Гангстер одним ударом расправился с туристом в Таиланде и попал на видео18:08
Returning back to the Anthropic compiler attempt: one of the steps that the agent failed was the one that was more strongly related to the idea of memorization of what is in the pretraining set: the assembler. With extensive documentation, I can’t see any way Claude Code (and, even more, GPT5.3-codex, which is in my experience, for complex stuff, more capable) could fail at producing a working assembler, since it is quite a mechanical process. This is, I think, in contradiction with the idea that LLMs are memorizing the whole training set and uncompress what they have seen. LLMs can memorize certain over-represented documents and code, but while they can extract such verbatim parts of the code if prompted to do so, they don’t have a copy of everything they saw during the training set, nor they spontaneously emit copies of already seen code, in their normal operation. We mostly ask LLMs to create work that requires assembling different knowledge they possess, and the result is normally something that uses known techniques and patterns, but that is new code, not constituting a copy of some pre-existing code.
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The resulting script is available here, and it worked first try to scrape up to 20,000 videos (the max limit). The resulting Python script has very Pythonic code quality following the copious rules provided by the AGENTS.md, and it’s more robust than my old script from 2021. It is most definitely not the type of output I encountered with Sonnet 4.5. There was a minor issue however: the logging is implemented naively such that the API key is leaked in the console. I added a rule to AGENTS.md but really this is the YouTube API’s fault for encouraging API keys as parameters in a GET request.