Dwarkesh bets there will be overall more demand for human software engineers in 2027 than today, largely due to AI acting as a complementary input rather than a replacement.
Dwarkesh bets there will be overall more demand for human software engineers in 2027 than today, largely due to AI acting as a complementary input rather than a replacement.
Where this was said
At 9:42 · chapter starts 8:46
Dwarkesh argues inefficiency doesn't block white-collar automation because AI's training costs amortize across billions of sessions. [1] — Dwarkesh Patel "AIs can be wildly data-inefficient and still automate white-collar work, because common tasks are common enough to bring into the training …" 07:48 He bets on more human software engineers in 2027, and previews a future post on the intelligence explosion. [2] — Dwarkesh Patel "Current discourse on intelligence explosions is stuck between two bad takes: it's impossible, or a god emerges at the end. Neither is right…" 10:17
Software engineering is supposed to be the first job AI takes. But Dwarkesh bets there will be more demand for human software engineers in 2027 than today — because AI is acting as a complementary input that expands the overall market for software.
Current discourse on intelligence explosions is stuck between two bad takes: it's impossible, or a god emerges at the end. Neither is right. The real question is what a period of faster-than-usual AI progress looks like when it's built atop the particular kind of intelligence LLMs represent.
Avnish's solopreneur business reached $25,000 per month in revenue using a community-driven, zero-ad-spend marketing strategy.
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Highlighting time savings, money savings, or a painful problem solved in the headline and subheading is the core conversion lever.
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