AI coding philosophy
Introduction Since I started using AI for development, I've immediately noticed several problems along with the many benefits. This is especially true when projects aren't simple standalone or disp...

Source: DEV Community
Introduction Since I started using AI for development, I've immediately noticed several problems along with the many benefits. This is especially true when projects aren't simple standalone or disposable tools. If you develop complex projects with dozens of modules and/or services that interact with each other, you'll quickly notice code redundancy and unwanted repetition. It's a bit like going back to the mythical days of copy and paste. Of course, the code implementation is good (it depends a lot on the model you use). Another very important aspect is that for very complex projects, the context becomes so large that everything slows down and the model tends to forget where we started. To summarize Duplicate or unoptimized code As the code grows, the model "forgets" and tends to hallucinate Changing models results in different implementations that often don't follow the rules. The costs of cloud-based models are increasing exponentially. To solve these problems, I've tried to find a w