Grace Hopper's Revenge

4 hours ago

Kernighan’s Law highlights the difficulty of debugging overly clever code, emphasizing simplicity.
LLMs perform better with functional programming languages like Elixir, which have clear, immutable structures, compared to Python or JavaScript.
Tesla and Figure’s approach to robotics and autonomous vehicles focuses on human-centric design, leveraging existing infrastructure.
The future of software engineering involves LLMs writing code while humans focus on verification and high-level specifications.
Functional programming languages like Elixir and Racket are better suited for LLMs due to their explicit semantics and locality.
The importance of language design is underscored by how well LLMs can generate and verify code in functional paradigms.
Grace Hopper’s vision of translating English directly to machine code is becoming feasible with modern LLMs.
The shift towards machine-generated code requires clear contracts, explicit effects, and composable pieces for effective verification.

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