The top 1% of engineers at FAANG companies (Google, Meta, Tesla, etc.) reject conventional careers, dive into failure and the unknown, and create genuine innovation in their own way. What they have in common is not "always finding the right answer" but rather "being wrong in meaningful ways." They use failure as fuel for learning, willingly expose their limitations, and fearlessly pursue bold, long-term endeavors — and this attitude is what truly sets them apart.

1. The Birth of GANs: A Late-Night Challenge That Made the Impossible Possible

One night in 2014, Ian Goodfellow was drinking beer with friends at a bar in Montreal. His friends were debating a seemingly impossible problem — getting computers to generate realistic images on their own — and each proposed their own solutions. But Goodfellow thought they were going in entirely the wrong direction.

"Instead of that... we need a completely different approach."

Rather than arguing, he went home and spent the entire night coding a completely new method. Before morning, he had created GANs (Generative Adversarial Networks). One of the most important innovations in AI history began in that moment.

2. The Power of 'Being Wrong Carefully': A Common Trait of the Top 1%

The friends who debated with Goodfellow were by no means unintelligent. They were conventional, smart engineers. But "being spectacularly wrong from an entirely new angle" proved far more valuable than small, correct incremental progress.

This pattern appears repeatedly among FAANG's top 1% engineers. After deeply analyzing their career trajectories, these individuals are frequently and boldly wrong, but they prove that:

"Being wrong in the right way is far more rewarding than accumulating small correct answers."

3. The Courage to Teach and Grow: The Karpathy Example

Andrej Karpathy chose not to keep his deep learning knowledge to himself. Instead, he created Stanford's first deep learning course, teaching 750 students, and now educates millions about AI on YouTube.

"Teaching is terrifying for smart people. You have to say 'I don't know' in front of others, and simplifying ideas makes it easy to make mistakes."

Many engineers try to avoid this vulnerability, but the best engineers actually welcome it. Through teaching, they discover gaps in their own understanding and examine their blind spots through students' questions.

"Teaching helps not only others but also corrects my own misconceptions."

4. Boundary-Breaking Careers and 'Idea Arbitrage'

Ilya Sutskever moved from academia to Google to co-founding OpenAI to developing ChatGPT to a new company (SSI). Karpathy also accumulated diverse experience moving between Stanford, OpenAI, and Tesla. Goodfellow likewise has a career characterized by constantly crossing between fields and organizations — Google, OpenAI, Apple, DeepMind, and more.

Typically, such frequent job changes are seen as unstable. But these individuals collected different perspectives and insights by moving between worlds (academia, industry, large corporations, startups).

"Every field has invisible blind spots. What's obvious in one world becomes innovation in another."

These talents became bridges connecting islands of knowledge, developing broader and deeper capabilities than the "single-domain mastery" most people pursue.

5. Risk-Taking Attitude: Reputation, Career, and Bold Challenges

When Sutskever left Google to co-found OpenAI, most people raised doubts:

"General artificial intelligence is decades away. Is it even possible?"

In the 1990s, when LeCun pushed forward with Convolutional Neural Networks (CNNs), the AI community had turned its back on neural nets. This was more than a simple career move — it was a reputational risk.

"Truly innovative ideas always look wrong even to smart people. If they were clearly right, someone would have already built them."

World-changing ideas hide among apparent failures, and success can only be judged in hindsight. The best engineers don't fear being wrong. They see it as the "tuition fee for discovering the truth."

6. Long-Term Thinking and the Power to Stay Ahead

Sutskever doesn't stop at just developing AI:

"He's planning disaster-preparedness bunkers for his research team, preparing for a world where AI becomes more powerful than humans."

This reflects an extremely long-term perspective.

LeCun similarly:

"There are fundamental limitations in current approaches, so entirely new architectures are needed."

He dedicates himself to work that appears useless right now.

This decade-spanning perspective doesn't help much with short-term competitiveness. Realistically, most people can't do this because there are no immediate rewards. But the engineers who invest over long periods ultimately create the future, while everyone else adapts to the world they've built.

7. The 1%'s Path Is the Opposite of Conventional Advice

Remarkably, the success traits of these engineers —

• Teaching publicly
• Frequently moving across fields
• Betting on seemingly crazy ideas
• Maintaining unrealistically long-term perspectives

— are all the opposite of most career advice (focus on one thing, minimize risk, build your brand as a specialist, etc.).

"The top 1% don't just want to be good engineers. They want to be 'the person who was right about the future.' And the best way to be right about the future is to be willing to be wrong, here and there, right now."

Conclusion

In a word, this article says that behind every breakthrough lies the courage to endure repeated mistakes and vulnerability. Experience gained from being wrong, boundary-crossing moves, long-term perspective, and self-expansion through teaching — these four things are the true competitive edge of FAANG's top 1% engineers. When we all become more tolerant of challenges and mistakes, the path to innovation draws closer.