Your Next Move #05 — What to Say When Your Direct Report Brings You an AI Solution You Don't Fully Understand
Exact script + 5-question checklist for the moment a direct report brings you an AI tool/build you don't fully understand
The moment usually looks like this.
Your senior IC — the one you trust, the one who's been carrying the weight on the team's hardest workflow — slacks you: "Hey, got 15? I built something."
You sit down. They share their screen. There's a notebook open, or a custom GPT, or a no-code workflow with seven AI nodes wired through it. They start walking you through it, and somewhere around minute three you realize: you do not actually understand what this thing is doing.
You understand the outcome they're claiming — "it cuts our weekly reporting prep from six hours to forty minutes." You understand that they're proud of it, and they should be. What you do not understand is the engine.
This is the moment most managers either rubber-stamp it ("amazing, ship it") or shut it down ("let's run this past IT first") — and both are mistakes that cost you authority either way. The rubber-stamp turns you into a mascot, not a manager. The shut-down trains your best people to stop bringing you their AI work and route around you.
Here's the exact script and the five-question checklist that lets you stay the manager in the room without faking competence you don't have.
The opening line that buys you back authority
The instinct is to fake understanding. The career move is to name the gap honestly — but frame the next move, not the gap.
Say this:
"Walk me through it one more time, but slower. I'm going to ask the boring questions on purpose. I need to be able to defend this when someone two levels up asks."
What that one sentence does:
It legitimizes your slowness. You're not catching up; you're stress-testing for them.
It positions you as their cover. You're not the bottleneck; you're the shield between their build and the next round of scrutiny.
It signals the questions are coming. They get to prepare, not be ambushed.
Now you've earned the right to ask the five questions every direct-report-built AI thing must survive before you put your name on it.
The 5 questions every AI build must survive
These are not technical questions. You don't need to know what a vector embedding is. You need to know what breaks, who owns it, and what happens when it's wrong.
1. "What's the worst output it could produce, and how would we know."
This is the most important question, and the one almost no one asks. If your direct report says "it can't really produce a bad output" — that's a red flag. Every LLM-driven workflow has a failure mode. The good builders have already thought about it. Make them name one.
2. "Who is going to maintain this when you go on PTO."
