Reviewing AI Code Is Not A Viable Argument

Summary

Reviewing AI Code Is Not A Viable Argument I am a skeptic of the utility of LLM in software development. It is not because of IP laws problems (even if they are highly problematic), nor is it for ecological and ressource comsumptions reasons. It is not even for “they are all crap” reasons. My problem with LLM Coding Assistants is that I cannot see, in the face of the scientific evidence, how they can help someone write code better or faster. And the thing that irritate me is that it seems that none of the proponents of LLM Coding Assistants seems to ever address this problem and this evidence when they defend their tooling choices. Worse, it seems that they give fuel to my arguments everytime they write a rebuke of the skeptics. So let’s look at what I have a problem with, how empirical scientific research support that view, how proponents of LLM Coding Assistants could show this is not a problem and then how right now they are doing the actual opposite. Note: This piece was written nearly a year ago, hence why you may find vocabulary, like “Coding Assistants” that has been mostly replaced at this point. Sadly, I have not been able to find a term in the current vocabulary around genAI used to code that covers all the use case. So I kept the “Coding Assistants” wording. The Intern Problem The fundamental problem of LLM Coding Assistants that my criticism center on is their relatively high risk of getting things wrong. For all kind of reasons, some structural to how LLM works and other more akin to the interfaces we provide to interact with them, LLM Coding Assistants get things wrong. It can be hallucinations, typos, simply doing something that is not linked to the task demanded, going into a different path, etc etc. A lot of people I have talked about that experimented with LLM Coding Assistants explains that they feel “Like an intern”. Like an intern, you should not expect too much from them, you should expect that everything they do will be more or less wrong, and...