David SenraBuilding a $150 Billion Company With Just 400 People | Adam Foroughi of AppLovin
David Senra and Adam Foroughi on appLovin’s contrarian buybacks, Axon AI, and lean A-team scaling.
In this episode of David Senra, featuring David Senra and Adam Foroughi, Building a $150 Billion Company With Just 400 People | Adam Foroughi of AppLovin explores appLovin’s contrarian buybacks, Axon AI, and lean A-team scaling AppLovin’s stock fell ~92% in 2022 despite rising EBITDA, prompting a highly targeted ~$6B buyback program that ultimately created ~$50–$60B in value as the market repriced the business.
At a glance
WHAT IT’S REALLY ABOUT
AppLovin’s contrarian buybacks, Axon AI, and lean A-team scaling
- AppLovin’s stock fell ~92% in 2022 despite rising EBITDA, prompting a highly targeted ~$6B buyback program that ultimately created ~$50–$60B in value as the market repriced the business.
- After being rejected by top VCs in 2012, AppLovin bootstrapped to product-market fit by turning an “app discovery” recommendation insight into an SDK-based mobile ad network optimized for developers, not brand advertisers.
- A board-less early history enabled fast, founder-led decisions but also led to a near-disastrous China-linked transaction that was later salvaged via a pivot to a non-control convertible note and then refinanced with KKR.
- To compete with data-rich platforms, AppLovin temporarily bought multiple gaming studios to obtain advertiser-like purchase data needed to train machine-learning models, later selling the studios once the core ad platform became dominant.
- The company’s operating system is “hyper-competence with minimal process”: ruthless headcount discipline, CEO-approved hires, heavy pruning of non-A players, and leveraging LLMs so small teams can outperform much larger orgs.
IDEAS WORTH REMEMBERING
5 ideasBuybacks can be transformational when fundamentals and price diverge dramatically.
Foroughi argues the 2022 selloff created an unusually “juicy” valuation (low multiple on cashflow/EBITDA), so AppLovin leaned in—using both operating cash and leverage—to retire shares at distressed prices and compound the upside when sentiment reversed.
Don’t do “generic” buybacks—source liquidity from the sellers you can predict.
Instead of only buying in the open market, AppLovin negotiated repurchases directly with large holders (private equity and departed founders) it expected to sell over time, improving execution certainty and reducing the risk of buying from the “wrong” counterparties.
Being board-less increases speed, but raises the cost of capital-market ignorance.
The lack of a board helped him avoid pressure to sell early, but it also contributed to a major misstep: underestimating geopolitical/regulatory risk (CFIUS scrutiny) in a China-linked control transaction.
Regulatory and geopolitics can dominate deal logic—even if the business feels innocuous.
AppLovin thought it was “solitaire and poker data,” but regulators evaluated it as a large-scale data platform on mobile devices; the control element and state-linked capital made approval unlikely regardless of valuation appeal.
Data is the unlock for performance advertising; acquiring it can justify temporary vertical integration.
To build stronger machine-learning models (and compete with Facebook/Google’s data advantage), AppLovin bought gaming studios to access purchase/monetization data, trained Axon models, and later exited the studios once the platform no longer needed that crutch.
WORDS WORTH SAVING
5 quotesSo you're running a business, and the whole world is telling you your business is trash. Like like what, what do you do?
— Adam Foroughi
But then two, to lever up to buy your own shares when everyone's telling you your, your company is a piece of shit, that's really scary to do.
— Adam Foroughi
I never believed in saving cash for a rainy day.
— Adam Foroughi
We ended up deploying somewhere around $6 billion of buybacks of our own capital, and we leveraged some to buy back shares in the company. And over time, that ended up creating somewhere in the neighborhood of $50, $60 billion of actual proceeds from the buyback, one of the more successful buybacks in the history of companies.
— Adam Foroughi
I'd wake up every morning and go, "I gotta check stats. Are we going bankrupt today, or are we still doing well?"
— Adam Foroughi
QUESTIONS ANSWERED IN THIS EPISODE
5 questionsOn the buyback: what exact decision rules (valuation/cashflow/leverage limits) told you to “hit it as hard as you could,” and what would have made you stop?
AppLovin’s stock fell ~92% in 2022 despite rising EBITDA, prompting a highly targeted ~$6B buyback program that ultimately created ~$50–$60B in value as the market repriced the business.
You said you avoided open-market buybacks by dealing directly with likely sellers—how did you structure timing/pricing so you weren’t overpaying as the stock rebounded?
After being rejected by top VCs in 2012, AppLovin bootstrapped to product-market fit by turning an “app discovery” recommendation insight into an SDK-based mobile ad network optimized for developers, not brand advertisers.
What were the earliest “developer-first” tools or product decisions that most clearly differentiated AppLovin from AdMob’s brand-oriented approach?
A board-less early history enabled fast, founder-led decisions but also led to a near-disastrous China-linked transaction that was later salvaged via a pivot to a non-control convertible note and then refinanced with KKR.
Looking back, what due diligence questions would a strong board have forced you to answer before signing the China control deal (especially around state-owned capital and CFIUS)?
To compete with data-rich platforms, AppLovin temporarily bought multiple gaming studios to obtain advertiser-like purchase data needed to train machine-learning models, later selling the studios once the core ad platform became dominant.
When you bought game studios for data, how did you technically and organizationally separate “platform fairness” from “first-party advantage” to reduce developer paranoia?
The company’s operating system is “hyper-competence with minimal process”: ruthless headcount discipline, CEO-approved hires, heavy pruning of non-A players, and leveraging LLMs so small teams can outperform much larger orgs.
Chapter Breakdown
AppLovin’s stock collapse and the contrarian $6B buyback
Foroughi explains how AppLovin’s market cap fell from ~$40B to ~$3.8B despite rising EBITDA, creating an extreme disconnect between fundamentals and price. He describes choosing offense over defense: aggressively repurchasing stock when the public market narrative turned negative.
Borrowing to repurchase shares—why leverage made sense
Senra presses on the risk of borrowing money to buy back stock in a company the market had “written off.” Foroughi argues he doesn’t hoard cash and believes high cash generation plus a deeply discounted valuation justified leverage.
Why top VCs passed in 2012 and why he bootstrapped anyway
Foroughi recounts being rejected by major VCs in 2012 despite prior ad-business success. He explains the skepticism about competing with Google/Facebook and why he preferred to bootstrap while pivoting until product-market fit was clear.
Failed consumer apps → the pivot from app discovery to an ad network
Attempting direct-to-consumer apps (dating and fashion) flopped, but a third experiment—an app recommendation product—revealed a powerful distribution mechanism. AppLovin’s breakthrough was packaging that recommendation capability as an SDK-based ad platform inside other apps.
Beating Google’s AdMob with performance marketing for developers
AppLovin outcompeted AdMob by focusing on developer outcomes instead of brand advertising. Foroughi explains building a performance-based system that let developers both monetize and acquire users with measurable ROI, avoiding the agency/brand sales model.
No board for six years: speed, control, and capital-market blind spots
Foroughi describes operating without a formal board until 2018, which gave him unilateral decision-making power but also increased risk in complex financing and dealmaking. He shares how hyper-growth and acquisition interest tested his judgment and team dynamics.
The China deal that nearly derailed the company (CFIUS and geopolitics)
A proposed China-based investment intended to take AppLovin public in China triggered national security scrutiny. Foroughi details walking into CFIUS unprepared, learning about state-owned capital concerns, and facing a long, uncertain regulatory gauntlet.
Convertible-note pivot and KKR: cleaning up the cap table and forming a board
To salvage the situation and protect the company, the deal was restructured into a convertible note that limited Chinese ownership and control. That created a new problem—large convertible debt—solved by bringing in KKR, which also led to AppLovin’s first formal board.
Buying gaming studios to get data and build Axon (ML upgrade)
To compete with Facebook-level targeting, AppLovin needed richer advertiser data to train more powerful models. Since advertisers wouldn’t share data, the company bought gaming studios to gain first-party purchase/monetization data and to understand developer needs, enabling the Axon model evolution.
Trust breakdown with developers—and the communication fix
Owning studios made AppLovin look like a vertically integrated competitor, which threatened trust with developer customers. Foroughi explains how unclear communication fueled suspicion, and how direct conversations and transparency restored partnerships as performance proved out.
Exiting the studios: refocusing on the high-margin core platform
Once the ad platform had sufficient external data and traction, studios became a distraction and headcount burden. AppLovin sold the studio portfolio to Tripledot, prioritizing simplicity and strategic focus over piecemeal optimization.
The 2022 crash: retaining key talent, resetting incentives, and cutting bloat
When the stock fell ~92%, Foroughi changed equity strategy and organizational design to protect the people most critical to product outcomes. He shifted many roles to cash compensation, narrowed equity participation to key contributors, and executed large workforce reductions even as revenue surged.
Building a hyper-competent, ultra-lean company (and why Adam approves every hire)
Foroughi describes how AppLovin’s operating philosophy favors minimal process, few executives, and high-ownership builders. A key inflection came from new technical leadership challenging every role and process, leading to systematic pruning and a rule that new hires require CEO approval to stop automatic “backfills.”
Axon 2 inflection: deep learning turns advertisers into ‘arbitragers’
Foroughi explains the performance-marketing north star: advertisers must reliably earn more than they spend, making scaling automatic. Axon 2 (deep learning) dramatically reduced manual setup and improved prediction quality, driving rapid revenue and market-cap expansion from 2023 onward.
One great engineer beats a hundred: AI leverage and expansion beyond gaming
AI tools magnify the output of top talent, reinforcing AppLovin’s bias toward small teams of exceptional engineers. Foroughi describes LLM-driven productivity, the move from gaming ads to e-commerce ads, and the ambition to become a broad performance marketing platform for SMBs and eventually enterprises.
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