For me the biggest signifier is Spotify. They claim their (best) devs don't even code anymore, they use an internal AI tool that they just send prompts to which then checks out a personal test build that they can download off of Slack. "A new feature in 10 minutes!"
Okay, if that is the case, why have we only seen like 3-4 minor new QoL improvements in Spotify the last ~12 months, with no new grand features? And why haven't they fired 95% of their devs and let the remaining elite go buckwild with Claude?
Everyone here says "if developers are so much faster, why aren't we seeing more features?!" as if the only thing required to release a feature is developers.
My CEO keeps asking me "how can we go faster with AI", and my answer is "we can't, because even if we had developers that would instantly develop any feature perfectly, we'd still be bottlenecked on how slow we are at deciding what to actually release".
tbf they have been saying they've started doing this since December, so we're only a few months in. And like most software it's an iceberg: 99% of work on not observable by users, and in spotify's case listeners are only one of presumably dozens of different users. For all we know they are shipping massive improvements to eg billing
Because believe it or not, majority of users couldn't care less whether it is native or not. I don’t even see Spotify, it’s just something that lives in the background and plays music.
Strange subthread. I don't see Claude Opus 4.6 changing the tide for PyPy. There is no need to understate AI capabilities for this.
"Anthropic released vibe coded C compiler that doesn't work" sounds like https://github.com/anthropics/claudes-c-compiler/issues/1 passed through a game of telephone. The compiler has some wrong defaults that prevent it from straightforwardly building a "Hello, world!" like GCC and Clang. The compiler works:
> The 100,000-line compiler can build a bootable Linux 6.9 on x86, ARM, and RISC-V. It can also compile QEMU, FFmpeg, SQlite, postgres, redis, and has a 99% pass rate on most compiler test suites including the GCC torture test suite. It also passes the developer's ultimate litmus test: it can compile and run Doom.
This two week project did not displace GCC, one of the most complex pieces of machinery built by man, so the conclusion on hacker news is that AI is fake.
What you’re seeing is a shibboleth. If you can make the above claim without choking, then you’re a member of the tribe. If it seems so outlandish that honor and sense demand you point out the problems, you’re marked as an enemy.
The primary objective is to retarget PyPy on top of the Python main branch. A minor objective is to document what of PyPy can be ported to CPython (or RustPython).
Keep a markdown log of issues in order to cluster and close when fixed
Clone PyPy and CPython.
Review the PyPy codebase and docs.
Prepare a devcontainer.json for PyPy to more safely contain coding LLMs and simplify development
Review the backlog of PyPy issues.
Review the CPython whatsnew docs for each version of python (since and including 3.11).
What has changed in CPython since 3.11 which affects PyPy?
Study the differences between PyPy code and CPython code to understand how to optimize like PyPy.
Prepare an AGENTS.md for PyPy.
Prepare an agent skill for upgrading PyPy with these and other methods.
Write tests to verify that everything in PyPy works after updating it to be compatible with the Python main branch (or the latest stable release, CPython 3.14)
> Anthropic released vibe coded C compiler that doesn't work, how their LLM can help in maintaining PyPy?
This is the perfect question to highlight the major players. In my opinion, a rapidly developing language with a clear reference implementation, readily accessible specifications, and a vast number of easily runnable tests would make an ideal benchmark.
Yup.
For me the biggest signifier is Spotify. They claim their (best) devs don't even code anymore, they use an internal AI tool that they just send prompts to which then checks out a personal test build that they can download off of Slack. "A new feature in 10 minutes!"
Okay, if that is the case, why have we only seen like 3-4 minor new QoL improvements in Spotify the last ~12 months, with no new grand features? And why haven't they fired 95% of their devs and let the remaining elite go buckwild with Claude?
The Emperor really has no clothes.
Everyone here says "if developers are so much faster, why aren't we seeing more features?!" as if the only thing required to release a feature is developers.
My CEO keeps asking me "how can we go faster with AI", and my answer is "we can't, because even if we had developers that would instantly develop any feature perfectly, we'd still be bottlenecked on how slow we are at deciding what to actually release".
> They claim their (best) devs don't even code anymore
No, they claimed they didn’t code during a time period. Around year end until early this year. Technically they could have just been on leave.
Also best dev = principal / staff engineers. They rarely code anyway.
AI or no AI anyone could have made that claim.
tbf they have been saying they've started doing this since December, so we're only a few months in. And like most software it's an iceberg: 99% of work on not observable by users, and in spotify's case listeners are only one of presumably dozens of different users. For all we know they are shipping massive improvements to eg billing
> why have we only seen like 3-4 minor new QoL improvements
You are seeing improvements? From what I can tell, my user experience has only been going downhill over the past years - even pre-AI...
Also, why isn‘t there a native client for all platforms? Could they not just let the AI auto-translate the code?
Because believe it or not, majority of users couldn't care less whether it is native or not. I don’t even see Spotify, it’s just something that lives in the background and plays music.
Anthropic released vibe coded C compiler that doesn't work, how their LLM can help in maintaining PyPy?
Strange subthread. I don't see Claude Opus 4.6 changing the tide for PyPy. There is no need to understate AI capabilities for this.
"Anthropic released vibe coded C compiler that doesn't work" sounds like https://github.com/anthropics/claudes-c-compiler/issues/1 passed through a game of telephone. The compiler has some wrong defaults that prevent it from straightforwardly building a "Hello, world!" like GCC and Clang. The compiler works:
> The 100,000-line compiler can build a bootable Linux 6.9 on x86, ARM, and RISC-V. It can also compile QEMU, FFmpeg, SQlite, postgres, redis, and has a 99% pass rate on most compiler test suites including the GCC torture test suite. It also passes the developer's ultimate litmus test: it can compile and run Doom.
https://www.anthropic.com/engineering/building-c-compiler
This two week project did not displace GCC, one of the most complex pieces of machinery built by man, so the conclusion on hacker news is that AI is fake.
What you’re seeing is a shibboleth. If you can make the above claim without choking, then you’re a member of the tribe. If it seems so outlandish that honor and sense demand you point out the problems, you’re marked as an enemy.
Prompts for this?
The primary objective is to retarget PyPy on top of the Python main branch. A minor objective is to document what of PyPy can be ported to CPython (or RustPython).
Keep a markdown log of issues in order to cluster and close when fixed
Clone PyPy and CPython.
Review the PyPy codebase and docs.
Prepare a devcontainer.json for PyPy to more safely contain coding LLMs and simplify development
Review the backlog of PyPy issues.
Review the CPython whatsnew docs for each version of python (since and including 3.11).
What has changed in CPython since 3.11 which affects PyPy?
Study the differences between PyPy code and CPython code to understand how to optimize like PyPy.
Prepare an AGENTS.md for PyPy.
Prepare an agent skill for upgrading PyPy with these and other methods.
Write tests to verify that everything in PyPy works after updating it to be compatible with the Python main branch (or the latest stable release, CPython 3.14)
Strikes me as the worst possible solution if they're struggling to find maintainers in the first place. Who reviews the vibe coded patches?
> Anthropic released vibe coded C compiler that doesn't work, how their LLM can help in maintaining PyPy?
This is the perfect question to highlight the major players. In my opinion, a rapidly developing language with a clear reference implementation, readily accessible specifications, and a vast number of easily runnable tests would make an ideal benchmark.
Most maintainers don't have a stack of cash to throw at tokens.
They don’t need to throw a stack of cash at them, Anthropic and OpenAI have programs for open source maintainers.
https://claude.com/contact-sales/claude-for-oss https://openai.com/form/codex-for-oss/
I'd say they're less of "programs" as they are "six-month trials". What's the plan after six months?
And for what's it worth, PyPy isn't even eligible for the Claude trial because they have a meager 1700 stars on GitHub.
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Isn't the Claude one only for a few months?
(I haven't checked the OpenAI one, as I have no interest in them)
7 replies →
"You're completely right. That mushroom is poisonous."