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← Code quality still matters even as LLMs make writing code much faster.
17 connected korrents · 17 moments on record from 17 Apr 2012 to 12 Sept 2026. Nearly all of them are about software quality .
Everything filed under LLMs
LLMs
Everything filed under coding agents
coding agents
Everything filed under Apple
Apple
Everything filed under AI slop
AI slop
Everything filed under design
design 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: Code quality still matters even as LLMs make writing code much faster. Code quality still matters even as LLMs make writing code much faster. Last stated 2 months ago
10 Jul 2026
FS
Fabien Sanglard — holds since 2026-07-10 — tap for who they are
Same subject: A language-agnostic conformance suite is the most powerful thing you can hand a coding agent, because the whole instruction becomes: write code until these tests pass. — tap to centre the map on it A language-agnostic conformance suite is the most powerful thing you can hand a coding agent, because the whole instruction becomes: write code until these tests pass. Last stated 6 months ago
19 Mar 2026
SW
Simon Willison — holds since 2026-03-19 — tap for who they are
Same subject: A passing test suite is not evidence that the software works, so an agent must also be made to start the thing and exercise it the way a person would. — tap to centre the map on it A passing test suite is not evidence that the software works, so an agent must also be made to start the thing and exercise it the way a person would. Last stated 6 months ago
19 Mar 2026
SW
Simon Willison — holds since 2026-03-19 — tap for who they are
Same subject: Adding a config option so nobody breaks compounds into permutations no test suite can cover, because it is infinitely harder to evolve software that has users. — tap to centre the map on it Adding a config option so nobody breaks compounds into permutations no test suite can cover, because it is infinitely harder to evolve software that has users. Last stated a month ago
10 Aug 2026
PS
Peter Steinberger — holds since 2026-08-10 — tap for who they are
Same subject: Agentic code review raises the floor but cannot be trusted, because the model reading the code is the same model that wrote it, and it will tell you the code is great. — tap to centre the map on it Agentic code review raises the floor but cannot be trusted, because the model reading the code is the same model that wrote it, and it will tell you the code is great. Last stated 2 months ago
15 Jul 2026
DH
Dex Horthy — holds since 2026-07-15 — tap for who they are
Same subject: Apple has more reason to stumble now than ever: terribly behind on AI, faltering software quality, rivals catching up on silicon, and a leadership too old to relearn. — tap to centre the map on it Apple has more reason to stumble now than ever: terribly behind on AI, faltering software quality, rivals catching up on silicon, and a leadership too old to relearn. Last stated a year ago
12 Jul 2025
DH
David Heinemeier Hansson — holds since 2025-07-12 — tap for who they are
Same subject: Astra writes weird Python slop when one step removed from normal code, and its unit tests are horrific. — tap to centre the map on it Astra writes weird Python slop when one step removed from normal code, and its unit tests are horrific. Last stated 2 weeks ago
6 Sept 2026
AR
Armin Ronacher — holds since 2026-09-06 — tap for who they are
Same subject: Building on a model is unlike any previous software engineering, because the thing you are building on cannot be designed up front. — tap to centre the map on it Building on a model is unlike any previous software engineering, because the thing you are building on cannot be designed up front. Last stated 2 months ago
27 Jul 2026
BC
Boris Cherny — holds since 2026-07-27 — tap for who they are
Same subject: Making test coverage a target destroys it, because high coverage numbers are easy to reach with worthless tests. — tap to centre the map on it Making test coverage a target destroys it, because high coverage numbers are easy to reach with worthless tests. Last stated 14 years ago
17 Apr 2012
MF
Martin Fowler — holds since 2012-04-17 — 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 9 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 2 months ago
15 Jul 2026
DH
Dex Horthy — holds since 2026-07-15 — tap for who they are
Same subject: A child who has seen ten cats learns what a machine needs the whole internet of cat photos for, by a learning pathway nobody has solved. — tap to centre the map on it A child who has seen ten cats learns what a machine needs the whole internet of cat photos for, by a learning pathway nobody has solved. Last stated a month ago
10 Aug 2026
FL
Fei-Fei Li — holds since 2026-08-10 — tap for who they are
Same subject: Humans can generally perform new language tasks from few examples or simple instructions, while current NLP systems largely cannot. — tap to centre the map on it Humans can generally perform new language tasks from few examples or simple instructions, while current NLP systems largely cannot. Last stated 6 years ago
28 May 2020
DA
Dario Amodei — holds since 2020-05-28 — tap for who they are
Same subject: Language models are already a form of AGI; what the labs are chasing is a further step, not the arrival of general intelligence. — tap to centre the map on it Language models are already a form of AGI; what the labs are chasing is a further step, not the arrival of general intelligence. Last stated 2 years ago
3 Feb 2025
NL
Nathan Lambert — holds since 2025-02-03 — tap for who they are
Same subject: The jump from Sol to Astra is larger than from Fable 5 to Fable 5.1, and Astra is the best model for ambitious projects with likely the highest raw intelligence of any model. — tap to centre the map on it The jump from Sol to Astra is larger than from Fable 5 to Fable 5.1, and Astra is the best model for ambitious projects with likely the highest raw intelligence of any model. Last stated a week ago
12 Sept 2026
ZM
Zvi Mowshowitz — holds since 2026-09-12 — tap for who they are
Same subject: AI progress is faster than people expect, and ordinary scaling can be enough to solve problems that looked very hard. — tap to centre the map on it AI progress is faster than people expect, and ordinary scaling can be enough to solve problems that looked very hard. Last stated 2 years ago
2 Feb 2025
AC
Ajeya Cotra — holds since 2023-08-29 — tap for who they are
SA
Scott Alexander — holds since 2022-09-12 — tap for who they are
MB
Miles Brundage — holds since 2025-02-02 — tap for who they are
Same subject: Current techniques restrict pre-trained representation power because standard language models are unidirectional. — tap to centre the map on it Current techniques restrict pre-trained representation power because standard language models are unidirectional. Last stated 8 years ago
11 Oct 2018
KT
Kristina Toutanova — holds since 2018-10-11 — tap for who they are
MC
Ming-Wei Chang — holds since 2018-10-11 — tap for who they are
KL
Kenton Lee — holds since 2018-10-11 — tap for who they are
JD
Jacob Devlin — holds since 2018-10-11 — tap for who they are
Same subject: Emergent abilities come from generalisation turning compositional, not merely from a training set containing a lot of stuff. — tap to centre the map on it Emergent abilities come from generalisation turning compositional, not merely from a training set containing a lot of stuff. Last stated a year ago
12 Sept 2025
SL
Sergey Levine — holds since 2025-09-12 — tap for who they are
At the centre
Code quality still matters even as LLMs make writing code much faster.
Holds Read this korrent →
A language-agnostic conformance suite is the most powerful thing you can hand a coding agent, because the whole instruction becomes: write code until these tests pass.
Holds
A passing test suite is not evidence that the software works, so an agent must also be made to start the thing and exercise it the way a person would.
Holds
Adding a config option so nobody breaks compounds into permutations no test suite can cover, because it is infinitely harder to evolve software that has users.
Holds
Agentic code review raises the floor but cannot be trusted, because the model reading the code is the same model that wrote it, and it will tell you the code is great.
Holds
Apple has more reason to stumble now than ever: terribly behind on AI, faltering software quality, rivals catching up on silicon, and a leadership too old to relearn.
Holds
Astra writes weird Python slop when one step removed from normal code, and its unit tests are horrific.
Holds
Building on a model is unlike any previous software engineering, because the thing you are building on cannot be designed up front.
Holds
Making test coverage a target destroys it, because high coverage numbers are easy to reach with worthless tests.
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 child who has seen ten cats learns what a machine needs the whole internet of cat photos for, by a learning pathway nobody has solved.
Holds
Humans can generally perform new language tasks from few examples or simple instructions, while current NLP systems largely cannot.
Holds
Language models are already a form of AGI; what the labs are chasing is a further step, not the arrival of general intelligence.
Holds
The jump from Sol to Astra is larger than from Fable 5 to Fable 5.1, and Astra is the best model for ambitious projects with likely the highest raw intelligence of any model.
Holds
AI progress is faster than people expect, and ordinary scaling can be enough to solve problems that looked very hard.
Holds
Current techniques restrict pre-trained representation power because standard language models are unidirectional.
Holds
Emergent abilities come from generalisation turning compositional, not merely from a training set containing a lot of stuff.
Holds