I stopped asking my team to use AI. I asked them to manage it

Dan Graves, chief product officer at WitnessAI, has seven people on his team manage AI agents like junior hires, with a person approving work before it moves on.

Dan Graves, chief product officer at the company WitnessAI, stopped asking his product team to use AI to do their own jobs faster. He asked them instead to manage AI agents like junior employees: train them, set expectations, review their plans and own the quality of what they produce. In a column for the business-technology magazine CIO, he describes how seven people on his team work this way and what went wrong along the way.

• Each person works with a primary agent for their role. A design agent turns designers' Figma mockups into working code, a frontend engineering agent reviews that code, and an orchestrating agent routes each ticket to the right agent.
• A person approves work before it moves forward, and no agent opens a pull request, a proposed code change, without a human sign-off.
• Early designs from the design agent used the wrong components, and developers reworked half of them. Once the engineering agent was loaded with frontend practices and reviewed the design agent's work first, the frontend team accepted roughly 95 percent.
• When a designer picked a task from a list only to point the design agent at it, the agent started building. It now asks clarifying questions first and builds nothing without an explicit go-ahead.

When each person manages an agent, much of the review work moves into the rules and checklists the agents follow. The account is one executive's report on his own team, and applying it elsewhere is an inference.

Derived by Working Surface from the article. Source line: The net effect is we all end up acting more like product owners, not just holders of one job title.

26 September 2026: when agents can finish whole tasks, teams redesign the work, the checks and the roles around them.