test market desirability using existing traffic and infrastructure before buying $50,000 truck.
How do you calculate skin in the game?
Savoia uses a Skin in the Game Caliper with point values:
Zero points (unreliable data):
- Opinions from friends/family
- Focus group responses
- Survey results
- Social media likes, views, comments
- Expert opinions
- “I would buy it” statements
1 point: Valid email address (real work email, not throwaway)
2 points: Phone number
10 points: 10 minutes of their time (scales linearly)
Highest points: Money (pre-orders, purchases, subscriptions)
Advanced validation: Trying to take it away and them refusing (“over my dead body”). Complaints about broken features (means they’re using it).
The principle: Only commitment with consequences reveals true market interest. Stated preferences lie. Revealed preferences tell the truth.
What is the difference between initial and ongoing level of interest?
Initial level of interest: The enthusiasm people show when first exposed to your idea. Easy to generate. Can be misleading.
Ongoing level of interest: Whether people continue to engage, use, and pay for your product over time.
Why the distinction matters:
- You can get 100% initial enthusiasm easily
- Freemium models: 100 people sign up for free, only 1-2 might pay
- Downloads don’t equal usage
- Trial users don’t equal paying customers
The funnel (typical drop by two orders of magnitude per step):
- 10,000 see your ad
- 100 click on it
- 1 makes a purchase
Validation strategy:
- Get initial interest (free downloads, email signups)
- Measure ongoing engagement (usage over weeks/months)
- Test conversion to paid (introduce pricing)
- Monitor retention (do they keep paying?)
- Validate habits (sunk cost fallacy kicks in—see Netflix, Apple TV price increases)
Once users invest time and form habits, ongoing interest becomes more predictable.
Why do focus groups fail to predict product success?
Focus groups suffer from the gap between stated preference and revealed preference.
Stated preference: What people say they’ll do (“I’d order the salad”) Revealed preference: What people actually do (orders the Big Mac and fries)
The McDonald’s example: Focus groups consistently say McDonald’s should add more healthy items like salads. When McDonald’s adds salads, almost nobody buys them. Once you smell the fries, stated preferences disappear.
Focus groups have zero skin in the game. It costs nothing to give an opinion. Savoia calls them “focus fictions” because they’re good for insights about problems but terrible at predicting actual buying behavior.
Only when people commit something of value—email, time, money, reputation—do you get reliable data.
What is the Law of Failure?
The Law of Failure states that most new ideas fail in the market, regardless of how well they’re executed.
Savoia’s research shows that even world-class teams with proper funding, great execution, and expert guidance fail 80% of the time. The very same Google team that created Gmail and Google Maps also worked on products that completely flopped (Google Glass, Google Groups).
The problem isn’t execution—it’s building the wrong thing. There’s no such thing as inherently good or bad ideas. There are:
- Ideas that, if competently executed, will succeed
- Ideas that, even if competently executed, will fail
Pretotyping exists to identify which category your idea falls into before you waste 80% of innovation resources building something nobody wants.
How do you pretotype a physical product or service?
Physical product pretotyping uses creative, low-cost methods to test desirability:
The One Night Stand: Borrow or rent existing infrastructure instead of buying your own. (Example: Pay Jose $100 to test dirty soda sales from his taco truck instead of buying a $50,000 truck)
The Infiltrator: Place your pretotype in an existing retail environment. (Example: IKEA Valhub—placed 3D-printed product on IKEA shelves with fake tags to test buying behavior)
The Simple Setup: Use a basic table or stand in high-traffic areas. (Example: College campus table with dirty soda to collect real purchase data)
Key principles:
- Leverage what already exists
- Minimize time to data, dollars to data, distance to data
- Collect actual behavioral data with skin in the game
- Test locally to validate globally (hyperzooming)
What role does vibe coding play in pretotyping?
Vibe coding democratizes technology development by allowing people to create functional apps and tools using natural language instead of traditional programming.
Benefits for pretotyping:
- Dramatically reduces time to create testable products (hours instead of weeks)
- Eliminates need for technical co-founder for initial market testing
- Makes pretotyping examples more accessible to everyone
- Lowers barriers to market contact
Current limitations:
- Great for pretotyping (testing market desirability)
- Not yet proven for “building it right” (scalability, security, production readiness)
The evolution: From binary code → assembly language → high-level languages → vibe coding with natural language. Each step democratizes who can test product ideas.
How much does pretotyping cost?
Pretotyping should cost very little compared to traditional market research:
Low-cost examples from the interview:
- $0: Carrying block of wood in pocket for a week (Palm Pilot pretotype)
- $100: Renting space on Jose’s taco truck to test dirty soda sales
- $1,000: Paying a mom-and-pop store to run an experiment for you
- Cost of materials: 3D printing a few samples, printing fake tags
Compare to traditional methods:
- Focus groups: Thousands of dollars, zero skin in the game, unreliable data
- Building a prototype: Weeks to years, $20 to millions of dollars
- Full product development: Months to years, significant capital investment
The goal: Minimize dollars to data, time to data, and distance to data. Get real market feedback as quickly and cheaply as possible before major investment.
What is market engagement hypothesis vs. XYZ hypothesis?
These represent two stages of idea clarity:
Market Engagement Hypothesis (broad, fuzzy): “A lot of people in very polluted cities are concerned about air quality and would pay a lot for a portable air pollution monitor.”
Problems: Who are “a lot of people”? How many is “a lot”? What’s “a lot” of money?
XYZ Hypothesis (focused, testable): “At least 5% of expectant mothers in Shanghai will purchase a portable air pollution monitor for $150 within the first year.”
The sequence:
- Idea: General concept
- Market Engagement Hypothesis: High-level, fuzzy expression
- XYZ Hypothesis: Specific, testable, numerical assertion
The XYZ hypothesis exists to be tested and falsified. If you can’t state your idea in XYZ format, you don’t understand it well enough yet.
How do you handle overly positive feedback during pretotyping?
Overly positive feedback can be a warning sign:
The problem: High initial enthusiasm doesn’t always translate to ongoing interest or actual purchasing behavior.
How to validate positive feedback:
- Increase skin in the game: Move from opinions to email addresses to money
- Test revealed preference: Don’t trust what they say—watch what they do
- Try to take it away: Offer refunds or the option to return the product. If they say “over my dead body,” the enthusiasm is real
- Look for reputation risk: Will they publicly endorse it? Write a review? Recommend to colleagues?
- Convert to ongoing engagement: Initial downloads mean nothing if nobody uses the product after a week
The Story Cycle Genie example: Park Howell’s team got overwhelmingly positive feedback but validated it with:
- $500 skin in the game per beta user
- 1-2 hours of usage time per user
- 1-2 hours on Zoom providing feedback
- Willingness to use it in their actual businesses
What does “ignore the law” mean for entrepreneurs?
“Ignore the law” means: If your idea doesn’t conform to current laws, but the market wants it, pursue it. Eventually it will change the laws.
This is NOT about breaking laws or doing anything immoral, unethical, or illegal. It’s about:
Not letting current regulations kill innovation:
- Self-driving cars were illegal when Waymo started
- Airbnb started by renting air mattresses without hospitality licenses
- Uber started operating without proper taxi/limousine licenses
The entrepreneurial principle: If your technology or business model proves valuable to the market and doesn’t harm people, pursue it. The laws will eventually adapt.
Contrast with traditional advice: “Ignorance of the law is no excuse” (you must know all regulations). Savoia’s version: “Ignore the law” (as it’s written today, because your innovation may change it tomorrow).
Boundaries: Don’t harm anybody. Be willing to push the envelope. Maybe be ready to pay some fines. But create value the market wants.
How do you minimize time to data, dollars to data, and distance to data?
Time to data: How quickly can you get real market feedback?
- Use existing infrastructure (borrow, rent, partner)
- Do local experiments before global rollouts
- Test with accessible groups first
- Example: One week carrying block of wood vs. two years building Palm Pilot
Dollars to data: How cheaply can you test your hypothesis?
- Leverage what already exists instead of building from scratch
- Use creative low-cost pretotypes (cardboard, 3D printing, temporary setups)
- Partner with existing businesses for $100-$1,000 instead of $50,000+ infrastructure
- Example: $100 to Jose’s taco truck vs. $50,000 for your own truck
Distance to data: How accessible is your test market?
- Start with local groups in your town/region
- Use communities you already have access to (college campus, local clubs, nearby businesses)
- Test with people you can easily reach before trying to reach nationwide markets
- Example: Silicon Valley Birdwatchers Group vs. all 1 million US birdwatchers
The goal: Break the ice with the market as quickly, cheaply, and locally as possible. The market will tell you what to do next.
Why is contact with the market so important?
Contact with the market is the #1 thing entrepreneurs fear but the #1 thing they must do.
Why entrepreneurs avoid it:
- Fear of rejection (like asking someone on a date)
- Product is their “baby”—afraid of market rejection
- Leads to prep, delay, procrastination
- Preference for staying in “safe” planning mode
Why it’s essential:
- The market will tell you what to do
- Everything becomes easier after you break the ice
- You get real data instead of assumptions
- You discover actual vs. stated preferences
- You find out early if you’re wasting your time
The courage principle: Have the courage to put something in front of the market in some form. Even if it’s embarrassing. Even if it’s incomplete. As Reid Hoffman says: “If you’re not embarrassed at the time you launch your product, you’ve launched too late.”
Once you make that first contact, you move from theory to reality. From assumptions to data. From fear to action.
What are some famous pretotype examples?
Palm Pilot (Jeff Hawkins): Carried a block of wood with paper interface drawings in his pocket for a week, pretending it worked. Tested whether he’d actually use it before spending two years building it. Proved he’d use it for just four functions. Became the form factor for all smartphones.
Pretotype It Book (Alberto Savoia): Wrote 72-page booklet in one week, stapled it at Google, handed it to colleagues. Demand proved market interest. Got translated into seven languages (mostly without permission). Used to secure book deal. Book became a success.
IKEA Valhub (Wall Hub creators): Bought IKEA employee t-shirt on eBay, created fake IKEA tags, placed 3D-printed wall hubs on IKEA shelves. Filmed customers putting items in shopping cart. Validated willingness to pay before building inventory.
Dirty Soda Test (Hypothetical): Pay existing taco truck $100 to add “Dirty Soda – $3” to menu and track sales. Test market desirability using existing traffic and infrastructure before buying $50,000 truck.
How do you calculate skin in the game?
Savoia uses a Skin in the Game Caliper with point values:
Zero points (unreliable data):
- Opinions from friends/family
- Focus group responses
- Survey results
- Social media likes, views, comments
- Expert opinions
- “I would buy it” statements
1 point: Valid email address (real work email, not throwaway)
2 points: Phone number
10 points: 10 minutes of their time (scales linearly)
Highest points: Money (pre-orders, purchases, subscriptions)
Advanced validation: Trying to take it away and them refusing (“over my dead body”). Complaints about broken features (means they’re using it).
The principle: Only commitment with consequences reveals true market interest. Stated preferences lie. Revealed preferences tell the truth.
What is the difference between initial and ongoing level of interest?
Initial level of interest: The enthusiasm people show when first exposed to your idea. Easy to generate. Can be misleading.
Ongoing level of interest: Whether people continue to engage, use, and pay for your product over time.
Why the distinction matters:
- You can get 100% initial enthusiasm easily
- Freemium models: 100 people sign up for free, only 1-2 might pay
- Downloads don’t equal usage
- Trial users don’t equal paying customers
The funnel (typical drop by two orders of magnitude per step):
- 10,000 see your ad
- 100 click on it
- 1 makes a purchase
Validation strategy:
- Get initial interest (free downloads, email signups)
- Measure ongoing engagement (usage over weeks/months)
- Test conversion to paid (introduce pricing)
- Monitor retention (do they keep paying?)
- Validate habits (sunk cost fallacy kicks in—see Netflix, Apple TV price increases)
Once users invest time and form habits, ongoing interest becomes more predictable.
How should entrepreneurs think about AI-generated content?
Savoia’s perspective on AI in content creation:
The good: Focused AI with proper curation can deliver high-quality, valuable content. The Story Cycle Genie assessment took 6 minutes and was “actually pretty damn good and actionable.”
The bad: Clearly AI-generated content with no human curation is worthless. Emails with six long paragraphs that are obviously 100% AI with nothing real or genuine.
The principle: AI is a tool that complements your insights and understanding. It translates and enhances, but doesn’t replace authentic expertise.
Requirements for effective AI content:
- Proper prompts (not random questions)
- Human curation and editing
- Real insights and understanding as foundation
- Integration of genuine expertise
- Doesn’t feel “slapped together”
Warning signs of bad AI content:
- Generic praise with no specifics
- Long paragraphs with no authentic voice
- No evidence of actual engagement with subject matter
- Lacks genuine insights or original perspective
What resources does Alberto Savoia offer for learning pretotyping?
Free resources:
- Pretotype It book (PDF) – Free download, 10th anniversary edition available
- YouTube series: “The Math of Success for Product Managers and Innovators” – Formalizes book concepts with additional material
- Website: albertosavoia.com (simple, information-focused)
Paid resource:
- The Right It book: Available for purchase (Savoia makes $0.50 per copy, states “won’t change my life, but will change yours”)
The mission: Help entrepreneurs and innovators avoid wasting 80% of their efforts on ideas that will fail. Get more people doing product management and idea development systematically.
Search terms: “Alberto Savoia” or “Pretotyping” in Google
What are the main reasons new product ideas fail?
Based on Savoia’s experience and research:
The core problem: Building the wrong it, even when building it right.
Common failure patterns:
- Assumption without validation: “If you build it, they will come” mentality
- Other People’s Data: Relying on market statistics instead of YODA
- Stated vs. revealed preferences: Believing what people say instead of watching what they do
- Fear of market contact: Procrastinating on getting real customer feedback
- Building too much too soon: Spending years and millions on full product before testing desirability
Success patterns aren’t about quality:
- Best teams fail (Google Glass by same team that created Gmail)
- Best funding fails (Sequoia Capital-backed companies that flopped)
- Perfect execution fails (products that work exactly as designed but nobody buys)
The solution: Test desirability first with pretotypes before investing in viability with prototypes or full products.
How did Alberto Savoia validate the Story Cycle Genie?
Park Howell’s team used pretotyping principles to validate the Story Cycle Genie:
Skin in the game validation:
- Financial: 20 beta users invested $500 each
- Time: Users spent 1-2 hours using the genie
- Consultation: 1-2 hour Zoom sessions for feedback
- Reputation: Willingness to use it in their actual businesses
Value exchange: Added value during Zoom sessions by providing branding and story advice, ensuring beta users received more than just product testing opportunity
Market hypothesis evolution:
- Original hypothesis: Small-to-medium businesses would use it to replace agency expenses (primary market)
- Revealed market: Ad agencies and marketing consultants became the primary adopters
- Key insight: Agencies saw it as “wealth generation tool”—creates wealth of free time, improved margins, higher quality output
The pretotyping lesson: Even with proper pretotyping, the market will often tell you the real application differs from your original hypothesis. Contact with the market reveals the truth.
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