Sachin Katti
VP of Compute Strategy, OpenAI · 1 appearance on the record.
computed by AI from the episodes · how this works → · full disclaimer →
executiveacademicscientistfounder@sk7037 ↗stanford.edu/~skatti ↗
Before joining OpenAI to lead large-scale compute infrastructure, data center, and Stargate strategy, Katti served as Chief Technology and AI Officer and Senior Vice President at Intel. He spent years as a professor at Stanford University and co-founded tech startups including Kumu Networks and Uhana.
6 supported 1 partly supported 0 contradicted 7 not checkable as stated how the 14 claims stand · each chip opens the sources
4 predictions · 10 assertions · 2 opinions · 1 insight · 4 disclosures · every statement was checked. The predictions and assertions are the 14 claims: statements the public record can support or contradict. 7 are resolved, and 7 name no date, number or outcome precise enough to check. Everything else (opinions, insights, what ifs, disclosures) can never be settled by the record, so it carries no assessment.
The record, in short
What the tape says about how Sachin argues and how the claims held up. Everything they said, and everything said about them, is in the tabs below.
Their most notable supported claim
Expressed certainty vs assessment result
weighted support: a fully supported claim counts one, a partly supported claim counts half. Each filled bar is clickable and opens exactly those claims; "none yet" means nothing said at that certainty level has resolved yet
Argument clarity: do they answer the question? how? →
answered every one of 12 assessed questions directly
This is a score against a rubric. It is not a rank. Every host question → answer exchange is scored with names hidden on directness, coherence, precision and compression, 1–5 each, on meaning alone: disfluencies are ignored, and only raw unedited episodes count. This is the score that measures thought. Every scored exchange, scores shown → · The rubric and its checks →
How they sound: speaking style how? →
222 words/min while actually speaking · 41.9 um and uh per 1k words
Measured by listening to the audio itself: 5,078 words across 1 episode of raw-level tape, transcribed verbatim with every um and uh kept, each one attributed only where the alignment onto our timed stream is unambiguous. These are measurements of speaking style. We do not rank them: across this corpus, fluency and argument quality are nearly uncorrelated (ρ≈0.2), and smooth talking does not signal clear thinking. How it's measured →
Everything Sachin Katti said on the MAD Podcast that made the record, most notable first. Filter by type, assessment or year in the ledger →
Appearances (1)
| Episode | Date | Speaking time |
|---|---|---|
| OpenAI’s Compute Chief: We Can’t Build Fast Enough | Sachin Katti | Jul 16, 2026 | 27m |