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← In AI, great engineers can contribute to progress at the same level as great researchers.
17 connected korrents · 15 moments from 14 Jul 2018 to 23 Oct 2026.
Everything filed under team size
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AI and jobs Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Read this korrent: In AI, great engineers can contribute to progress at the same level as great researchers. In AI, great engineers can contribute to progress at the same level as great researchers. Last stated 5 years ago
11 Apr 2022
GB
Greg Brockman — holds since 2022-04-11 — tap for who they are
Same subject: Software engineers who master AI will generally fare better than those who do not. — tap to centre the map on it Software engineers who master AI will generally fare better than those who do not. Last stated a week ago
23 Oct 2026
GO
Gergely Orosz — holds since 2026-10-23 — tap for who they are
Same subject: Progress in AI takes a very strong dozen or two researchers, not hundreds or thousands of them. — tap to centre the map on it Progress in AI takes a very strong dozen or two researchers, not hundreds or thousands of them. Last stated 5 months ago
10 Jun 2026
MZ
Mark Zuckerberg — holds since 2026-06-10 — tap for who they are
Same subject: AI tooling has not compressed the gap between great and average engineers: it is still two or three times, and for the same reasons as before — curiosity and appetite for the bleeding edge. — tap to centre the map on it AI tooling has not compressed the gap between great and average engineers: it is still two or three times, and for the same reasons as before — curiosity and appetite for the bleeding edge. Last stated 7 months ago
1 Apr 2026
TP
Thuan Pham — holds since 2026-04-01 — tap for who they are
Same subject: AI research is by far the most impactful place for engineers who want to build useful systems. — tap to centre the map on it AI research is by far the most impactful place for engineers who want to build useful systems. Last stated 5 years ago
11 Apr 2022
GB
Greg Brockman — holds since 2022-04-11 — tap for who they are
Same subject: As AI systems get better at scientific research tasks, it becomes more likely they will soon be capable of improving and building themselves. — tap to centre the map on it As AI systems get better at scientific research tasks, it becomes more likely they will soon be capable of improving and building themselves. Last stated 2 months ago
17 Aug 2026
JC
Jack Clark — holds since 2026-08-17 — tap for who they are
Same subject: AI progress comes from a simple, systematic way of improving models, not from researchers suddenly getting smarter. — tap to centre the map on it AI progress comes from a simple, systematic way of improving models, not from researchers suddenly getting smarter. Last stated a year ago
16 Jun 2025
JK
Jared Kaplan — holds since 2025-06-16 — tap for who they are
Same subject: AI researchers should contribute ideas but stop enacting them: a single queue of ideas and automated workers should run the experiments. — tap to centre the map on it AI researchers should contribute ideas but stop enacting them: a single queue of ideas and automated workers should run the experiments. Last stated 7 months ago
20 Mar 2026
AK
Andrej Karpathy — holds since 2026-03-20 — tap for who they are
Same subject: AI will not replace the best programmers; it will make them ten times more productive than they are today. — tap to centre the map on it AI will not replace the best programmers; it will make them ten times more productive than they are today. Last stated a year ago
23 Jul 2025
DH
Demis Hassabis — holds since 2025-07-23 — tap for who they are
Same subject: A few senior individual contributors can be paid VP money and still cost less than the layered product org they replace. — tap to centre the map on it A few senior individual contributors can be paid VP money and still cost less than the layered product org they replace. Last stated 3 months ago
2 Aug 2026
TV
Tom Verrilli — holds since 2026-08-02 — tap for who they are
Same subject: A functionally organised engineering team seizes up at around a hundred people, because every feature then has to be negotiated against every other team's bandwidth. — tap to centre the map on it A functionally organised engineering team seizes up at around a hundred people, because every feature then has to be negotiated against every other team's bandwidth. Last stated 7 months ago
1 Apr 2026
TP
Thuan Pham — holds since 2026-04-01 — tap for who they are
Same subject: A group of fewer than four people is not a team: it behaves like a set of individuals, and a single departure knocks it back into maintenance. — tap to centre the map on it A group of fewer than four people is not a team: it behaves like a set of individuals, and a single departure knocks it back into maintenance. Last stated 8 years ago
14 Jul 2018
WL
Will Larson — holds since 2018-07-14 — tap for who they are
Same subject: A narrow, highly accurate model can beat a general one inside its own domain, as AlphaFold did, and materials science and chip design are next. — tap to centre the map on it A narrow, highly accurate model can beat a general one inside its own domain, as AlphaFold did, and materials science and chip design are next. Last stated 3 months ago
30 Jul 2026
JD
Jeff Dean — holds since 2026-07-30 — tap for who they are
Same subject: Contemporary physical and evolutionary structure-prediction approaches fall far short of experimental accuracy without a close experimental homologue, limiting biological utility. — tap to centre the map on it Contemporary physical and evolutionary structure-prediction approaches fall far short of experimental accuracy without a close experimental homologue, limiting biological utility. Last stated 5 years ago
15 Jul 2021
DH
Demis Hassabis — holds since 2021-07-15 — tap for who they are
Same subject: Deep learning has effectively solved the problem of predicting a protein's 3D structure from its sequence. — tap to centre the map on it Deep learning has effectively solved the problem of predicting a protein's 3D structure from its sequence. Last stated a year ago
29 Jun 2025
EH
Elliot Hershberg — holds since 2025-06-29 — tap for who they are
Same subject: A persistently rising dividend yield eventually forces capital appreciation as the market rerates the stock. — tap to centre the map on it A persistently rising dividend yield eventually forces capital appreciation as the market rerates the stock. Last stated 8 months ago
3 Mar 2026
SB
Sanjay Bakshi — holds since 2026-03-03 — tap for who they are
Same subject: A proof and an explanation are different things, and a theorem can stay an unsolved expository problem long after it is proved. — tap to centre the map on it A proof and an explanation are different things, and a theorem can stay an unsolved expository problem long after it is proved. Last stated 4 months ago
30 Jun 2026
GS
Grant Sanderson — holds since 2026-06-30 — tap for who they are
Same subject: A stream of AI-written papers with any error rate at all becomes insufferable, because finding the error costs more than the paper is worth even at ninety-nine percent. — tap to centre the map on it A stream of AI-written papers with any error rate at all becomes insufferable, because finding the error costs more than the paper is worth even at ninety-nine percent. Last stated 4 months ago
30 Jun 2026
GS
Grant Sanderson — holds since 2026-06-30 — tap for who they are
At the centre
In AI, great engineers can contribute to progress at the same level as great researchers.
Holds Read this korrent →
Software engineers who master AI will generally fare better than those who do not.
Holds
Progress in AI takes a very strong dozen or two researchers, not hundreds or thousands of them.
Holds
AI tooling has not compressed the gap between great and average engineers: it is still two or three times, and for the same reasons as before — curiosity and appetite for the bleeding edge.
Holds
AI research is by far the most impactful place for engineers who want to build useful systems.
Holds
As AI systems get better at scientific research tasks, it becomes more likely they will soon be capable of improving and building themselves.
Holds
AI progress comes from a simple, systematic way of improving models, not from researchers suddenly getting smarter.
Holds
AI researchers should contribute ideas but stop enacting them: a single queue of ideas and automated workers should run the experiments.
Holds
AI will not replace the best programmers; it will make them ten times more productive than they are today.
Holds
A few senior individual contributors can be paid VP money and still cost less than the layered product org they replace.
Holds
A functionally organised engineering team seizes up at around a hundred people, because every feature then has to be negotiated against every other team's bandwidth.
Holds
A group of fewer than four people is not a team: it behaves like a set of individuals, and a single departure knocks it back into maintenance.
Holds
A narrow, highly accurate model can beat a general one inside its own domain, as AlphaFold did, and materials science and chip design are next.
Holds
Contemporary physical and evolutionary structure-prediction approaches fall far short of experimental accuracy without a close experimental homologue, limiting biological utility.
Holds
Deep learning has effectively solved the problem of predicting a protein's 3D structure from its sequence.
Holds
A persistently rising dividend yield eventually forces capital appreciation as the market rerates the stock.
Holds
A proof and an explanation are different things, and a theorem can stay an unsolved expository problem long after it is proved.
Holds
A stream of AI-written papers with any error rate at all becomes insufferable, because finding the error costs more than the paper is worth even at ninety-nine percent.
Holds