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I’m exploring how to leverage GSD (Get Shit Done) within Cursor to structure AI-assisted development more systematically.
For those already using it in production:
What does a robust GSD + Cursor workflow look like in practice?
How do you structure specs, tasks, and iterations to maximize LLM efficiency while minimizing context drift?
Do you maintain a distinct GSD planning layer alongside the codebase, or integrate it directly into the repository structure?
If introducing GSD mid-project, how would you retrofit it without slowing down delivery?
Is there a recommended migration strategy (e.g., progressive feature adoption, spec backfilling, or parallel planning layer)?
Appreciate insights from teams applying this beyond experimental use.
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Hi,
I’m exploring how to leverage GSD (Get Shit Done) within Cursor to structure AI-assisted development more systematically.
For those already using it in production:
Appreciate insights from teams applying this beyond experimental use.
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