Key Takeaways

  • Most CEOs are shrinking teams with AI, believing it will drive efficiency and replace roles, seeing additional headcount as a drag on speed and product quality.
  • Glean founder Arind argues the opposite, planning for 10x team growth, asserting that effectively deployed human capital with AI creates products 10 times better than the competition.
  • The future workforce will increasingly feature "composite roles," where individuals blend multiple specializations (e.g., product, data, growth) rather than hyper-specializing.
  • Roles like data analysts focused solely on dashboard creation or sourcers doing routine discovery are likely to disappear as AI automates their core functions.

The Disagreement

It’s the question haunting every founder right now: does AI mean fewer people? On one side, Harry Stebbings hears a resounding yes. He points out that the CEOs he speaks with are actively cutting headcount, driven by a belief that AI is here to streamline and replace. “You I sit with the biggest CEOs in the world and every single one of them is shrinking teams and every single one of them is saying I absolutely don't believe in it,” Stebbings says. He pushes back on the idea of growth, adding, “But I don't think more people makes for better products. ... But I think that argument and I think more people slow down everything.” For many, more people equals more complexity, slower decisions, and ultimately, a worse product.

Then there’s Arind, founder of AI search startup Glean, who offers a starkly different vision. He’s planning for significant team expansion, not contraction. Arind believes the competitive advantage lies not in replacing people with AI, but in amplifying them. He argues that while your competition might use AI to cut costs, a truly ambitious company will use it to empower its people to build something far superior. “Your competition can also do the same but they chose actually not to do the same amount of work. they chose to actually, you know, elevate and build a 10x better product or build 10 times more,” Arind explains. His point: AI provides the leverage; humans still provide the ambition and the creative output to build at a higher order of magnitude.

Who's Right (and When They're Wrong)

Both Stebbings and Arind hold pieces of the truth, but they apply to different types of companies and ambitions. Harry's observation is correct for organizations focused on cost-cutting and optimizing existing processes. For these companies, AI will automate repetitive tasks, making leaner teams possible. If your goal is primarily efficiency gains and maintaining status quo, then shrinking your team is a logical play.

However, Arind's perspective is far more compelling for ambitious builders aiming for true product differentiation and market leadership. The core insight is that AI doesn't just replace; it enables. If you view AI as a tool to make your current team 10 times more productive, then the bottleneck shifts. The new challenge isn't automation, but having enough skilled humans to direct that immense new power towards building. This is where Arind introduces the concept of “composite roles.” He predicts, “Well, the comp com uh composite roles will be um will be very common.” These are not hyper-specialized roles, but rather individuals who can leverage AI to perform functions previously split across several specialists. Arind points out that many routine roles, particularly those lacking business thinking, are on the chopping block: “A lot of analyst roles like or like the the data analyst roles which are not business thinkers... I think like that that kind of work definitely goes away.” The goal isn't just to do the same work with fewer people, but to do radically more and better work with a slightly different—and often more potent—mix of human talent.

What to Do With This

Don't default to the "AI means fewer people" mindset if you're building to dominate. Instead, map your current team roles against Arind's "composite role" idea. Identify which hyper-specialized tasks (like creating basic dashboards, managing routine data queries, or simple sourcing) could be fully automated or absorbed by a more generalist role using AI tools. Then, brainstorm new, higher-leverage "composite roles" that blend multiple traditional functions—think a “Product Growth Engineer” who uses AI to handle data analysis, A/B testing, and even some content generation, freeing them to focus purely on strategic growth levers. Finally, consider piloting a small, AI-augmented team expansion. Find one crucial area where 10x output would be a game-changer and hire two people instead of one, equipping them with the best AI tools, to see if Arind's growth-for-better-products hypothesis holds true for your business."