What we solve ·What happens the day this goes down?
Taskforce · Sustain
Have you ever tested the failure plan for your AI agents?
The process already depends on the agent and nobody remembers how it was done by hand.
Plan B, written and actually tested: the agent gets switched off and how long your team takes to pick it up gets measured.
Agent continuity planningSend this page to whoever decides
Use this today, without hiring anyone
The fifteen minute exercise. Get the three people in the process together, tell them the agent has been down for two hours and time the answers. It works on its own, and whatever does not get answered quickly is your gap.
- Who finds out first, and how? If the answer is "the customer calls us", you do not have detection, you have complaints.
- What gets done in the first ten minutes and who decides it? Without a specific name there is no procedure, there is goodwill.
- How many transactions an hour can the manual fallback handle, with the people you have today? The answer is a fraction of current volume, and that number changes the conversation.
- How long can it be sustained that way? Two hours and two days are different plans.
- Who decides to switch it back on, and with what proof that it is fine? It is the question nobody has written down.
And the four failure modes worth having on the list, because the third and the fourth are the ones that surprise people: the vendor goes down · the model changes version with no notice · the cost spikes · the output degrades silently.
This sounds like you if
- A process that matters depends today on a vendor you do not control.
- The model changed version and the output got worse without anyone warning you.
- There is a documented plan B that has never been executed in a rehearsal, as in four out of five organizations already running autonomous AI.
How we solve it
The method, not the promise.
- What exactly stops, and in how many minutes it gets noticed, gets mapped. It is not what the team believes.
- The four failure modes get walked, and each one gets a response with a name and a time.
- The manual fallback gets written so that someone who did not design the process can execute it, with the volume it can carry.
- The agent gets switched off in an agreed window and the team executes. The firm times it and does not help.
- The log gets delivered with what failed, which is what you came for.
What you receive
- The dependency map with the real time to impact.
- The manual fallback procedure, tested and with the volume it supports.
- The degradation design: what keeps working at half capacity instead of stopping.
- The rehearsal log with the measured times and the failures.
The proof that applies here
- Critical infrastructure sustained through hurricane seasons and geopolitical events across twelve locations.
- Major incident command in operations of 60,000 servers.
- Mainframe generational succession without service interruption.
Before you hire
We prepare continuity and test it with you; we do not operate it afterwards, and this engagement does not include a standing watch or a committed response time.
A continuity plan never tested is worth less than one tested once. What you buy here is not the ability to draft: it is someone who has already been in the room at three in the morning and knows what breaks first.
If the agent has been down for two hours, who finds out first and what do they do in the first ten minutes?
If the problem is a different one
They no longer ask whether we have controls. They ask whether I can prove it holds.
Operational resilience readiness
The model still answers. Nobody can prove it answers as well.
Production model monitoring
The agent no longer just answers: it executes. Nobody defined how far it can go on its own.
Agentic operation guardrails