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Author @defi_dua asserts education was the earliest product–market fit (PMF) for…

2026-07-09 · 05:45 UTC ·@defi_dua ·0 min read

Brief

Author @defi_dua argues education was AI’s earliest PMF, noting AI EdTech achieved unusually high engagement and retention but failed to become a $10B+ market because of seasonality and low student LTV. Paul Graham’s cited Brown professor anecdote—with midterm (orange) and in-person final (gray) scores—illustrates widespread AI-assisted cheating, leaving only three honest midterm scores.

Why it matters

Author @defi_dua asserts education was the earliest product–market fit (PMF) for AI, claiming AI EdTech delivered exceptional engagement and retention compared with most consumer products.

Key details

  • They argue AI EdTech didn’t scale to a $10B+ revenue category due to structural EdTech constraints—seasonality and low lifetime value (LTV) of students.
  • Paul Graham shared a Brown professor anecdote: a take-home midterm (orange points) vs an in-person final (gray points) showed that all but three students appear to have cheated on the midterm using AI.
Source evidence

Earliest PMF of AI was always education

AI Edtech might not have panned out as a $10B+ revenue field but that’s a structural Edtech issue of seasonality/LTV of graduating students

Pound for pound our engagement/retention was north of most consumer products’ wildest dreams

Paul Graham (@paulg)

A Brown professor gave his students a take-home midterm exam. After suspecting many cheated using AI, he made the final in-person. The orange dots are the midterm scores and the gray dots are the final scores. Looks like all but 3 cheated on the midterm.

— https://nitter.net/paulg/status/2075031014628311236#m