What exactly AI is doing for people, function by function Results from a large-scale AI productivity survey of my 1m+ newsletter subscribers (with @noamseg) 1. PMs are seeing the most value from AI tools to (1) write PRDs, (2) create mockups/prototypes, and (3) improve their communication across emails and presentations. Not so much to help them come up with roadmap ideas, run meetings, GTM, or user research synthesis. AI is helping PMs produce, but so far it lags in helping them think.

2. Designers are finding AI most helpful with user research synthesis, content and copy , and design concepts ideation. Visual design ranks #8. AI is helping designers with everything around design (research synthesis, copy, ideation), but pushing pixels remains stubbornly human. Meanwhile, compare prototyping: PMs have it at #2 (19.8%), while designers have it at #4 (13.2%). AI is unlocking skills for PMs outside of their core work (at least in the case of prototyping), whereas designers aren’t seeing the marginal improvement benefits from AI doing their core work.

3. Founders lean heavily toward productivity and decision support, product ideation, and vision/strategy. Unlike others, founders are using AI to think, not just to produce. The top three jobs are all strategic: decision support, ideation, and vision/strategy. That’s a stark contrast to PMs (whose top jobs are documents and prototypes) and designers (research synthesis and copy). And look at that #1 category: “productivity/decision support,” at 32.9%, is unlike anything else in the survey. No other role has a single use case this dominant. Founders are treating AI as a thought partner and sounding board, not just a tool for specific deliverables. This pattern may explain why founders report the highest satisfaction throughout the survey—they’ve figured out how to use AI for higher-leverage strategic work, not just production tasks.

4. Engineers are the outlier. For them, AI is doing just one big job: writing code, the core engineering task. Whereas for the PMs and designers, AI is helping them with supporting work. Farther down the list are jobs like documentation (7.7%), testing (6.2%), and code review (4.3%). These are the “boring but necessary” tasks engineers typically dislike. As you’ll see in the opportunities data below, that’s about to change. Engineers have accepted AI as a coding partner; now they want it to handle the tedious work that comes after the code has been written. One more pattern worth noting: engineers report the most mixed results on quality later in the survey (51% better but 21% worse, the highest “worse” of any role).