Researchers want to kill the vibe, propose better model for AI coding

A pair of MIT researchers have detailed a proposed new model for software that would help both humans and AI code generators alike create better and more transparent applications. No more vibing!

The approach is detailed in a paper authored by MIT’s Eagon Meng and Daniel Jackson, titled "What You See is What it Does: A Structural Patten for Legible Software". They flag up the problem of “illegible” modern software, which lacks "direct correspondence between code and observed behavior".

Modern software is often, also, "insufficiently modular" they continue, "leading to a failure of three key requirements of robust coding": incrementality, integrity, and transparency.

These are not purely human flaws. In fact, they argue that the growing use of LLMs has "exposed deep flaws in the practice of software development, and how a reevaluation might be needed to capitalize on the benefits of LLMs and mitigate their failings."

When LLMs ...