| Hope this doesn't become a trend 'cause it can become very problematic.
Lots of newbies could replicate and this can produce waste of tokens as a first issue.
Also this creates additional problems, for example binding something new to a single AI vendor or tool (and also to an unpredictable model behind other than some pay subscription) is conceptually wrong. Nothing against AI obv, but we must start to address the use and abuse of it.
Some sorts of patterns in the usage, having a documentation or a readme as in this case is ugly and should be catalog under "anti-pattern". This is just an example, in a WIP project and okays, it's not a sin. But maybe we should start addressing, backed by big players an in big proportion by no profit foundation and academic (public and private) institutions, the problem of: How to use AI, what kind of things is useful doing with it and what not, how to evaluate that, in what stages of things can one have space to misuse this tool and in what not. This not much as a mandatory thing, but as a starting point for everyone approaching the use of AI as a building tool. A guideline. A market standard.
So that anybody can address at moment 0 landing on a repo, if it's compliant with some standard or not. Because have in mind, as a compass, what somebody investing some effort put into this field. Could be argued that common sense already addresses this very efficiently and that it's a matter of iteration and we all as a whole can build this common sense on ai use, but I think that having some credible org write it in a easy, accessible, verifiable, and used is a milestone toward it. And can accelerate the process with a small effort. Also can affect directly the various AI tools. Best practices, and concept, must be shared and easy to be access by everyone, as always have been in this field. |