[HN] LLMs audit code from the same blind spot they wrote it from. Here's the fix

Summary

A high school teacher with no software engineering background built a large TypeScript application entirely with AI assistance. They discovered that the AI models used for generation consistently missed the same categories of bugs when auditing the code, highlighting a significant "blind spot." The teacher claims to have found a fix for this auditing limitation, which could improve AI's ability to review its own generated code.

Continue Reading

Explore related coverage about community news and adjacent AI developments: [r/ML] [D] MYTHOS-INVERSION STRUCTURAL AUDIT, [r/LocalLLaMA] karpathy / autoresearch, [r/ML] [R] Agentic AI and Occupational Displacement: A Multi-Regional Task Exposure Analysis (236 occupations, 5 US metros), [r/ML] Building behavioural response models of public figures using Brain scan data (Predict their next move using psychological modelling) [P].

Related Articles

• [r/ML] [D] MYTHOS-INVERSION STRUCTURAL AUDIT

  March 29, 2026

• [r/LocalLLaMA] karpathy / autoresearch

  March 10, 2026

• [r/ML] [R] Agentic AI and Occupational Displacement: A Multi-Regional Task Exposure Analysis (236 occupations, 5 US metros)

  April 7, 2026

• [r/ML] Building behavioural response models of public figures using Brain scan data (Predict their next move using psychological modelling) [P]

  April 5, 2026