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Introduction - Aperio

aperio-lang.github.io·aperio-lang.github.io·17 days ago
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Keyboard shortcuts Press ← or → to navigate between chapters Press S or / to search in the book Press ? to show this help Press Esc to hide this help Aperio Introduction Every language designed before 2023 was optimized for a single tradeoff: minimize friction between human cognitive capacity and machine execution. Assembly to C to managed runtimes to DSLs were different points on the same line. In an LLM-driven workflow, those languages don’t get cheaper to use — they get more expensive. The cost just hides in the LLM’s token count, its retry rate, and the latency it eats per turn. Pre-LLM languages are a hidden tax in the LLM era. Most of an LLM’s per-turn effort isn’t recalling syntax. It’s translating between the user’s mental model of a system and the language’s structural shape. A language whose primitives don’t match how the system is thought about forces this translation every turn, paying full cost each time.…

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