Most of the value in Feature Flags appears before anyone says done. The useful work is usually in the questions, the examples, and the evidence that changes the conversation.
When I review work in Feature Flags, I am not only asking whether the ticket appears complete. I am asking whether the evidence, code behavior, and surrounding assumptions fit together tightly enough that I would trust the result after release. The risk never stays theoretical for long, because the flag makes rollout safer at first, then months later nobody remembers which combinations still exist.
The review becomes useful when it tests the story behind the result, not just the result itself.
The First Signals I Look For
- Does the implementation clearly support targeting rules, fallback behavior, and keeping flags from becoming hidden complexity?
- Is the risky path visible, or has it been left to assumption?
- Would another reviewer understand the user impact without extra verbal explanation?
Questions I Ask Before I Call It Ready
I ask what changed outside the happy path, what happens under interruption, and how the team would know it failed in real use. With Feature Flags, those questions matter because a user sees a half-enabled experience because front-end and back-end flags diverge.
I also want to know whether the work can be explained to teams using gradual rollout to reduce release risk without hand-waving. If the answer needs too much translation, there is often still a hidden gap.
What Good Evidence Looks Like to Me
Good evidence is easy to point to and hard to misunderstand. For this topic I am looking for something like targeting rules, off-state proof, and a plan for cleanup after rollout.
I hold the review when the result depends on a promise nobody verified, when a negative path was skipped because it seemed unlikely, or when the notes only show activity instead of meaning. I keep the practice alive because it improves both release quality and team clarity at the same time.