[folkrav]

My latest feature was an overarching change across 4 different stacks, about a full work day of going back and forth iterating on different designs, generating workarounds for stack/language specific quirks and the business' usage patterns. Multiple fresh agent sessions, review passes, exploratory work with subagents, etc. "The prompt(s) that generated the change" in that context is multiple hours of discussion, Q&A, refactoring and feedback. Is that really the value, pages and pages of reactive prompting?

[jaxn]

Yes. Because that is where the intent is/was. In the future, as more changes are made, having the history of the intent is helpful context. And in that back and forth there are also details of what you didn't want, and why. Some of that can be captured in decision docs, etc.

when devs work in isolation, that context/memory is siloed. Same is true when working across platforms (codex, claude, etc).

[lstodd]

Yes.

The value is in how you came to the design you expressed.

[folkrav]

What puzzles me is, what matters is context. Most of the context would be the specific model I used and its training data, the result of tool calls, and the model's inner monologue/thinking (which is increasingly getting encrypted by frontier models). My prompts are a tiny sliver of that, and most of them dependended on the actual answers I was getting from the model in the middle of the whole process. Or the result of handoffs, or internal compactions.

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.

[zeroimpl]

Wouldn’t the same argument apply even if they didn’t use AI? Being able to drill into coworkers minds would be nice on many occasions.