A demo proves possibility, not operation
A prototype can run against selected inputs and perfect access. Production sees missing fields, contradictory records, expired logins, repeated events, and people who do not use the output.
Moving from demo to production means designing for those ordinary failures.
The data is not ready just because it exists
Company data can be present and still unusable: no stable identity, no current source, no ownership, and no path for resolving disagreements.
AI makes those gaps scale faster. The context and source hierarchy have to be designed before automation is trusted.
No owner means silent decay
Every system needs a person who owns approvals, exceptions, source changes, and the decision to widen authority.
If that person is not named before launch, the system becomes another abandoned tool with impressive screenshots.
No acceptance test means endless revision
“Make it better” is not a production test. The team needs named cases, thresholds, human-review conditions, and explicit failure behavior.
A passing system can still improve. A system with no definition of done can never finish.