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Comment by somnium_sn | Hacker News Reader

I am still a bit surprised that this is not more widely used. Normal inference + tool calls is effectively composition via serialized natural language, whereas Code Mode / Programmatic Tool Calling is using purpose built languages (aka programming languages) for composition and concurrency. It somewhat feels obvious to me that the latter is way more token and latency efficient.

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In the world of AI hype, everything is to be learned again and we are going to see many many breakthroughs like this. You can see this shift already in the tone of conversation in HN for example.

The basics of computer engineering is now novel approaches. We are discovering why programming languages exist, starting with a worst version of Cobal running on a very expensive and probabilistic VM.

We will shoehorn every square, rectangular, and all forms of peg through the AI hole.

"You know, as impressive as these systems are, they sure are bafflingly stupid. I am wondering if perhaps there is more to human intelligence than technical mastery of human language."

Drew McDermott, 1976, "Artificial Intelligence Meets Natural Stupidity": https://dl.acm.org/doi/10.1145/1045339.1045340

  I wish to rail against a pervasive sloppiness in our thinking, the tendency to see in natural language a natural source of problems and solutions. Many researchers tend to talk as if an internal knowledge representation ought to be closely related to the "corresponding" English sentences; and that operations on the structure should resemble human conversation or "word problems". Because the fault here is a disregard for logic, it will be hard for my criticism to be logical and clear.

Note that 1976 had some cool AI, including theorem-provers and story-tellers (Knuth wrote a story-telling program, I think it's an exercise in TAoCP). Yet the underlying theory of intelligence was "intelligence is logical processing of symbolic information"; this is obviously inadequate, but the ideology of analytic philosophy is a helluva drug for a scientist. Likewise with the 21st century "intelligence is about correctly predicting things based on past information,"; this is obviously inadequate, but the ideology of big data technocracy is a helluva drug for a scientist.

to be fair, people are also discovering why vaccines, democracy and human decency are desirable traits; so it's not just programming in the age of LLMs.

There's clearly a paradox that happens when people have to face things they treat as essentially magic because the magic has wiped away the pain and suffering that borne them. So too will be another age when people have to relearn everything the LLMs do for us.

TFA suggests that it already is:

> The one-line takeaway

> This already ships by default in every claude/codex/opencode session's system prompt

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