Also, slop code is not open source. It's not source, it's a build artifact. The prompt is the source. But we don't have a deterministic build system for it so publishing the prompt isn't even useful.
a deterministic build system for prompts is a called a compiler.
The value is in how you came to the design you expressed.
What's the value of getting all my prompts if the rest of the equation is unknowable? Unless you mean the value is in the full agent log, but even then, frontier models and harnesses would still be hiding a major part of the equation from us.
when devs work in isolation, that context/memory is siloed. Same is true when working across platforms (codex, claude, etc).
Before AI we had prompts called "requirements" and of course they were the starting point for reviewing code: the customer needs X, the code doing that is Y.
With agents that prompt became much longer, with the original requirement a short note at the beginning of the conversation with the AI, but the resulting code is about the same size. Maybe in YOLO development the original requirement is all the AI needs but I'll be surprised because requirements from customers are too fuzzy and can be turned into very different features, often too different from what the customers had in mind.
Actually I never looked at the detailed prompts of coworkers, only at the original requirements from customers. How they instructed their agents is not particularly interesting except maybe to get a gist of the different approaches.