Capturing the prompt is probably a good idea. But if I think about the goal of "reproducible builds" and "supply chain security," the use of LLMs in a vibe-coding mode looks like a step backward.
Ultimately the code needs to stand alone, but if you discover that a specific version of an LLM produced vulnerable code, you have no recourse but to try again and read the generated code more carefully. And reading code carefully is the opposite of vibe-coding.
When dealing with prompts, there is no such thing as reproducible builds, since we are dealing with a non-deterministic system. The purpose for connecting prompts and conversation to code is to aid in debugging and developing new features. I also believe by connecting code to conversations, we will produce better LLMs in the future.
I would say AI has generated about 98% of my code for my chat app in the last 3 months and it was definitely not vibe coding. Every function and feature was discussed in detail and some conversations took over a week.
My reasoning for building my chat app wasn't to support vibe coding, but rather to 10x senior developers. Once you know how things work, the biggest bottleneck to a senior developers productivity is typing and documentation. The speed at which LLMs can produce code and documentation cannot be matched by humans.
The only downside is, LLM don't necessary produce pretty or more readable code. The more readable code is something I would like to tackle in the future, as I believe post-processing tools can make LLM code much more readable.
Ultimately the code needs to stand alone, but if you discover that a specific version of an LLM produced vulnerable code, you have no recourse but to try again and read the generated code more carefully. And reading code carefully is the opposite of vibe-coding.