Everyone is Lying to You
After hosting a podcast for over three years, I thought I knew how to ask questions. I believed there were clever ways to phrase a question to get to the truth, like asking, “Are you multilingual at home?” instead of the direct “Where are you from?”. I was confident in my ability to get the information I needed. It turned out I still had so much to learn.
While building Engage AI, I heard about a book called “The Mom Test” by Rob Fitzpatrick. I decided to give it a try, not expecting much. I read it, and it immediately showed me how wrong I had been, especially with my first startup, 22 Laps, a digital marketplace for bicycles.
With 22 Laps, I had based the entire business on conversations I thought were validating the market. But as Rob Fitzpatrick points out, when you ask people if your idea is good, they tend to be nice. And because of that, everyone lied to me. I built my first startup on those well-intentioned lies, only to discover that nobody wanted the product, at least not in the way I thought I was solving their problem.
That experience taught me the crucial lesson that “The Mom Test” articulates perfectly: you must truly understand the user’s problem before you even think about scaling for growth. The book is full of practical advice, but these three ideas have stuck with me:
The Mom Test: Don’t ask if your business is a good idea.
This is the core principle. If you ask someone if your business idea is good, they will most likely lie to protect their image and your feelings. The book teaches you to ask questions about their life and the problems they already face, instead of pitching your solution. With Engage AI, I applied this by asking questions like: “How did you find out about us?”, “Why were you searching for a solution like this?”, and “What were you doing before you found Engage AI?”.
From those questions, I learned many of our users had hired virtual assistants (VAs) to help them with commenting on LinkedIn. This proved our theory: people want to engage, but they are time-poor, and consistent engagement is taxing. They also said that while their VAs spoke perfect English, they struggled to be insightful and often ended up leaving generic comments like, “Thank you for sharing,” or “great post.” This was a real, specific problem we could solve with Gen AI.
Avoid fluff and compliments.
People will often say things like, “That’s a great idea!” or “I would totally use that!”. The book warns that these are opinions, not commitments. You should be skeptical of compliments and steer the conversation back to the facts of their problems. So, every time someone told me Engage AI was a “great idea,” I would politely say thank you and then dig deeper.
For example, I asked some people why they weren’t paying for the premium version, despite their praise. By asking about how often they engage with prospects on LinkedIn, I learned they only do it once or twice a week. It turned out they were job seekers or used other channels like networking and cold email for customer acquisition. This helped me realize who our target niche was and where we should focus our energy.
Focus on facts, not hypotheticals.
What people have done in the past is a much stronger indicator of their future behavior than what they claim they would do. Instead of asking hypothetical questions like, “Would you pay for a service that did X?”, you should ask about their current and past actions. For instance, I asked users, “Who do you engage with on LinkedIn?”. I learned that most free users just engage with anyone they see on their newsfeed. Our paid users, on the other hand, had a Google Spreadsheet with hundreds of people they wanted to target. Their process was to manually click into the “All Activity” page of each profile to see if they had posted something new.
After interviewing so many users, this discovery led me to two powerful conclusions:
We needed to focus on power users who already had a list of target prospects.
We should build an agentic AI to monitor these prospects on their behalf and bring all their posts into a single, focused feed.
This insight was a game-changer. Instead of quickly expanding Engage AI to other channels like X, Reddit, and Facebook, we doubled down on LinkedIn and built our second core feature: prospect feed and monitoring. That focus allowed us to convert more free users to paid users, build a loyal customer base, and fend off hundreds of copycats. To my surprise, 98% of them still haven’t built this feature.
This experience taught me that while it’s critical to speak with your users, you have to do it in a way that gets you past the polite lies. It’s about using first principles to understand the ‘why’ behind their problems. If you want to build a product with high adoption, learning to ask the right questions is one of the most important skills you can develop. Get the book, apply these principles, and you’ll be on your way to building better products that genuinely serve your niche.