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AI Productivity Doesn't Mean What I Think It Means
AI productivity should not be measured by doing the same tasks faster, but by the elevated quality of output that was previously unattainable.
What: Tom Tunguz argues that the industry's reliance on 'one-shot' prompt templates is yielding to more robust, closed-loop systems. Developers should leverage AI's capabilities to raise their baseline standards of work.
Why it matters: Organizations that equate AI solely with automation are missing the opportunity to leverage the technology for higher-complexity work that humans previously could not achieve at scale.
Original article
One-shot prompt templates often fail. The current best working architecture is a closed-loop taste flywheel. AI raises the ceiling of what the same effort produces. Users should push for the higher-quality output AI now makes possible rather than just accepting the pre-AI baseline.
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