I once watched a founder, a really sharp guy with a great track record, pour $10 million into an AI-powered “customer sentiment analysis” tool. He hired a team of PhDs, bought a mountain of GPUs, and spent a year building the most complex, technically impressive model you can imagine. The only problem? It didn’t work. Not in the real world, anyway. It could tell you if a customer was “happy” or “sad” with 98% accuracy in a lab, but when faced with the messy, sarcastic, emoji-filled reality of customer support tickets, it fell apart. The project was a total write-off. The founder was humbled, and the company’s AI ambitions were set back by years.
That story isn’t unique. I’ve seen it happen again and again. As an investor in over 200 companies, including some of the biggest names in AI like Anthropic and OpenAI, and having built and sold two of my own tech companies, I’ve had a front-row seat to the AI revolution. And I can tell you that the biggest reason most AI projects fail isn’t the technology. It’s the leadership.
There’s a fundamental misunderstanding at the executive level about what it takes to lead in the age of AI. They’re trying to apply the old playbook to a brand-new game. It’s like trying to win a Formula 1 race with a horse and buggy. It’s just not going to work.
The Illusion of Control
Founders and executives are used to being in control. They’re used to detailed roadmaps, predictable timelines, and clear deliverables. They want to know what they’re going to get, when they’re going to get it, and how much it’s going to cost. That’s how you build a traditional software product. But that’s not how you build a successful AI product.
AI development is not a linear process. It’s a messy, unpredictable, and often frustrating journey of discovery. You can’t just write a spec, hand it to a team of engineers, and expect them to deliver a working model six months later. It’s a process of experimentation, of trial and error, of going down dead ends and then, just when you’re about to give up, having a breakthrough.
I learned this the hard way with my first company, MovieLaLa. We were trying to build a recommendation engine for movies. We had a team of smart engineers, a ton of data, and what we thought was a solid plan. We spent months building a complex collaborative filtering model, the same kind of technology that Netflix was using. We were so confident that we were on the right track. But when we finally launched it, the recommendations were terrible. Our users hated it. We had to go back to the drawing board, and it was a painful, humbling experience.
What we eventually realized was that we had been too focused on the technology and not focused enough on the user. We were trying to build a perfect model in a vacuum, without any real-world feedback. We had to learn to embrace the uncertainty, to iterate quickly, and to listen to our users. It was a lesson that I’ve carried with me ever since.
Here's a related post on my journey as an angel investor.
The Myth of the All-Knowing AI Guru
Another huge mistake I see founders make is thinking they need to hire a “Chief AI Officer” who is some kind of all-knowing guru. They go looking for a unicorn, someone with a PhD from Stanford, 20 years of experience at Google Brain, and a long list of publications in top-tier journals. And when they can’t find that person, they either give up or they hire someone who looks good on paper but has no real-world experience.
Look, I get it. You want to have the best people on your team. But the truth is, the perfect AI leader probably doesn’t exist. And even if they did, you probably couldn’t afford them. The reality is that AI is still a new and rapidly evolving field. There are no established best practices, no proven playbooks. We’re all just figuring it out as we go along.
Instead of looking for a guru, you should be looking for a leader who is curious, adaptable, and not afraid to admit when they don’t know something. You need someone who is a quick learner, who can get up to speed on the latest research, but who is also humble enough to listen to their team and to learn from their mistakes. You need a leader who can build a culture of experimentation, where it’s safe to fail, and where the best ideas can win, no matter where they come from.
When we were building RemoteTeam, which was later acquired by Gusto, we didn’t have a Chief AI Officer. We didn’t have anyone with a fancy AI title. What we had was a team of smart, curious engineers who were passionate about solving problems for our customers. We gave them the autonomy to experiment, to try new things, and to learn from their failures. And you know what? They built an amazing product. They built a product that our customers loved, and that ultimately led to our acquisition.
Leading Through the Fog
So if you can’t rely on a detailed roadmap, and you can’t just hire a guru to solve all your problems, how do you lead in the age of AI? The answer is that you have to learn to lead through the fog. You have to be comfortable with uncertainty, and you have to be able to inspire your team to keep moving forward, even when you don’t know exactly where you’re going.
This is a huge mindset shift for most leaders. They’re used to having all the answers. They’re used to being the smartest person in the room. But in the age of AI, that’s no longer possible. The field is moving too fast, and the problems are too complex for any one person to have all the answers. The best you can do is to have a clear vision, to set a direction, and to empower your team to figure out the rest.
It’s about creating a framework for decision-making, not a rigid set of rules. It’s about asking the right questions, not having all the right answers. It’s about being a coach, not a commander.
I remember when we were trying to build an AI-powered onboarding flow for new employees at RemoteTeam. We had a vision for what we wanted to create, but we had no idea how to get there. We spent weeks trying different approaches, and we failed over and over again. The team was getting discouraged, and I was starting to doubt whether it was even possible. But we kept at it. We kept experimenting, we kept learning, and we kept moving forward. And eventually, we had a breakthrough. We found a solution that was simple, elegant, and that worked even better than we had imagined.
That experience taught me that leadership in the age of AI is not about having a perfect plan. It’s about having the resilience to keep going when things get tough, and the humility to learn from your mistakes. It’s about trusting your team, and giving them the space to do their best work.
For more on my investment philosophy, check out this post.
Your New Playbook for AI Leadership
So what does this all mean for you, the founder in the trenches? It means you need to throw out the old playbook and start writing a new one. Here are a few things you can do right now to become a more effective AI leader:
Embrace the unknown. Stop trying to plan everything out in minute detail. Instead, focus on creating a culture of experimentation where it’s safe to fail. Your goal is not to avoid mistakes, but to learn from them as quickly as possible.
Get your hands dirty. You don’t need to be a machine learning expert, but you do need to have a basic understanding of the technology. Take an online course, read a few books, or just spend some time talking to your engineers. The more you understand about how AI works, the better you’ll be able to lead your team.
Hire for curiosity, not for credentials. When you’re building an AI team, don’t just look for people with fancy degrees and impressive resumes. Look for people who are curious, adaptable, and passionate about learning. These are the people who will be able to thrive in the fast-changing world of AI.
Lead with vision, not with authority. In the age of AI, you can’t lead by telling people what to do. You have to lead by inspiring them with a clear and compelling vision for the future. You have to empower them to do their best work, and you have to trust them to figure out the details.
I’m not going to lie to you. This is not an easy path. It’s going to be messy, it’s going to be frustrating, and there will be times when you’ll want to give up. But if you can embrace the uncertainty, if you can learn to lead through the fog, and if you can build a team that is as passionate about the journey as they are about the destination, then you will not only survive, but you will thrive in the age of AI.
Building an AI-driven company is the hardest thing I’ve ever done. It’s also the most rewarding. There’s nothing quite like the feeling of creating something out of nothing, of solving a problem that no one has ever solved before, of building a team that is capable of doing things that you never thought were possible.
So, are you ready to throw out the old playbook? Are you ready to embrace the chaos? Are you ready to become the leader that the age of AI demands? I hope so. Because the future is not something that just happens to us. It’s something that we build. And I, for one, can’t wait to see what you build.
Frequently Asked Questions
What experience informs this perspective?
This perspective comes from over a decade of building companies in Silicon Valley, two successful exits (RemoteTeam to Gusto, MovieLaLa to Gfycat), and investing in 200+ startups including Anthropic, OpenAI, and Scale AI. I write about what I've lived.
What's the most common pushback you get on this?
People often push back by citing exceptions or edge cases. And they're usually right that exceptions exist. But building a strategy around exceptions rather than patterns is a losing game for most founders.
Do all experts agree with this view?
No, and that's fine. The best ideas in business are often contrarian. I share my perspective based on my experience and data, but I encourage you to seek out opposing viewpoints and form your own conclusions.