Make Every Function Full-Stack

Howie Liu believes that in the AI era, the most successful companies will collapse traditional role boundaries, requiring everyone to develop broader capabilities beyond their core specialization.

At Airtable, Liu has observed that the most effective team members are those who can cross over into adjacent disciplines. Rather than having siloed specialists, he encourages a "polymathism" where people develop minimum competency across multiple domains while maintaining depth in their primary area. This approach creates more autonomous, versatile contributors who can drive outcomes without excessive dependencies.

Liu sees this as particularly crucial for product teams, where the traditional PM-Engineer-Designer triangle is evolving. As he puts it, "As a PM you need to start looking more like a hybrid PM-prototyper who has some good design sensibilities." Engineers benefit from understanding product requirements and user needs, while designers need technical awareness to create feasible solutions.

This philosophy extends beyond product teams. In marketing, Liu encourages individuals to handle entire campaigns rather than splitting responsibilities across targeting, copy, and creative. In sales, account executives are expected to develop solution engineer capabilities, becoming fluent enough with the product to run compelling demos themselves.

The practical implication is that career development now requires intentional expansion into adjacent domains. Individual contributors should identify which complementary skills would make them more effective and invest time in developing those capabilities. For managers, this means creating learning opportunities that cross traditional boundaries and evaluating team members not just on their core specialty but on their ability to drive outcomes independently.

Liu frames this not as a threat but as an opportunity: "Everyone can learn how to be a versatile unicorn product-engineer-designer hybrid in the AI native era, and the only thing stopping you is just going out and doing it." With AI tools making learning more accessible than ever, the barriers to developing these cross-functional capabilities are lower than they've ever been.

Practical Implications

For leaders, this means rethinking how teams are structured and how work is allocated. Rather than optimizing for specialization, consider organizing around outcomes that require cross-functional capabilities. Evaluate whether your current team structure creates unnecessary handoffs that slow execution.

For individual contributors, this suggests investing time in adjacent skills even if they seem outside your job description. If you're a designer, learn enough about technical constraints to propose feasible solutions. If you're an engineer, develop product thinking to better understand the "why" behind requirements.

The most valuable team members in this new world won't be the deepest specialists, but those who can independently drive outcomes by drawing on a broader set of capabilities. As Liu puts it, "The ideal person may be very specialized and deep in one dimension like engineering, but they're well-rounded enough to be dangerous on the other two."