I ran a little experiment for the same feature with two different PRDs.
- PRD A: I fed ChatGPT some context and asked it to "write the PRD." → Estimated implementation time: 57 eng days.
- PRD B: I used Wisary in Confluence, which interrogated me with questions, forced me to slow down, and think more thoroughly → Estimated implementation time: 818 eng days.
At first glance, 818 days feels like "bad news." But in reality, it's the first time the full scope of work became visible.
What inflated the estimate?
- Security, reliability, performance
- Integrations, auth, permissions, audit logs
- Metrics, rollback, observability, supportability
- Testing, release strategy, change management
A lightweight PRD skips these decisions, making things look fast. Until launch time exposes the gaps.
👉 The real lesson: engineers don't underestimate because they're bad at estimating. They underestimate because the scope isn't visible.
Estimates are an output of clarity.
A rigorous PRD slows you down just enough to go faster, because once the work is visible, you can actually decompose, challenge, and right-size it.
Question for this group:
How do you balance the need for speed in writing requirements with the discipline needed to make hidden scope visible early?
