The L in "LLM" Stands for Lying (acko.net)

Article summary

The article discusses the limitations and potential drawbacks of using Large Language Models (LLMs) in software development, arguing that they can produce low-quality, unoriginal code and undermine the value of human craftsmanship. The author suggests that LLMs are often used as a crutch, allowing developers to produce code without truly understanding the underlying problems or constraints. This can lead to a flood of mediocre code and a devaluation of the skills and expertise of human developers. The article also touches on the idea that LLMs can be seen as a form of forgery, producing code that is not truly original or authentic.

Main themes

• LLMs in software development
• Craftsmanship vs automation
• Code quality and authenticity
• Intellectual property and forgery
• Artisanal coding

What commenters say

• LLMs are useful for programming, but their output should be carefully reviewed and checked for errors and quality.
• The use of LLMs can lead to a devaluation of human skills and expertise in software development, as well as a flood of low-quality code.
• The concept of 'artisanal coding' may become more prominent as a reaction against the automated, industrialized approach to software development enabled by LLMs.
• LLMs are not a replacement for human judgment and expertise, and their output should not be trusted without careful evaluation and verification.
• The idea of treating LLM output as 'guilty until proven innocent' is not a viable solution, as it would require a fundamental shift in how we approach intellectual property and copyright law.
• The use of LLMs can be seen as a form of laziness, allowing developers to produce code without truly understanding the underlying problems or constraints.
• There is a need for more transparency and accountability in the use of LLMs, including clear attribution and sourcing of code and ideas.
• The value of code lies not just in its functionality, but also in its cultural and historical context, and LLMs may struggle to replicate this value.