A billing provider retires an interface nine weeks into a migration. The AI team has the announcement, the old documentation and a plan built around the old interface. The team then has to work out which of its decisions the announcement overturns.
When evidence like this arrives, the work that rested on the old assumption should change and everything else should stand. In this migration, the invoice writer and the backfill change, while the completed account transfer and the search index stay useful. In our September study, agents that kept their information but left dependent decisions unrevised made 22 violations per thousand decisions, against 6 for agents that revised them.
What a durable team keeps
A durable team can explain why it made an earlier decision without still acting on a retired assumption, and it can leave a question open while it investigates.
Interruptions test this most directly. A team that stops mid-task should resume with its commitments intact and know which of its last actions took effect. In the same study, agents ran a median 109.6 hours before a person had to rebuild their work, against 7.4 hours without durability.
The approach works with hosted and open models alike, and it gives a team one shared basis for its decisions, even as its members change.