IC CEOs Drive Non-Incremental Outcomes

Howie Liu advocates for a return to founder-level engagement with product details, especially in the AI era. He believes that as companies scale, CEOs often drift away from the details that made their products magical in the first place, delegating to specialized teams that optimize incrementally within their domains rather than holistically.

This "IC CEO" approach isn't about micromanaging but about maintaining intimate knowledge of the product experience. As Howie explains, "The times where I felt most disintermediated from what I felt was the substance of this company was when I thought I was almost forcing myself to step away from the details because I thought that's what an at-scale CEO was supposed to do."

For leaders, this means carving out significant time to experiment with your product and adjacent technologies. Howie personally spends hours using AI tools, intentionally becoming Airtable's highest consumer of inference costs. He believes this hands-on approach provides strategic insights no consulting firm could match at any price.

For individual contributors, this leadership style creates opportunities to work more autonomously and cross-functionally. Howie restructured Airtable into "fast thinking" and "slow thinking" teams, with the fast-moving AI platform group shipping capabilities weekly. He encourages team members to cancel meetings for days or even weeks to experiment with AI tools, valuing this exploration over rigid roadmaps.

The most successful team members in this environment are those who can transcend traditional role boundaries. As Howie puts it, "If you're any one of those roles [PM, engineering, design], you need to be minimally good at the other two and then you can go deeper into your own specialty." This polymathic approach allows teams to move with the speed required in the AI era, where capabilities evolve rapidly and product form factors must evolve with them.

Rather than optimizing for efficiency through specialization, Howie optimizes for innovation through integration—bringing together perspectives that would typically be siloed. This approach creates more engaging work for everyone while enabling the company to make bolder, more cohesive product bets.

Practical Implications

When evaluating AI opportunities, Howie recommends asking: "If you were literally founding a new company from scratch with the same mission, how would you execute on that mission using a fully AI-native approach?" This forces you to consider whether your existing assets truly provide an advantage or if you're constrained by legacy thinking.

For product development, he suggests starting with "vibes" rather than formal evaluations. Instead of defining metrics upfront for novel AI features, experiment broadly first to understand what's possible, then formalize testing once you've identified promising directions.

The most valuable skill in this environment is the ability to create working prototypes rather than documents. As Howie notes, "I wanna see actual interactive demos because... it's hard to get that feel of the product with anything but a functional prototype."