Multiple Big Tech Companies
Guo names a bottleneck that most enterprise AI postmortems miss: adoption stalls not because of tooling but because expertise is concentrated in one expensive 'fixer' per firm. Her sharper point — that frontier practitioners would rather join AI-native teams than upgrade incumbents from inside — describes a real talent flight, and it compounds: companies that ship faster attract exactly the people who could fix the others.… more
We mostly buy it, with two caveats: capital and proprietary data still anchor some top talent, and the biggest labs are themselves AI-native. Also note the messenger — a VC backing AI-native startups benefits when this narrative spreads. Still, we expect this observation to age well; today's 'fixers' look like tomorrow's founders.
multiple big tech companies have essentially one (very well paid) person who really knows how to use AI, and this “AI fixer” is their great hope — taking on projects and educating others.
problem is, some don’t have anyone, and a lot of those frontier people would rather work in a broadly AI-native company and find out what a team of people going …
Source:
X — Sarah Guo
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