Run AI Workflows in Several Steps, With a Person Approving
The short answer
An AI workflow with several steps splits a job into stages, like gathering information, drafting, checking and sending, with a separate AI step for each. A person approves at the points where a mistake would cost you: before anything reaches a customer, changes a record or spends money.
The problem
The jobs worth handing to AI are rarely one step. Answering a new client request might mean reading their message, looking them up, checking your capacity, drafting a proposal and sending it. A single AI prompt that tries to do all of that is hard to trust. When it gets something wrong, you can’t tell where, and you can’t fix one part without breaking another.
So most businesses end up in one of two places. Either the AI only does tiny, safe tasks, or someone wires up a big automation that runs unchecked until it does something embarrassing. Neither one gets you real help on the work that eats your week.
How it works
- We map the job step by step with the people who do it now, and mark where judgment or risk lives.
- Each step gets its own AI worker with a narrow job and only the access it needs: one gathers information, one drafts, one checks the draft against your rules.
- Approvals go at the risky points. The workflow pauses and sends a person a clear summary in Slack or Teams with Approve, Edit and Reject options.
- Approved work moves to the next step. Rejected work goes back with the person’s notes, or stops.
- If a step fails, the workflow stops there and tells a person.
Human checkpoints
In this example, AI does the work and people approve before anything goes out or changes.
- Anything customers see is approved. Emails, proposals, quotes and replies wait for a yes.
- Anything that changes your data is approved. Record updates, status changes and deletions get checked.
- Anything involving money or commitments is approved. Prices, discounts, deadlines and promises stay human.
- Approvals come off one at a time. When a step has a long, clean record, you can choose to let it run on its own. Some steps never should, and we’ll tell you which.
What it doesn’t do
It doesn’t remove the need for someone who understands the work. If nobody on your team can tell a good draft from a bad one, approvals become rubber stamps. It’s also overkill for simple tasks with only one step. And it won’t fix a process that’s broken to begin with; if the steps don’t make sense on paper, automating them just makes the confusion faster.
Illustrative outcome
Picture an accounting practice handling new client inquiries. AI reads each inquiry, pulls any history, drafts a tailored reply and an engagement checklist, and checks both against the firm’s rules. A partner approves the reply in Slack in a minute or two, and the checklist lands in the project tool.
