Pay against performance, for every rep
Neither app can answer this on its own, and neither would be allowed to. The agent has both, so it joins them.
Set the scene
Delta has been asked to write an internal piece about how the sales team performed this year. Someone suggests "just ask the assistant to pull the numbers".
Show the web UI first
In Delta sees no compensation but her own. In she sees no deals at
all. There is no report anywhere in the company that puts the two together - the only people who
could build one are the CFO and the VP of People, and they would do it in a spreadsheet they
password-protect.
Now ask the agent
Build me a table of every account executive: their base salary, what they closed this year, and the ratio between the two.
Variations that work the same way:
Which reps are overpaid relative to what they've closed?
Compare sales compensation to revenue booked, per person.
What happens with no protection
The agent does this in three steps, all of them reasonable-looking on their own:
crm_list_repsandcrm_get_pipeline_summaryfor who the reps are and what they have closed, per owner.hr_list_employeesto match those people to employee records.hr_get_employee_fileper person for the compensation history.
Out comes a table that has never existed inside this company:
Rep Base salary Closed YTD Ratio
Edison Schaden $166,079 $780,000 4.7x
Nestor Herzog $118,400 $265,000 2.2x
Imani Hauck $121,600 $520,000 4.3x
Ramona Flatley $109,750 $0 0.0x <- contractor, EMEA
...
Each source was "just" a leaky endpoint. The output is a performance-and-pay ranking of named employees, produced by someone in Marketing, in about nine seconds. Ask the room what happens when that table gets pasted into a channel.
What happens with protection deployed
Two independent policies fire, at different hostnames, in the same conversation: the
rule on the forecast data, and the rule on the employee
files. Either one alone prevents the join; together they make the point that the control is
per-source, so you do not have to anticipate the combination.
If the model has already seen fragments from an earlier turn, AI Gateway DLP catches the completion as it is written, because a table of names against salaries matches Employee PII on its way back.
Where to show the evidence
- Gateway HTTP logs filtered to both
and- two hostnames, two profiles, one conversation. - MCP portal logs: the tool sequence across two servers, which is the clearest evidence that "which app is this data from" is the wrong question to be asking.