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← The lessons learned from success are worth applying more, while…
17 connected korrents · 17 moments from 25 Oct 2023 to 17 Sept 2026.
Everything filed under innovation
innovation
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behavioural science
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patience 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: The lessons learned from success are worth applying more, while lessons from failure tend to be generic or get in the way. The lessons learned from success are worth applying more, while lessons from failure tend to be generic or get in the way. Last stated 2 months ago
23 Aug 2026
SA
Sam Altman — holds since 2026-08-23 — tap for who they are
Same subject: In iterative problem-solving, each failure has value because it rules out one way that doesn't work. — tap to centre the map on it In iterative problem-solving, each failure has value because it rules out one way that doesn't work. Last stated 9 months ago
6 Feb 2026
AK
Arvid Kahl — holds since 2026-02-06 — tap for who they are
Same subject: It is not clear what you can learn from your mistakes; you learn by moving forward and doing new things. — tap to centre the map on it It is not clear what you can learn from your mistakes; you learn by moving forward and doing new things. Last stated 9 months ago
15 Feb 2026
JF
Jason Fried — holds since 2026-02-15 — tap for who they are
Same subject: People do not automatically learn from their failures. — tap to centre the map on it People do not automatically learn from their failures. Last stated 4 months ago
9 Jul 2026
CD
Charles Duhigg — holds since 2026-07-09 — tap for who they are
Same subject: Rate of iteration separates success from failure: a competitor learning one thing a month will never matter to a company learning one thing a week. — tap to centre the map on it Rate of iteration separates success from failure: a competitor learning one thing a month will never matter to a company learning one thing a week. Last stated 3 months ago
7 Aug 2026
MH
Max Hodak — holds since 2026-08-07 — tap for who they are
Same subject: Build where today's models succeed one percent of the time, not twenty: partial success means the capability is already arriving. — tap to centre the map on it Build where today's models succeed one percent of the time, not twenty: partial success means the capability is already arriving. Last stated 3 months ago
30 Jul 2026
JD
Jeff Dean — holds since 2026-07-30 — tap for who they are
Same subject: When learning from someone successful, copy only what is repeatable; the rest of their success cannot be reproduced. — tap to centre the map on it When learning from someone successful, copy only what is repeatable; the rest of their success cannot be reproduced. Last stated 3 years ago
7 Apr 2024
MH
Morgan Housel — holds since 2024-04-07 — tap for who they are
Same subject: People tend to remember the outcomes of things that worked out and forget the many attempts that led nowhere. — tap to centre the map on it People tend to remember the outcomes of things that worked out and forget the many attempts that led nowhere. Last stated 3 months ago
29 Jul 2026
ZH
Zach Holman — holds since 2026-07-29 — tap for who they are
Same subject: Ordinary learning from experience makes organizations abandon things after early failure, so good things are dropped too soon — tap to centre the map on it Ordinary learning from experience makes organizations abandon things after early failure, so good things are dropped too soon
JM
James G. March — holds since c. 2013 — tap for who they are
Same subject: "Lots of anonymous people worked it out by trial and error" is never the real story of an invention: on closer investigation, identifiable people always turn out to be responsible. — tap to centre the map on it "Lots of anonymous people worked it out by trial and error" is never the real story of an invention: on closer investigation, identifiable people always turn out to be responsible. Last stated 3 years ago
25 Oct 2023
AH
Anton Howes — holds since 2023-10-25 — tap for who they are
Same subject: A business can have market fit, real advantages, and sustained effort behind a hard product and still fail if it doesn't give customers a strong enough reason to switch from what they already use. — tap to centre the map on it A business can have market fit, real advantages, and sustained effort behind a hard product and still fail if it doesn't give customers a strong enough reason to switch from what they already use. Last stated 5 months ago
2 Jun 2026
JJ
Justin Jackson — holds since 2026-06-02 — tap for who they are
Same subject: A capability existing is not the same as a capability being absorbed: how fast a technology changes the world is not set by how fast the technology improves. — tap to centre the map on it A capability existing is not the same as a capability being absorbed: how fast a technology changes the world is not set by how fast the technology improves. Last stated 3 months ago
21 Jul 2026
RT
Ruxandra Teslo — holds since 2026-07-21 — tap for who they are
Same subject: "Scaling" was powerful because it was one word: naming a research direction is what tells a whole field what to do next. — tap to centre the map on it "Scaling" was powerful because it was one word: naming a research direction is what tells a whole field what to do next. Last stated 11 months ago
25 Nov 2025
IS
Ilya Sutskever — holds since 2025-11-25 — tap for who they are
Same subject: A benchmark result should be reported under a stated budget, or as a curve against test-time compute — never as a single number. — tap to centre the map on it A benchmark result should be reported under a stated budget, or as a curve against test-time compute — never as a single number. Last stated 4 months ago
26 Jun 2026
NB
Noam Brown — holds since 2026-06-26 — tap for who they are
Same subject: A lab should spend most of its compute on research rather than on building the next model, because research is where the tenfold yearly efficiency gains come from. — tap to centre the map on it A lab should spend most of its compute on research rather than on building the next model, because research is where the tenfold yearly efficiency gains come from. Last stated 8 months ago
13 Mar 2026
DP
Dylan Patel — holds since 2026-03-13 — tap for who they are
Same subject: A badly written AI outbound email is evidence of a bad vendor, not of a limit of AI. — tap to centre the map on it A badly written AI outbound email is evidence of a bad vendor, not of a limit of AI. Last stated 10 months ago
1 Jan 2026
JL
Jason Lemkin — holds since 2026-01-01 — tap for who they are
Same subject: A bigger context window does not give you a smarter model; the intelligence of the model is what decides how much of that window it can actually attend to. — tap to centre the map on it A bigger context window does not give you a smarter model; the intelligence of the model is what decides how much of that window it can actually attend to. Last stated 4 months ago
15 Jul 2026
DH
Dex Horthy — holds since 2026-07-15 — tap for who they are
Same subject: A body of publications is easy for AI models to consume via pretraining corpora but cumbersome for most humans due to CAPTCHAs, accounts, and paywalls. — tap to centre the map on it A body of publications is easy for AI models to consume via pretraining corpora but cumbersome for most humans due to CAPTCHAs, accounts, and paywalls. Last stated a month ago
17 Sept 2026
PC
Patrick Collison — holds since 2026-09-17 — tap for who they are
At the centre
The lessons learned from success are worth applying more, while lessons from failure tend to be generic or get in the way.
Holds Read this korrent →
In iterative problem-solving, each failure has value because it rules out one way that doesn't work.
Holds
It is not clear what you can learn from your mistakes; you learn by moving forward and doing new things.
Holds
People do not automatically learn from their failures.
Holds
Rate of iteration separates success from failure: a competitor learning one thing a month will never matter to a company learning one thing a week.
Holds
Build where today's models succeed one percent of the time, not twenty: partial success means the capability is already arriving.
Holds
When learning from someone successful, copy only what is repeatable; the rest of their success cannot be reproduced.
Holds
People tend to remember the outcomes of things that worked out and forget the many attempts that led nowhere.
Holds
Ordinary learning from experience makes organizations abandon things after early failure, so good things are dropped too soon
Last stated c. 2013
Holds
"Lots of anonymous people worked it out by trial and error" is never the real story of an invention: on closer investigation, identifiable people always turn out to be responsible.
Holds
A business can have market fit, real advantages, and sustained effort behind a hard product and still fail if it doesn't give customers a strong enough reason to switch from what they already use.
Holds
A capability existing is not the same as a capability being absorbed: how fast a technology changes the world is not set by how fast the technology improves.
Holds
"Scaling" was powerful because it was one word: naming a research direction is what tells a whole field what to do next.
Holds
A benchmark result should be reported under a stated budget, or as a curve against test-time compute — never as a single number.
Holds
A lab should spend most of its compute on research rather than on building the next model, because research is where the tenfold yearly efficiency gains come from.
Holds
A badly written AI outbound email is evidence of a bad vendor, not of a limit of AI.
Holds
A bigger context window does not give you a smarter model; the intelligence of the model is what decides how much of that window it can actually attend to.
Holds
A body of publications is easy for AI models to consume via pretraining corpora but cumbersome for most humans due to CAPTCHAs, accounts, and paywalls.
Holds