Your AI work throughput

Work your team set up months ago is in one of two states. It is still running, or it stopped and nobody noticed. Most dashboards only draw the first kind, because a chart of things that worked looks better than a chart with a gap in it.

This counts both. Scheduled jobs, the apps your team built, and what they produced over thirty days rather than today. Thirty days matters: a single day tells you whether Tuesday was busy, not whether the thing you set up in March is still running.

Then it counts what failed. Scheduled job success is the number that stops a thing that broke three weeks ago from staying invisible for a fourth. You find out from a page instead of from a customer.

And it counts people honestly. Active members, inactive members, total active days. The second number is the useful one and it is the one most tools leave out, because a dashboard that shows you who stopped is harder to sell than one that shows you who started.

The part worth showing your manager is the work that ran while nobody was at a keyboard: runs outside working hours, runs while the owner was away, and the longest unbroken streak of automated work. Schedule attainment sits next to it, so you know how many of the runs that were supposed to happen actually did. A day-by-hour map shows when work happens across the week, with the change against the prior period. All of it prints to a PDF, computed from the audit log with no AI in the path, so it prints the same twice.