Answer.AI Essay Applies Naur's Theory Building to LLM Coding

An Answer.AI essay draws on Peter Naur's classic 'Programming as Theory Building' to argue that LLMs cannot truly simplify code because a program's essence is the theory held by engineers, not the code itself. It also warns that OpenAI and Anthropic increasingly hide data server-side, making abstraction layers over their APIs harder to build.

2026-08-19 ~ 2026-08-19 · 5 related posts

• Why LLMs can't make your code simpler, per Naur's "Programming as Theory Building" — math_rachel · 2026-08-19
• A program is the Theory in its builders' minds, not the code — math_rachel · 2026-08-19
• Abstractions simplify your Theory — until you debug beyond their contract — math_rachel · 2026-08-19
• OpenAI and Anthropic hide more data server-side, making abstraction layers brittle — math_rachel · 2026-08-19
• Simplifying theory pays off more than quick LLM code generation long-term — math_rachel · 2026-08-19