This article summarizes an episode of 20VC’s video series featuring Adam Foroughi, co-founder and CEO of AppLovin.
Adam Foroughi, co-founder and CEO of AppLovin/ Photo credit: Adam Forough
Most companies hire aggressively during periods of high revenue growth. Adam Foroughi, co-founder and CEO of AppLovin, does the exact opposite, using layoffs to push AI adoption and increase overall output.
Company delays blocking the move to AI
Business leaders often treat AI simply as a software upgrade. They soon discover that the speed of work stays the same because the company rules refuse to change.
Foroughi believes people, not the technology, are the real roadblock. Layoffs are the spark needed to clear out slow groups.
He notes, “We grew near triple digits, but we ended up cutting the team’s staff by 40% to 50%… If a role could be automated or AI adoption was too slow, it was time to rebuild around today’s technology.”
This rebuilding process explicitly targets middle management and those who manage company rules rather than actual output.
“Companies get bloated,” Foroughi argues. “I went through and said: What are the processes I don’t like at the company? Let me eliminate those. Then we can go through and say: Who are the gatekeepers of those processes? You can remove those people.”
The danger of tracking bad technology numbers
While removing these gatekeepers speeds up the company, it creates a new risk for management. Leaders desperate to show progress often start tracking the wrong numbers, which encourages bad choices.
One of the worst choices is paying programmers simply to write large amounts of AI assisted code, which destroys product quality.
“If you’re incentivizing slop, you’re not going to get very far as a business,” Foroughi warns. “You’re going to have massive fees to go pay the large language model businesses, but you’re not going to get further as a business.”
Beyond bad code, budgets must connect AI spending directly to sales. Without tracking how usage turns into money, leaders simply pay for useless work.
The problem with average workers
The mental cost of working hard
Tying big pay to company turnarounds
The risk of misunderstood finances
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