Simply hiring superstar "Galacticos" is an ineffective team-building strategy. A successful AI team requires a deliberate mix of three archetypes: visionaries who set direction, rigorous executors who ship product, and social "glue" who maintain team cohesion and morale.

Leaders often feel they must have all the answers, which stifles team contribution. A better approach is to hire domain experts smarter than you, actively listen to their ideas, and empower them. This creates a culture where everyone learns and the entire company's performance rises.

To be truly successful, a product leader cannot just focus on features and users. They must operate as the head of their product's business, with a deep understanding of P&Ls, revenue drivers, and capital allocation. Without this business acumen, they risk fundamentally undercutting their product's potential impact and success.

The best leaders don't just stay high-level. They retain the ability to dive deep into technical details to solve critical problems. As shown by Apple's SVP of Software, this hands-on capability builds respect and leads to better outcomes, challenging the 'empower and get out of the way' mantra.

To get product management buy-in for technical initiatives like refactoring or scaling, engineering leadership is responsible for translating the work into clear business or customer value. Instead of just stating the technical need, explain how it enables faster feature development or access to a larger customer base.

When hiring for the C-suite, the importance of domain expertise varies by role. For Chief Product Officers, a deep passion and knowledge of the problem space is critical for setting vision. For engineering leaders (CTOs/VPs), specific domain experience is less important than relevant tech stack knowledge and transformation skills.

AI tools reduce the communication overhead and lengthy handoffs that traditionally separated product and engineering. By streamlining the path from idea to code, AI makes the combined Chief Product and Technology Officer (CPTO) role more viable, enabling a single leader to manage both functions effectively.

Companies mistakenly try to hire one person for both applying AI in products and building the underlying AI infrastructure. These are two distinct roles requiring different skill sets. A VP of Engineering leverages existing AI for efficiency, while a Head of AI builds the core platforms for the company.

Better products are a byproduct of a better team environment. A leader's primary job is not to work on the product, but to cultivate the people and the system they work in—improving their thinking, decision-making, and collaboration.