I welcome issues, discussions, and pull requests. If you've run into Web streams problems I haven't covered, or if you see gaps in this approach, let me know. But again, the idea here is not to say "Let's all use this shiny new object!"; it is to kick off a discussion that looks beyond the current status quo of Web Streams and returns back to first principles.
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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Murray played in several semi-successful prog-rock and jazz fusion bands during the late 1960s and early 70s.
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dynamically-sized stack frames. All Go stack frames are constant