AppLovin's CEO instilled a core engineering belief: technology moves fast, so be humble and willing to throw away what you've built to re-architect on current, cutting-edge platforms. This mindset enabled the creation of their new, more powerful Axon 2 model.
AppLovin's CTO initially tried to set up weekly one-on-ones, but they were quickly canceled. The engineering culture, driven by a "doer" mindset, prioritized direct communication via code, finding it more efficient than traditional management processes even at scale.
AppLovin's CTO found junior engineers were disconnected from business, receiving only low-level tasks. By showing them how their work directly impacted business outcomes, he unlocked their ability to contribute ideas and solve problems more effectively, improving the entire team's output.
AppLovin skips traditional, lengthy training manuals. New hires, from interns to senior engineers, push code to production within their first week. This provides an immediate, real-world feedback loop and a sense of impact, which accelerates learning and retention.
AppLovin's culture empowers engineers to solve business problems directly, often without a product spec. A new data flow engine for their e-commerce ads was designed on a napkin by engineers at breakfast, highlighting a philosophy where engineers are competent enough to ideate and build products autonomously.
New CTO Gio planned a month-long vacation but was convinced to work one week first. That week was so immersive it inspired him to code through his entire trip, building the foundational infrastructure for the company's transformative Axon 2 model, highlighting a culture of extreme ownership.
AppLovin's CTO doesn't see AI as a collaborator but as a foundation. The engineer's role is to sit "on top of" AI, focusing on higher-level problems like long-horizon planning that AI can't yet handle. As AI's capabilities grow, the engineer's role is continuously elevated.
Facing a 92% stock price collapse, AppLovin leveraged its strong cash flow to become its own best investor. They paused investor relations and deployed every available dollar to buy back shares, confident that their internal technology rebuild (Axon 2) would fuel a massive recovery.
With AI commoditizing the ability to build, the key differentiator is "taste"—the ability to discern what problems are worth solving and what ideas are wasteful. Building faster with AI is useless if you're building the wrong things. True success comes from what you decide *not* to do.
The CEO intentionally built a performance-based system where advertisers only pay for results. This model eliminates the need for a large sales force because the platform's value is self-evident. It enables small, unheard-of businesses to scale into companies with very large P&Ls purely based on ROI.
Beyond raw intelligence, AppLovin seeks candidates with low ego, as this trait enables them to listen, take feedback, and question themselves—all crucial for growth. The third, equally important criterion is how they respond to adversity, as resilience is a key predictor of success in a challenging environment.
While AppLovin's business scaled massively, its engineering team size stayed at ~100 people. This counterintuitive feat was achieved because the rise of AI coincided with the increasing complexity of their work. AI elevated each engineer's productivity, allowing the same team to solve much more challenging problems.