What your AI ran, and what broke

The pilot worked. Nine months later it is still a pilot

Runs by type with their success rates, and a ledger of what failed beside them. The second half is what makes the first half worth reading.

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Throughput

Workflows

Schedules

AI Agents Team Dashboard

Continuity

The Challenge

The thing that impressed everybody in the demo is not running anywhere nine months later
You are shown how much automated work ran and never how much of it failed
Nobody can tell you which processes are actually running without you and which still need somebody watching
A job fails quietly at 3am and the first anybody knows is when a customer asks
Automated work gets described as headcount saved by people who never checked where those hours went

The Runwork Solution

Runs are counted by process type with their success rates, so volume never arrives without reliability beside it
A ledger of failed runs by resource, so an exception is a row you can open rather than a number in a footnote
What is running today is a list anybody in the workspace can open, which is a different thing from what was demonstrated in March
Work that ran outside working hours and while the owner was away, which is capacity that did not exist before
Capacity created is reported as capacity, never converted into headcount or into money, because nobody has observed where those hours went

What your team gets

Volume with its failure rate attached

How many runs, of what type, and how many did not finish. A throughput number without a failure number is the shape of a report built to reassure.

The exception ledger

What failed, on which resource, and when. It is a list to work through on a Monday rather than a percentage to feel bad about in a quarterly review.

Running, not demonstrated

The workflows and scheduled work executing this month, which is a different question from which pilot went well. Anybody in the workspace can open that list, not only you.

The 3am run nobody watched

Work that ran outside working hours, and work that ran while its owner was on leave. Nobody was at a keyboard for any of it.

Capacity, and only capacity

Freed hours are reported as capacity created. They are not converted into headcount and not turned into money, because whether that time got redeployed is something we cannot see and you can.

What is quietly going cold

Resources that used to run and have stopped, and processes whose failure rate is climbing. The report is built to show you those before somebody else finds them.

A Day in the Life

Monday. The number and its other half. You open the operations view and the run counts arrive with success rates attached. You have been handed throughput without failures before and you know what that report was for.

9:30 AM. The exception ledger. Four runs failed over the weekend, on two resources. That is a list to work through rather than a percentage to explain, and it is the first thing you look at rather than the appendix.

11:00 AM. Running versus demonstrated. Somebody asks how the AI programme is going. You open the list of what is actually executing this month. The pilots that impressed people in March are either on that list or they are not.

2:00 PM. Work that happened while nobody was there. Runs outside working hours, and runs while the person who built them was on leave. That is the difference between a process and a person with a habit.

3:30 PM. Something going cold. A scheduled job that used to run every day has not run for two weeks. Nobody reported it, because nobody was waiting for it. You find it here rather than from a customer.

And nothing was reported as headcount. Freed hours are capacity, on the page, in those words. Where that capacity went is a question about your operation rather than a number we are entitled to claim.

Frequently Asked Questions

Why is the failure data as prominent as the run counts?

Because a throughput number without a failure number is not an operations report, it is a marketing artefact, and you have seen several. Every report here carries a required section on what failed, what is missing and what is going wrong. It cannot be omitted for a good quarter, which is the only reason to believe it in a good quarter.

How do I tell a real process from a pilot that impressed people?

By whether it is running now. The workflows, scheduled work and agents executing this month are a list you can open, and so can anybody else in the workspace. A pilot that stopped in April is simply absent from it, which is a more useful answer than a status update saying it is going well.

Does this tell me how much faster the work gets done?

No, and we would rather say so than imply otherwise. There is no speed or latency measurement in any of this. What it reports is volume and reliability: how much ran, of what kind, and how much of it finished. If somebody shows you an AI speed figure, ask what it was measured against.

Can I turn capacity created into headcount?

Not from this. Freed hours are reported as capacity created and are deliberately never converted into roles or into money, because whether that time was redeployed into something valuable is not something the product can see. You can see it. We are not going to make the claim on your behalf and have you defend it later.

What happens when a run fails at three in the morning?

It is recorded as a failed run against the resource that failed, with its time, and it appears in the exception ledger rather than being averaged into a success rate. A workflow also retries a failed step three times on its own before it stops, so what reaches the ledger is what did not recover.

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