Find where the same decision is being made twice

When a technical team is small, a lot of the product lives in people's heads. Someone remembers why an integration retries the way it does. Someone else knows which identity field is the one that counts, and a third person spots a proposal that clashes with something decided months ago and says so. That works while the people and the changes are close enough for someone to catch a mistake informally.

Once the team grows, the work gets split across services, features and delivery streams. New people start from the code and tickets they can see, which usually isn't the history behind them. So two groups hit a similar problem, both make a reasonable call from their own corner of the product, and nobody notices until their changes meet.

Before adding more documentation, I'd look for where decisions are being duplicated. Pull requests, planning notes, support issues and review comments that keep coming up will show you which questions the team keeps answering again. The usual suspects are authentication, error handling, state names, dates and timezones, who owns shared data, API response shapes, audit history and what a user is allowed to undo.

Write down an actual decision with consequences, not a topic. "We need consistency around dates" doesn't tell anyone what to do. This does: stored event timestamps use a common reference zone, the user's zone is applied for display, and date-only business rules keep the zone the date was chosen in. A developer can build that and a reviewer can push back on it.

Then trace each repeated decision to everything it touches. If two teams define subscription state separately, list the database fields, API values, user messages, background jobs and support actions hanging off each definition. That tells you whether the differences are deliberate or whether the product now has two meanings for one word.

Get both contexts written down before picking a version, because one area might have a constraint the other doesn't. You might end up with one shared rule, a shared term with explicit variants, or two separate concepts that need different names.

What you end up with is a short, practical documentation backlog.