"Not enough detail on the tickets"

If you've heard that before, you already know the trap. The moment teams try to fix ambiguity by writing more down, the real conversation stops – and misalignment quietly grows.

The usual response?
Write more down. More templates. More documentation.
But you can't scale clarity by writing more. More words create more ambiguity.

This session walks through the three failure patterns I've seen across various sectors: unclear tickets, tickets treated as facts, and organisations that optimise for documentation instead of understanding.

In one HealthTech platform, the term "Customer Type" meant something different to finance, marketing, and engineering – three definitions, multiple edge cases, and a mess of business rules nobody fully trusted.

You'll see why tickets are placeholders for conversations (not specifications), why requirements are hypotheses (not facts), and why executable examples in code and tests are the only spec that survives contact with reality – especially in a world where AI amplifies ambiguity.

If you've ever been stuck between vague tickets, late edge cases, or "just write it down properly", this talk shows what's actually going wrong – and the practical behaviours that turn it around.