Jun 8, 2025 · 20m · top-founders
18 Year Old Got Paid $2.9m Last Month for New AI Mobile App
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gold bands on the timeline = statements, start to end. Hover to read, click to jump. CC turns on captions
In this interview, host Nathan sits down with 18-year-old Cal AI co-founder Zach Yadegari to break down how the viral calorie-tracking app scaled past $10 million in revenue through rapid product experimentation, behavioral onboarding design, and an extensive influencer acquisition network.
How this conversation actually went
Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Nathan holds 42.8% of the talking time here. How this is scored →
Nathan as informed peer 5.3 Guest teaching 4.1 Guest disagreement 1.1 Nathan pushing back 1.7
speaking balance: gold is Nathan, purple is the guest (3 minute bins)
Sharpest disagreement ▶ 16:09 Pushing back on commission-only creator compensation
Zach directly rejects Nathan's suggestion to use commission-based pay, stating that in reality competitive market forces force brands to offer guaranteed cash.
Hardest push from Nathan ▶ 3:00 Demanding clarity on collected revenue vs run rateNathan interrupts Zach's forward projection of 35 million to pin him down on actual cash collected year-to-date.
Biggest teaching moment ▶ 7:19 Explaining the sunk cost dynamic in onboarding lengthZach details how adding irrelevant questions increased conversion because user time investment generated psychological commitment to finishing the onboarding.
Nathan holds their own ▶ 10:01 Deconstructing the post-trial checkout discount flowNathan walks through the app step-by-step, highlighting how Cal AI introduces urgency discounts right after offering a free trial.
the scores for every segment, with the reasoning behind each
| Chapter | Topic | Nathan as informed peer | Guest teaching | Guest disagreement | Nathan pushing back | Why |
|---|---|---|---|---|---|---|
| Preview of Cal AI's Rapid Growth and Metrics | 6 | 3 | 1 | 2 | Nathan drills into the unit economics, growth metrics, and launch history of Cal AI, pulling up background research. Zach clarifies the timeline and updates the revenue estimates smoothly without any friction. | |
| App Store Optimization and Strategic Focus | 5 | 4 | 1 | 2 | Nathan asks about ASO keyword tools, but Zach explains they operate purely on intuition rather than sophisticated software like Appfigures. Zach also explains why they abandoned their holding company strategy to focus exclusively on Cal AI. | |
| Scaling the Team via Social Media Recruiting | 5 | 5 | 1 | 1 | Nathan explores the viral recruiting playbook and asks detailed questions about onboarding screen tests. Zach explains the non-intuitive user psychology discovery that adding questions with no functional impact increased funnel conversion. | |
| Paywall Engineering, Superwall, and Friction Reduction | 6 | 4 | 1 | 2 | Nathan shares his screen to praise and break down the paywall sequence and discount upsell. Zach details their heavy testing cadence on Superwall and moving user sign-ups to the very end of onboarding to minimize drop-off. | |
| Balancing University and Viral Media Narrative | 4 | 3 | 1 | 1 | Nathan prompts Zach on translating social virality into mainstream broadcast media appearances. Zach explains how viral tweets on his college admissions snowballed into FOMO-driven TV network bookings. | |
| Influencer Marketing Infrastructure and Economics | 6 | 6 | 2 | 3 | Nathan asks why they do not use performance-based affiliate commissions rather than guaranteed flat retainers. Zach schools him on the creator market reality where top creators demand guaranteed pay due to intense brand competition. | |
| Execution Speed, Account Vulnerabilities, and Specialized Roles | 5 | 4 | 1 | 1 | Zach discusses being banned on Instagram due to malicious impersonator attacks and outlines their organizational philosophy of hiring hyperspecialized single-metric owners. Nathan closes out by summarizing key metrics. |
Statements from this episode (20)
Cal AI relies on third-party models rather than training its own
“We did not train our own model to do this.”
Cal AI reached $1 million in sales within five months
“Yeah, that was like five months into the company.”
Cal AI ignores ASO tools, relying on intuition for keyword strategy
“So tools, we actually don't use any tools. I know app figures is a very popular one, but we mainly use, it was mainly off of the dome, actually.”
Cal AI abandoned a multi-app strategy to focus on its core product
“And so we, the plan was to apply that same thing to other apps, but Cal AI just kept growing faster and faster. And so by the time we had finished development on those other ideas we had, we realized it didn't make sense to spend any time there. Just given Kal…”
Cal AI has generated over $10 million in revenue this year
“So I was backtracking on the revenue, revenue calculations, probably closer to like a little over 10 right now.”
Cal AI recruits the majority of its talent directly from X
“I'd say most of our talent came straight from X.”
Adding non-essential onboarding questions boosted Cal AI's user conversion rate
“Initially, we had no animations, we had no GIFs, it was,
Very bland.
We only asked the questions we needed in order to give the user their calorie daily intake estimate that they would need to gain weight or lose weight, and
That was, it was purely utility, bu…”
Adding reassurance screens to the onboarding flow boosted Cal AI's conversion rate
“And then we add the idea to, okay, let's add a screen that says, thank you for trusting us.
Let's add a screen that says, you're going to lose weight faster with Cal AI.
And that was cool.
That increased the conversion rate.
So how do we take this one step fur…”
Cal AI receives between 20,000 and 30,000 new downloads daily
“Every day we get 20 to 30,000 new downloads.”
Over 20% of new Cal AI downloads convert to trial or paid
“20 to 25 will convert either to paying right away or into a trial.”
Moving the sign-in screen to the end of onboarding reduced drop-off
“Definitely moving the sign-in screens to the end because there is a lot of drop-off there, that was the biggest by far.”
Yadegari's college admissions tweet received 28 million views
“It got twenty eight million views, and then if you scroll down the personal statement, got forty million views by itself, and so that garnered so much attention, and we actually had a few stations reaching out”
Cal AI retains about 250 influencers to post monthly content
“We have about 250 influencers right now on retainer that are just posting, integrating us into their content monthly.”
Cal AI pays top influencers tens of thousands monthly for four posts
“Per month, the largest, it's in the tens of thousands per month, and the expectation is four posts.”
Half of Cal AI's 17-person team exclusively manages influencer marketing
“17 people, about half of those are just on the marketing side right now working with these influencers.”
Pure commission deals fail because brands offer creators guaranteed fees
“That would be the dream, but the reality is that there's too much competition out here with the brands, and they want to be guaranteed a payment, and if we're not gonna do it, another brand will.”
Cal AI prioritizes hiring hyper-specialized talent dedicated to single product areas
“That is the number one priority right now is hiring, but not just hiring anyone, specialized talent. So my goal right now for the company is let's bring someone on whose only job is just paywall experiments all day. He's just thinking about how can I increase …”