Tap a claim on the ring to put it at the centre.
← A cancellation-reason drop-down measures list order rather than…
17 connected korrents · 16 moments on record from 18 Aug 2011 to 3 Sept 2026.
Everything filed under Anthropic
Anthropic
Everything filed under coding agents
coding agents
Everything filed under OpenAI
OpenAI
Everything filed under Trauma
Trauma
Everything filed under benchmarks
benchmarks 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: A cancellation-reason drop-down measures list order rather than reasons: randomise the options and every one of them gets picked equally. A cancellation-reason drop-down measures list order rather than reasons: randomise the options and every one of them gets picked equally. Last stated 7 months ago
25 Jan 2026
JC
Jason Cohen — holds since 2026-01-25 — tap for who they are
Same subject: A benchmark that ranks Claude Code last while it stays first in use is measuring the wrong thing, and has been for a year. — tap to centre the map on it A benchmark that ranks Claude Code last while it stays first in use is measuring the wrong thing, and has been for a year. Last stated 5 days ago
3 Sept 2026
DR
Dax Raad — holds since 2026-09-03 — tap for who they are
Same subject: The recommendation algorithm has no idea that you like surfing; it has a number that happens to correlate with surfing. — tap to centre the map on it The recommendation algorithm has no idea that you like surfing; it has a number that happens to correlate with surfing. Last stated 2 months ago
9 Jul 2026
AM
Adam Mosseri — holds since 2026-07-09 — tap for who they are
Same subject: A giving approach that ranks options only by estimated expected value, with no preference for better-grounded estimates, is flawed. — tap to centre the map on it A giving approach that ranks options only by estimated expected value, with no preference for better-grounded estimates, is flawed. Last stated 15 years ago
18 Aug 2011
HK
Holden Karnofsky — holds since 2011-08-18 — tap for who they are
Same subject: Every machine-learning deployment that has paid off so far left a person making the decision, which is the only reason imperfect models were useful. — tap to centre the map on it Every machine-learning deployment that has paid off so far left a person making the decision, which is the only reason imperfect models were useful. Last stated 4 weeks ago
12 Aug 2026
CF
Chelsea Finn — holds since 2026-08-12 — tap for who they are
Same subject: Coming into a project with a guess about what the data will show has, again and again, turned out to be wrong. — tap to centre the map on it Coming into a project with a guess about what the data will show has, again and again, turned out to be wrong. Last stated 4 months ago
8 May 2026
DR
David Reich — holds since 2026-05-08 — tap for who they are
Same subject: A plan that spells out every line of code to change gives you no leverage: it costs as long to read as the pull request, so you end up skimming it and reading the code twice. — tap to centre the map on it A plan that spells out every line of code to change gives you no leverage: it costs as long to read as the pull request, so you end up skimming it and reading the code twice. Last stated 2 months ago
15 Jul 2026
DH
Dex Horthy — holds since 2026-07-15 — tap for who they are
Same subject: Running a model five times and keeping the best answer buys a higher benchmark score without buying a better model. — tap to centre the map on it Running a model five times and keeping the best answer buys a higher benchmark score without buying a better model. Last stated 2 months ago
26 Jun 2026
NB
Noam Brown — holds since 2026-06-26 — tap for who they are
Same subject: Letting one calculation take over a giving decision is disturbing, and there is still a strong case for it if you want your ethics to be principled and about other people. — tap to centre the map on it Letting one calculation take over a giving decision is disturbing, and there is still a strong case for it if you want your ethics to be principled and about other people. Last stated 5 years ago
15 Feb 2022
HK
Holden Karnofsky — holds since 2022-02-15 — tap for who they are
Same subject: A language model asked to summarize its own system prompt risks that prompt's content biasing the summary it produces. — tap to centre the map on it A language model asked to summarize its own system prompt risks that prompt's content biasing the summary it produces. Last stated 6 days ago
2 Sept 2026
SW
Simon Willison — holds since 2026-09-02 — tap for who they are
Same subject: A trust that owns the mission protects a company better than founder control does, which is why Anthropic needs no dual-class shares. — tap to centre the map on it A trust that owns the mission protects a company better than founder control does, which is why Anthropic needs no dual-class shares. Last stated 4 months ago
10 May 2026
ER
Eric Ries — holds since 2026-05-10 — tap for who they are
Same subject: Agents can build about half a million lines before the codebase dissolves into a mess, and the next model will push that to a few million. — tap to centre the map on it Agents can build about half a million lines before the codebase dissolves into a mess, and the next model will push that to a few million. Last stated 6 months ago
11 Mar 2026
SY
Steve Yegge — holds since 2026-03-11 — tap for who they are
Same subject: A coding agent does not learn from its mistakes the way a person does -- it repeats the same error indefinitely unless a human notices and writes it down. — tap to centre the map on it A coding agent does not learn from its mistakes the way a person does -- it repeats the same error indefinitely unless a human notices and writes it down. Last stated 5 months ago
25 Mar 2026
MZ
Mario Zechner — holds since 2026-03-25 — tap for who they are
Same subject: A coding-agent company should not train its own model: it has to stay neutral ground for models to compete on. — tap to centre the map on it A coding-agent company should not train its own model: it has to stay neutral ground for models to compete on. Last stated 5 days ago
3 Sept 2026
DR
Dax Raad — holds since 2026-09-03 — tap for who they are
Same subject: A machine can complete the task and completely miss the job -- coding makes this easy to see precisely because its tasks are so legible and verifiable. — tap to centre the map on it A machine can complete the task and completely miss the job -- coding makes this easy to see precisely because its tasks are so legible and verifiable. Last stated 4 weeks ago
14 Aug 2026
SP
Sunil Pai — holds since 2026-08-14 — tap for who they are
Same subject: A startup should not begin life as a nonprofit and bolt a for-profit arm on later, whatever OpenAI's own history suggests. — tap to centre the map on it A startup should not begin life as a nonprofit and bolt a for-profit arm on later, whatever OpenAI's own history suggests. Last stated 2 years ago
18 Mar 2024
SA
Sam Altman — holds since 2024-03-18 — tap for who they are
Same subject: A technique that lets an AI model's reasoning shift outside its visible Chain of Thought is dangerous, both because it works and because a leading lab is willing to deploy it. — tap to centre the map on it A technique that lets an AI model's reasoning shift outside its visible Chain of Thought is dangerous, both because it works and because a leading lab is willing to deploy it. Last stated 5 days ago
3 Sept 2026
ZM
Zvi Mowshowitz — holds since 2026-09-03 — tap for who they are
Same subject: A tiny language model inventing a plausible-sounding name is the same phenomenon as a large one confidently stating a false fact. — tap to centre the map on it A tiny language model inventing a plausible-sounding name is the same phenomenon as a large one confidently stating a false fact. Last stated 7 months ago
12 Feb 2026
AK
Andrej Karpathy — holds since 2026-02-12 — tap for who they are
At the centre
A cancellation-reason drop-down measures list order rather than reasons: randomise the options and every one of them gets picked equally.
Holds JC Jason CohenRead this korrent →
A benchmark that ranks Claude Code last while it stays first in use is measuring the wrong thing, and has been for a year.
Holds
The recommendation algorithm has no idea that you like surfing; it has a number that happens to correlate with surfing.
Holds AM Adam Mosseri
A giving approach that ranks options only by estimated expected value, with no preference for better-grounded estimates, is flawed.
Holds HK Holden Karnofsky
Every machine-learning deployment that has paid off so far left a person making the decision, which is the only reason imperfect models were useful.
Holds CF Chelsea Finn
Coming into a project with a guess about what the data will show has, again and again, turned out to be wrong.
Holds DR David Reich
A plan that spells out every line of code to change gives you no leverage: it costs as long to read as the pull request, so you end up skimming it and reading the code twice.
Holds DH Dex Horthy
Running a model five times and keeping the best answer buys a higher benchmark score without buying a better model.
Holds NB Noam Brown
Letting one calculation take over a giving decision is disturbing, and there is still a strong case for it if you want your ethics to be principled and about other people.
Holds HK Holden Karnofsky
A language model asked to summarize its own system prompt risks that prompt's content biasing the summary it produces.
Holds
A trust that owns the mission protects a company better than founder control does, which is why Anthropic needs no dual-class shares.
Holds ER Eric Ries
Agents can build about half a million lines before the codebase dissolves into a mess, and the next model will push that to a few million.
Holds SY Steve Yegge
A coding agent does not learn from its mistakes the way a person does -- it repeats the same error indefinitely unless a human notices and writes it down.
Holds
A coding-agent company should not train its own model: it has to stay neutral ground for models to compete on.
Holds
A machine can complete the task and completely miss the job -- coding makes this easy to see precisely because its tasks are so legible and verifiable.
Holds
A startup should not begin life as a nonprofit and bolt a for-profit arm on later, whatever OpenAI's own history suggests.
Holds
A technique that lets an AI model's reasoning shift outside its visible Chain of Thought is dangerous, both because it works and because a leading lab is willing to deploy it.
Holds ZM Zvi Mowshowitz
A tiny language model inventing a plausible-sounding name is the same phenomenon as a large one confidently stating a false fact.
Holds