It seems like writing will no longer be an important part of the research process. It can easily be outsourced to AI. What's going to matter is the way researchers curate their materials. Claude Code was able to do a good job partially because I already had a well-curated list of materials, and I knew the direction of the argument. That said, researchers will still need to learn writing because it helps you think through problems.

Most people I know in AI think the median person is screwed, and they have no idea what to do about it. I spent the last 3 months talking to dozens of researchers, economists, and policy experts about AI's impact on work; including reps from every frontier lab and several Congressional offices. Unfortunately, I was not reassured. The AI industry is raising the alarm, but can't change course. These companies' core business model relies on the disruption they are warning about: their faith in full automation only makes them go faster. Policymakers are waking up, but still paralyzed by data and debates. Econ wonks disagree on plenty, but even the limited scenario looks like a "painful transition" that will disempower millions of workers. But an "underclass" is not inevitable, but rather a societal choice — and one we can and should stop. Instead of waiting for impact, we should start planning now to support workers through AI disruption. Whether policymakers can assuage concerns about economic security may determine if we get to reap AI's gains at all. New from me for @NYTOpinion. I put a ton into researching what I think may be the biggest topic of the year, so hope you read it (gift link here!) nytimes.com/2026/04/30/opini…