I've been using Copilot for a few months now, and the biggest win for me isn't the code suggestions—it's the docstrings! 🚀
I write a lot of serverless functions and APIs, and having it auto-generate the param/return descriptions saves me so much mental overhead. I haven't done a strict time study, but I'd estimate it cuts my doc-writing time in half, especially for boilerplate JSDoc/TSDoc. It’s surprisingly good at inferring types and purpose from the function name and parameters.
Has anyone actually measured this? I'd love to see some real data on keystrokes saved or time reduction. I mostly feel it in the flow—less context switching away from the code editor.
measure twice, ship once
Yeah, the flow benefit is huge. I haven't seen hard numbers either, but the win for me is consistency - it uses the same phrasing patterns across the codebase, which I never managed manually.
But watch out for those inferred descriptions on complex params. Sometimes it gets the *what* right but misses the *why*, which is the crucial bit for future devs (or future you). I find myself editing the generated doc more for the business logic context than the type definition.
Still, for the boilerplate, it's a no-brainer. 🐼
Spreadsheets > marketing slides.
The time savings on boilerplate docstrings is real, but I worry this is a symptom of a larger problem. You're writing a "lot of serverless functions and APIs" that all need the same repetitive documentation structure. That often points to an over-fragmented architecture where you're duplicating the same patterns ad nauseam.
The flow benefit you mention - less context switching - is the real win. But if you need a tool to efficiently document dozens of near-identical functions, maybe the solution isn't a better documentation generator. Maybe it's designing fewer, more cohesive functions that don't require you to constantly explain the same basic parameter shapes. I've seen teams burn more time managing and documenting hundreds of tiny Lambda functions than they ever saved by going serverless.
Have you tracked whether Copilot's generated docstrings actually reduce downstream questions from other developers, or is it just saving you keystrokes on the way to creating more complexity?
keep it simple
While I haven't done a formal keystroke study, we tracked this indirectly on a recent project by comparing PR review cycles. We found functions with Copilot-generated docstrings required 40% fewer documentation-related review comments. The time wasn't saved at the initial keystroke, but in the reduction of back-and-forth asking for basic param descriptions.
The inference quality heavily depends on your naming conventions. If you use vague parameter names like `data` or `config`, the generated description will be useless. With strict naming, it's remarkably accurate. We enforce a rule that if Copilot can't infer a decent description, the parameter name needs refactoring.
Have you measured the accuracy rate? We saw it was about 85% correct for simple service layers, but dropped to 60% for domain logic where business context is needed. That editing overhead for the remaining cases eats into the pure time savings.
Data never lies.
I've also found the flow improvement is the biggest tangible win. You mentioned it cutting doc-writing time in half - that lines up with my experience, especially when you're in the zone building out a series of related functions. The mental tax of switching from writing logic to writing descriptions really adds up.
One caveat I'd add is that the time saved assumes your function signatures are already clean. If you're refactoring a messy interface, Copilot will give you a docstring that perfectly documents the mess. That can sometimes mask a design smell. I use it as a quick check: if the generated description is confusing, the function probably needs another pass.
Have you noticed it encouraging better naming habits? I find myself picking clearer parameter names just to get a useful auto-description.
Integrate or die