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AI makes the product management job harder, not easier — the challenge shifts from execution to deciding what not to build, as rapid engineering velocity creates pressure to expand surface area chaotically while the real job is fighting to simplify and find the most scalable workflows.

Oswald explains that AI's acceleration of engineering output makes product management more difficult. The bottleneck moves from building features to understanding user needs and exercising judgment about what not to build, as the product team constantly fights against expanding surface area. ✦ AI generated

Oswald Nitski · 20VC · 2026-07-25 · original ↗

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starts at this moment · 12:35

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“Do we just build 10x more products quicker? Do we have smaller product teams? How do you think about that?”

This paradigm makes the job of product management a lot harder because we're trying not to build 10x more product surface area. It makes things incredibly chaotic. We have moments in time where product surface area rapidly expands because people think, 'Oh, I can make all these features really quickly. This is like I could you know, like let me just like push these multi-thousand line PRs.' But we are constantly in this battle to try to simplify our product surface area and find the interactions and the workflows that are most scalable. So, the trend that we see is we're as a product team constantly fighting to reduce surface area and simplify things. And we also see a higher ratio of PMs to eng because engineering is less bottlenecked. There's much, much more work to be done in understanding the workflows of users, the needs of users, and what products actually drive revenue the most becomes the bottleneck now to servicing more demand for us.

verbatim transcript · starts at 12:35

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12:39chaotic. We have moments in time where product surface area uh rapidly expands because people think, "Oh, I can make all these features really quickly. This is like I could you know, like let me just like push these multi-thousand line PRs." Um but we have uh we're constantly in this battle to try to simplify our product surface area and find the interactions and the workflows that are most scalable.

13:02So, the trend that we see is we're uh as a as a product team constantly fighting to reduce surface area and simplify things. Um and we also see a uh higher ratio of PMs to eng uh because engineering is less bottlenecked. So, there's much, much more work to be done in uh like understanding the uh workflows of users, the needs of users, and what products actually drive

13:31revenue the most becomes the bottleneck now to uh servicing more demand for us. >> If we think about the kind of pre-AI era, how has what it takes to be a great PM changed for this new world? >> There's two major changes. One is that don't really need to learn as many like tools anymore, you know? You just have to be able to use uh coding agents like

13:52a couple tools will do everything you need, you know? Um I don't I like even even Figma is uh we're moving away from it in favor of cloud design more and more. Um so more uh you know, less less tool diversity for us. Uh and then the other is everyone needs to up-level a lot and think about business impact much more. I think that all work is starting to look like higher

◉ Oswald Nitski
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