The effort signal

When AI tools landed in most teams, so did a pattern nobody quite had words for: a colleague sends AI-generated output without reviewing it, expecting the group to do the evaluation they skipped. The frustration is real. But the usual framing, “show effort when asking for attention,” puts the weight on the wrong thing.

Tom Bedor articulated the rule he now follows after a colleague forwarded AI analysis they hadn’t read and asked him to evaluate it. The rule is sensible. But I think it misidentifies what’s actually broken.

What effort was signaling

Effort never had intrinsic value in documents and analysis. A bad ten-hour report is worse than a good one-hour conversation. The value of a document is the value of its contents, not the time it took to produce them.

What effort signaled was skin in the game. When you wrote something from scratch, you had probably caught the obvious errors, spent enough time with the material to notice the gaps, considered the obvious objections. You were putting your name on something you built, which made you accountable for it in a way others could rely on.

AI breaks that mechanism. Generating a thorough-looking analysis takes seconds, so the act of generating it tells you nothing about whether the person behind it stands behind it.

The gap is accountability

The friction that flows from unreviewed AI output has nothing to do with how long it took to produce. It is about whose job it is to exercise judgment on the content before it reaches the reader.

When a colleague sends you AI output without annotation, they are asking you to figure out what they think, what they have checked, and what they are uncertain about. The work of evaluation has been delegated to you. The AI made the content; the person who shared it made none of the judgment calls.

Labeling AI content when you share it helps. But the more useful signal is what you are actually vouching for and what you are asking from the reader. “The model drafted this; I have checked the data and think the argument holds, but want a second opinion on the assumptions” gives the reader something to work with. “I asked the AI; here it is” forwards the AI’s work and calls it yours.

What replaces it

If you manage a team using AI tools, the accountability question is more useful than the effort question. Do you stand behind this? Have you said what you are asking of the reader?

A practical test: if someone acted on this and it turned out to be wrong, would you feel responsible for having shared it? If yes, you are owning the output. If no, you may be forwarding AI work while letting the accountability stay with the model.

Effort was the mechanism that produced accountability in a world where generating content was expensive. That world is gone. What needs to replace it is being explicit about what you are vouching for. That takes five seconds, and it actually serves the reader in a way effort alone never did.