Why I Started Ignoring AI-Written Work Documents (And You Might Too)

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A growing number of professionals are quietly tuning out documents that read like they came straight from an AI model. A recent essay describes the moment recognition kicks in — a design doc, a marketing deck, a requirements file — and how attention immediately drops. The pattern isn't about AI use itself, but about how obviously unedited the output is.

What's Happening

An essay circulating among developers and knowledge workers describes a specific kind of fatigue: the moment you spot low-effort AI-generated content in a work document, your focus collapses. Instead of trusting what's already written, you end up going back to the sender and asking them to explain it again — even though the answer is technically right there on the page.

The examples given are concrete. A design document laced with phrasing characteristic of Claude. A 20-page marketing deck padded with statements that sound technical but carry no actual information. A requirements document so rambling it reads like an AI's uncertain internal reasoning process, left in rather than cleaned up.

Why This Is Happening Now

Using large language models to draft emails, specs, proposals, and reports has become routine across industries. The friction isn't in the drafting — it's in what happens after. Increasingly, first drafts are being sent out with little to no human editing.

Early conversations about AI writing focused on whether readers could tell the difference between human and machine text at all. That conversation has shifted. Certain models have recognizable tics — repeated phrasing, a tendency to over-explain, conclusions that circle without landing — and those tics are becoming easier, not harder, to spot as usage scales up.

The Trust Problem

This matters beyond annoyance. When a reader identifies AI-generated filler in a document meant to convey a decision or a technical spec, the natural response is skepticism, not efficiency gain. The reader starts double-checking claims that would otherwise be taken at face value. In effect, unedited AI output can end up costing more time than it saves, just shifted from the writer to the reader.

There's also a signaling effect. A document that reads as AI-generated without revision can come across as low-effort, regardless of whether the underlying content is accurate. That perception gap — between the actual value of the information and how much effort readers think went into presenting it — is where trust erodes fastest.

Industry-Wide Implications

This dynamic is likely to intensify as AI drafting tools get embedded deeper into everyday workflows — email clients, project management software, internal wikis. The tools that generate text quickly are outpacing organizational norms around editing and review before sending.

For teams relying heavily on AI-assisted writing, the practical lesson isn't to stop using these tools. It's that unedited AI output is increasingly recognizable, and recognizability is starting to carry a credibility cost. Documents that get a human pass before distribution — trimming padding, removing hedge-y reasoning, tightening structure — are likely to be read more carefully and trusted more readily.

Takeaway

The issue was never really about AI writing quality. It's about what happens when a draft goes out the door without a second look. As AI-assisted writing becomes the default rather than the exception, the gap between a good draft and a properly edited document is becoming one of the more visible signals of effort in professional communication.

Reference: https://cymerys.com/w/im-becoming-ai-blind

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