> > Homoiconicity and the AST It's a purely theoretical and speculative advantage as of now. Human lisper think in AST, that's something powerful, and it's rea

> > Homoiconicity and the AST It's a purely theoretical and speculative advantage as of now. Human lisper think in AST, that's something powerful, and it's reasonable to assume an AI could too, with benefits. But LLMs simply don't; not only they will occasionally mismatch parens, but they will dig themselves in a pit when asked to fix it. Stronger models miss far fewer parens, but that's most likely that they adapt better, not that they think in s expressions ASTs. But we could totally imagine transformer producing directly ASTs, and lisp is probably the best first target for that. I've found macros and live programming to be much of the same: it'll do it when asked to, but is not particularly natural or apt at it. They can use macros well, but will rarely choose to write the correct macro when needed. Live programming feel particularly ill-suited: multiplying small request with an accumulating context sounds like a sure fire way to explode your token budget. It does wonder for humans because we're able to compress our "context" on the fly. Context caching may mitigate all or most of it, but then it make compressing context less worthwhile. As much as I dislike it, LLMs are punch-card programs suited punch-card programming (write/read all in one go, then compile and execute); his entire training set is arguably punchcard, even from live programming languages. > shouldn't we have the LLM generate Erlang? Unironically a good idea