Follow the Drudgery
Summary
The roles and tasks most transformed by AI won’t be where AI is “smartest” — they’ll be where there’s the most tedious busywork. This inverts the common assumption that AI’s highest-impact use cases are the most intellectually complex ones. Instead, the data shows that people don’t want AI to do the interesting parts of their job — they want it to do the parts they hate.
Engineers demonstrate this clearly: their dominant AI use case is writing code (51%), but their biggest demand gaps are documentation (+25.8pp), code review (+24.5pp), and writing tests (+23.5pp) — the boring-but-necessary tasks they typically dislike. The pattern generalizes: to predict where AI will create the most value in any role or workflow, look for the highest concentration of tedious, repetitive, necessary-but-unloved work.
How to Apply
When evaluating AI adoption priorities for a team or role:
- Map the drudgery: List the tasks people consistently avoid, complain about, or let pile up — not the intellectually challenging ones
- Prioritize automation there: Tools that eliminate tedious work will see faster adoption and higher satisfaction than tools that try to replace creative or strategic work
- Use as a product signal: If you’re building AI tools, “follow the drudgery” is a market-selection heuristic — the roles with the most busywork are the biggest opportunities
This is also a useful counter-argument when stakeholders want to apply AI to the flashiest, most complex problems first. The ROI is often higher on the boring stuff.
Sources
From: AI Tools Are Overdelivering: Large-Scale AI Productivity Survey
Key quote: “People don’t want AI to do the interesting parts of their job. They want it to do the parts they hate. […] The roles most transformed won’t be the ones where AI is ‘smartest.’ They’ll be the ones with the most tedious busywork. Follow the drudgery, and you’ll find where AI creates the most value.” Attribution: Lenny Rachitsky, Noam Segal What this source adds: Empirical backing from 1,750 respondents. Engineers’ demand gaps (docs +25.8pp, code review +24.5pp, tests +23.5pp) vs. writing code (+5.6pp) provide the clearest evidence. Founders’ high satisfaction correlates with using AI for high-leverage strategic work, but the framework explains why within any given role, drudgery elimination drives the most value. Links: Original | Archive
Related
- AI Production-Thinking Spectrum — Complementary lens: “follow the drudgery” predicts within-role value; production-thinking spectrum predicts cross-role satisfaction
- AI Disrupts Strategic PM Skills Most — Tension: strategic skills have the highest disruption potential, but drudgery elimination has the highest adoption pull
- Intentional Understaffing for AI-First Teams — When you remove staff, the drudgery is what AI must absorb first