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.
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Beyond vision and roadmaps, a CPO’s fundamental role is to act as a steward of the company's R&D investment. The primary measure of success is the ability to ensure that every dollar spent on development translates into tangible, measurable enterprise value for the business.
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 traditional product management skillset is no longer sufficient for executive leadership. Aspiring CPOs must develop deep expertise in either the commercial aspects of the business (GTM, revenue) or the technical underpinnings of the product to provide differentiated value at the C-suite level.
Unlike a functional manager who can develop junior talent, a CEO lacks the domain expertise to coach their entire executive team (e.g., CFO, VP of HR). A CEO's time is better spent hiring world-class leaders who provide 'managerial leverage' by bringing new ideas and driving their function forward, rather than trying to fix people in roles they've never done.
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.
At the VP or C-level, a leader's primary role shifts from managing their function to driving overall business success. Their focus becomes more external—customers, market, revenue—and their success is measured by their end-to-end impact on the company, not just their team's performance.
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.
The pivot from a pure technology role (like CTO) to product leadership is driven by a passion shift. It's moving from being obsessed with technical optimization (e.g., reducing server costs) to being obsessed with customer problems. The reward becomes seeing a customer's delight in a solved problem, which fuels a desire to focus entirely on that part of the business.