Don’t be lazy. Don’t forward ChatGPT’s hot take on someone’s deck. Good advice.

But it misses the real problem: ** nobody’s reading anymore **.

They’re pasting your document into their model of choice and asking if it contains anything worth knowing. You’re lucky if you get a reply from a human at this point.

I commented this on a recent post by Eytan Buchman and he replied: “Feedback prompt injection! Genius!”

He’s right. That’s exactly what I’m doing.

As a side hobby I’m working on a technical research project with a large document set: architecture specs, design rationale, experimental results. I sent the bundle to an engineer colleague for review.

He didn’t read it. His Claude session did.

He pasted the entire thing into his own AI session, which produced a summary and a prototype. A human never read my documents. The model was the actual reader.

This wasn’t laziness. This is what competent professionals do now. But I saw this coming a good year ago.

That’s when I pivoted. I shifted to writing my long-form documents for model consumption first. Not dumbed down… structured for accurate distillation. With correctives embedded in the text that keep a summarizing model on track.

Three things I learned the hard way:

1️⃣ **One word can change everything**: A single word in my docs (“reference” instead of “experimental”) changed how every model interpreted the project’s authority level.

2️⃣ **Framing is fate**: I described decisions as design choices. Every model helpfully suggested alternatives.

3️⃣ **Models skip to the interesting parts**: When I published the full doc set, models skipped the foundational work and went straight to whatever sounded like the hot topic.

I called this “semantic collapse”… accurate transmission of the what, silent replacement of the how and the why.

Your reader has perfect recall, zero judgment, and will confidently summarize what it thinks you said regardless of whether it caught the point.

Write for that reader. The humans will get the message once the model delivers it.

Full breakdown with more examples in the article “Feedback Prompt Injection: Writing for the Robot in the Room“