A naive AI doc writer comments on every PR. Some comments are useful. Most are noise. The team starts ignoring them. Three months later the writer is disabled and the docs are stale again.
The lesson isn't that PR-triggered writers don't work. It's that most of the value is in what the tool doesn't do. Knowing when to stay quiet is the harder problem.
Cases where a doc update is warranted
A PR clearly affects docs when:
- The diff adds, removes, or renames a user-facing endpoint or parameter.
- The diff changes a default value that is documented.
- The diff updates an install command, an env var, or a dependency that appears in setup docs.
- The diff modifies behavior that is described in a tutorial or guide.
These are the high-signal cases. The model can identify them with high confidence, and the proposed update is usually narrow.
Cases where the writer should stay quiet
A PR doesn't warrant a doc update when:
- The change is internal: a refactor, a test, a build script, a comment.
- The change touches code that isn't surfaced in the docs.
- The change is a version bump of a dependency that doesn't appear in setup instructions.
- The change is a copy edit to an error message that isn't documented.
- The diff is too small to be confident about what changed.
A writer that proposes a change on every internal refactor will train the team to ignore the comment.
The gray area
Some PRs are ambiguous. A change to error handling might affect docs, or it might not. A new optional parameter might be worth documenting, or it might be too niche.
A reasonable default is to propose conservatively in the gray area. A draft that includes a note like "this might be relevant to the error handling page" gives the reviewer a chance to weigh in without forcing a yes-or-no decision. The model says "I think this is in scope; you decide."
Proposing aggressively in the gray area is worse. False positives compound. Quiet weeks build trust faster than busy weeks.
How to think about silence
The absence of a comment is also a signal. If the writer comments on 10% of PRs and 90% of those comments turn into doc updates, the workflow is calibrated. If the writer comments on 80% of PRs, almost half of which get rejected, the signal is gone.
Treat the comment rate as something to tune over time. Most teams will want to start strict, with only the high-confidence cases, and loosen up as they build trust in the system.
What this means for setup
When choosing an AI writer, ask:
- How often does it comment on a typical PR stream?
- What categories of change does it consider in scope?
- Can the threshold be adjusted?
A tool that comments on everything isn't actually doing the work. The work is the filtering.
ReadMe's AI Writer is tuned to stay quiet on PRs that don't affect docs. When nothing in the diff matches an existing page or warrants a new one, no comment goes out. When something is in scope, the draft lands on a review branch and gets checked by the Linter before anyone has to look at it. The signal stays clean, the team keeps paying attention to the comments that do show up, and the review workflow closes the loop. For more on how the AI Writer fits with the rest of our AI tooling, see Introducing GitHub AI Writer.
