For support leaders

From running the queue to running the agent operation.

You used to run a queue. Now the queue includes an AI agent that handles half the volume, escalates the rest to your team, and reports to a vendor CSM who doesn't sit in your one-on-ones. You're already managing the operation. Nobody updated your job description.

Sound familiar?
"I run weekly QA on the team. I have no equivalent for the AI. When my team's escalations spike, I can't tell if the AI is sending more or if my team is getting worse."
"Onboarding a new hire takes me three weeks because I'm rebuilding the doc every time. The AI's system prompt is somewhere I don't have access to."
"When the AI gets something wrong, I'm the one fielding the escalation. I'm not the one who can fix it."
"My manager asks how the team is doing. I don't have a single answer that includes what the AI is doing."
"Half my job now is reading what the AI sent and deciding whether the team should answer the customer differently. Nobody has a name for that work."

The work you do has a name. It's running an agent operation.

You weren't taught the discipline. You learned it by doing it. You built a QA scorecard because the team needed feedback. You wrote an onboarding doc because the next hire was starting Monday. You made a contact reason taxonomy because nobody else would. Now you're also reading the AI's outputs, fielding escalations the AI created, and telling your team when to override an AI decision.

You're running an agent operation. The team is half of it. The AI is the other half. Nobody handed you the framework for what holds across both. That framework is seven functions. Here is what your week already looks like, mapped to it.

Perform
Weekly QA reviews. Spotting AI replies that went off-tone. Calibration with the team lead.
already doing it
Build
Cleaning up Zendesk macros. Adding routing rules when a new product ships. Flagging AI prompt issues to the vendor or your CX lead.
already doing it
Enable
Onboarding the new hire. Updating the KB. Training the team on when to override the AI.
already doing it
Measure
Pulling CSAT, FRT, AHT for the team. Asking the vendor for AI numbers. Reconciling them when your manager asks.
already doing it
Improve
Writing the escalation policy after the bad week. Catching process drift on the team and the AI. Updating the SOP nobody reads.
already doing it
Know
Tagging contact reasons. Spotting the new pattern in the queue, on either side. Telling product what customers are asking about.
already doing it
Grow
Building the case for the next hire. Writing the JD at midnight. Calling what should stay human and what should expand to the AI.
already doing it

You are running the seven functions across humans and an AI. Right now they live in your inbox, your Notion, your spreadsheet, the AI vendor's dashboard, and your head. Haven is what they look like when they live somewhere they can compound.

What changes with Haven

Same work. The operation gets to keep it. Across both populations.

Without Haven

Your QA scorecard lives in a Google Sheet for the team. The AI's performance lives in the vendor dashboard. You tweak both quarterly. You can't tell if quality is improving across the operation, or just on one side.

With Haven

One scorecard, both populations. Calibration is structured. Trends are visible across humans and AI. Coaching and prompt updates are backed by the same data.

Without Haven

When an agent leaves, the team's playbook leaves with them. The AI's prompt lives somewhere you don't have access to. The next person rebuilds half from scratch. You answer questions you answered six months ago.

With Haven

The standard lives in Haven, written down. The team is calibrated to it. The AI is built on it. Nothing gets lost when people change. The operation grows with you.

You don't have to own the budget to use this.

Most support leaders don't sign software contracts. They get assigned tools and asked to make them work. Haven runs differently. The diagnostic is free, takes five minutes, and scores your operation across all seven functions, both populations included. No signup required to start.

Take the result to your one-on-one. Now you have language.

In your next one-on-one

State it. Then name the exposure.

"We handled 8,400 tickets last month. 5,200 by the AI, 3,200 by the team. I cannot tell you which ones we handled well, on either side. When the next exec-level escalation lands, we will be defending decisions across two systems we cannot trace. I want to fix that before it happens, not after."

That is a different conversation than "we need better QA."

What the diagnostic gives you: a clear picture of where your operation is weakest across humans and AI both, a ranked list of what to fix first, and the language to put a number and a risk next to it. Evidence, not opinion.

See where your operation actually stands.

Five minutes. Seven functions. A maturity profile and a ranked list of what to fix first. Bring it to your next one-on-one.

Start the diagnostic Join the waitlist