Every collects 100 leader predictions on work and AI in 2027: answers get cheap, questions get valuable
danshipper · x · 2026-09-11
Every's new "Thesis Statements" series gathers 100 founders, investors, and researchers predicting what work looks like after AI automation in 2027.
Highlights:
- Anne-Laure Le Cunff (Ness Labs): answers become abundant; the value shifts to knowing which questions are worth asking
- Chris Pedregal (Granola): some of your hardest problems will solve themselves
- Dan Shipper (Every): there will be more human work than ever
- Karri Saarinen (Linear): AI's biggest problem will be design
- Sari Azout (Sublime): your attention will be handed back to you
- Others cover computational thinking, boring infrastructure winning, and jobs AI can't do scaling
Overall bullish on expert human work after automation; new statements roll out continuously.
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