Not that long ago, you could open a GitHub project, read the source code, and get a pretty good idea of the intellectual effort behind it. The programmer(s) wrote the code, made the design decisions, handled the edge cases, and the source code reflected the work and effort. As the saying goes: the source code does not lie . In 2026, that is changing. With Codex, Claude Code, Cursor, and similar tools, developers increasingly express their decisions through prompts while AI writes much of the actual code. So I was thinking about building a project called PromptSourceCode . The idea is simple: automatically maintain a PROMPT_SOURCE.md containing the chronological interaction between the developer and the AI, including prompts, files/images provided, model information, git state and other useful context. My thought is that this is becoming another form of source code. The generated programing language code shows the final result, while the prompt history shows much more of the human intent, architecture, constraints, corrections, and decisions that produced it. Would you find something like this useful in a GitHub repository, or is it just glorified logging? The main challenge I’m facing is integration with the vast variety of harness: Claude Code CLI, Claude Code Desktop, Codex CLI, Codex Desktop, Antigravity, PI, OpenModel, etc. That’s a tall order to build, even with AI. What do you think? Would people care to read the actual prompt source code of the project? Maybe they wouldn’t care to read, but they could definitely use it to create their own version of the project. submitted by /u/niosurfer
Originally posted by u/niosurfer on r/ArtificialInteligence
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