World Model Readiness What leaves the team unchecked

Module · What leaves the team unchecked

The Team Review Discipline Check

AI lets your team produce more than it can read. The risk is not that the work is bad, it is that nobody looked before it shipped. This module checks the five parts of a review habit that hold under volume: whether a gate exists at all, how deeply you sample, who is accountable, whether caught errors change the prompts, and whether scrutiny survives a deadline.

Question 1 of 5 · A review gate exists

Does AI-assisted work pass a human review before it leaves your team?

Not for everything, but for anything that reaches a customer, a system of record, or another team. If AI output can ship straight from the tool to the outside, the review gate is a preference, not a control.

Question 2 of 5 · Sampling is deep enough

When your team reviews AI work, does anyone actually check the substance?

Skimming for tone is not review. Real review checks the claim, the number, the citation, the code path. AI errors are confident and fluent, so a quick read is exactly what they survive.

Question 3 of 5 · A reviewer is accountable

When reviewed AI work turns out wrong, is it clear who signed off?

If the answer is 'the AI wrote it', nobody owns the output. A named reviewer who put their name on it is what turns review from a ritual into a responsibility.

Question 4 of 5 · Errors feed the prompts

When your team catches an AI mistake, does it change how you prompt next time?

A caught error is free training data. If it is fixed once and forgotten, the same mistake returns tomorrow. Teams that improve fold the fix back into the shared prompt or the checklist.

Question 5 of 5 · Scrutiny survives deadlines

When a deadline is tight, does review get done or get skipped?

The value of a review process is decided entirely on the bad day. If the first thing cut under pressure is the check, then you do not have a review discipline, you have a review preference.

For the statistics · one click each

Three questions for the public picture

These do not affect your score. They feed the anonymised, aggregated statistics; groups under 8 respondents are never shown.

What share of your team's outbound work is now AI-assisted?

Under 10 percent
10 to 40 percent
40 to 70 percent
Over 70 percent
We do not track it

How is AI work reviewed before it leaves your team today?

It is not
Ad hoc, if there is time
A norm, not a rule
A required gate
A risk-tiered gate

Has an AI error reached a customer or another team from yours?

Not that we know of
A near-miss, caught late
Yes, minor
Yes, serious
We would not know

Your context

Used to calibrate the report. Company size and sector remain in the anonymized dataset; your email does not.