On August 26, 2026, I am an hour into an AI lunch-and-learn for a product company with a few dozen people. They sent me 16 questions ahead of time, and I am working through them in order. Question 10 is the one every team gets to eventually: how do we make sure the output is accurate, and how do we catch the wrong answers?
Everyone in that room is deciding how much of their work to hand to a machine. This question decides how far.
I have an answer ready. It is a line I picked up somewhere in the five to ten hours of video summaries I go through every day.
“You can outsource your thinking,” I tell them, “but you cannot outsource your understanding.”
Then I say it again.
I explain it with soup. AI can make the soup. But if nobody in the building understands how the soup was made, nobody has any idea whether it is poisonous.
Then someone asks a question.
“Did you come up with that quote?”
“No,” I say.
That is the whole answer I have.
I have just told a room full of people that they need to understand where their answers come from.
I cannot tell them where mine came from.
That is the moment the line stopped being a quote to me. A machine had done the finding and the condensing, and I had skipped the understanding: who said it, where, and what they meant by it. It was a good line and I was confident in it. If it had been wrong, I would have had no way to know.
When I sat down to write this, I did the thing I should have done before I said it out loud. I looked it up.
The line reached me through Andrej Karpathy, a founding member of OpenAI. In a conversation with Stephanie Zhan published by Sequoia Capital, he says it came from a tweet that blew his mind, and he thinks about it every other day.
At the end of the session I asked what people were taking back to their desks. One of the first answers was that line.
What understanding actually means
AI can do the analysis. It can do the recommendation. What it cannot do is own the result.
Here is the hypothetical I gave the room. An agent reviews your sales and recommends ordering 100,000 units. The analysis might be right. It might also have read a one-time spike as a trend. Somebody has to ask why 100,000, and somebody has to be willing to put their name on that number.
That is understanding. It is not doing the math yourself. It is being able to explain the decision to the next person who asks.
The same goes for the agents themselves. When an agent is running part of your business, somebody has to understand its architecture. The AI can explain it to you, but somebody has to dig in and ask why it made each decision. Every workflow gets a named owner, and its instructions live in a shared folder, not in one person’s chat history.
Make the models argue
My first line of defense is not a person. I connect Claude Code to Grok and to Codex, so when one model reaches a conclusion, another one gets to challenge it. They argue until they settle it.
It doesn’t eliminate hallucinations. It reduces them significantly.
But two models agreeing is still outsourced thinking. It narrows down which answers need a human. It does not replace the human.
Four checks that scale with the stakes
Ask for the source, every time. Which row, which tab, which document. An answer that can’t point at where it came from is a guess wearing a suit. I learned that one in front of a room.
Spot-check two of twelve. If either one is wrong, throw the whole answer out. Don’t repair it. The errors you found are telling you about the ones you didn’t.
Know what wrong looks like before you ask. If you can’t describe a bad answer ahead of time, you won’t recognize one when it arrives looking confident.
Scale the check to the stakes. Glance at a draft email. Check a purchase order with a 60-day lead time the way you would check a colleague’s work, because by the time you find the mistake, the container is on the water.
The new hire
The best way I know to think about AI is as a very fast, very well-read new hire who has never been to your warehouse and will never admit to not knowing something.
You would let that hire draft almost anything. You would not let them order 100,000 units without asking why.
Hand it the thinking. Keep the understanding.
Someone asked me a simple question in front of a room, and all I had was “No.” Now I have a name, and I know what the line meant.
