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Overview
Personal website of Christian Henning, machine learning researcher and engineer. Home to a blog on ML theory, engineering and research leadership — and on what it takes to move frontier ML from research to real-world production.
News
Same Evidence, Opposite Certainty: Why AI Timelines Polarize on Shared Evidence
AI timelines never converge, a life-long belief about human intelligence keeps shaping how new evidence gets read, and an imprecise definition of AGI means the two sides were never comparing the same thing. The first is a well-documented mechanism from th
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Trust Is a Posterior: Why Good Work Can Only Be Appreciated Statistically
A shipped feature reveals almost nothing about how well it was built, because from the outside the quality of engineering work is a credence good. Trust accumulated across many projects is the only statistically valid way to price it.
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Ship the Upgrade Path First: Distribution as a Control Plane for Fast Iteration
The fastest-moving products are not the ones with the cleverest features, but the ones that can change what is already deployed. For self-hosted software that means building distribution and self-upgrade first, because without them there is no iterate ste
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The Two Cuts of an MVP - Why Iterating and Incrementing Both Come Down to Vision
Every "cut it for the MVP" is one of two moves. You either defer a feature or build a throwaway stand-in. Whether either becomes debt depends not on the cut but on the boundary you leave beneath it, and on a vision clear enough to place it.
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Your Best Work Leaves No Trace: Why Engineering Teams Reward the Fix and Replace the Prevention
From testing and reliability engineering to team culture, the hardest problems are prevented, not fixed. Yet we chronically undervalue prevention, and let visible process stand in for the invisible outcomes that actually matter.
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