Paste your latest outbound email into a blank document. Hit Command-F.
Type "delve."
If that word lights up, you haven't just failed a Turing test. You are actively burning revenue. In April 2024, Y Combinator founder Paul Graham flagged this specific verb as a "digital tell"—a shibboleth that instantly marks text as machine-generated. This wasn't just an old guard tech mogul yelling at a cloud. Researcher Jeremy Nguyen later validated Graham’s hunch with hard data, visualizing a vertical, unnatural spike in PubMed abstracts.
The usage of "delve" didn't just drift upward; it exploded by over 300% immediately after ChatGPT's release. Language doesn't move that fast naturally. Google Ngram Viewer shows us that human vocabulary evolves over decades, not weeks. This is an algorithmic infection.
We call it the Cognitive Friction Tax.
When a prospect’s brain detects these "safe," probability-based word clusters, it doesn't just get bored. It chemically disengages. The mind treats your copy as low-value noise, identical to generic filler text. You aren't just sounding robotic; you are triggering subconscious ad-blindness in the exact people you need to reach.
The Cognitive Friction Tax: Why Bot-Speak Bankrupts Trust
ð Key Takeaways
- The 17% Saturation Point
- Insider Moves: The "Uncanny Valley" Audit
ð Key Takeaways
- The 17% Saturation Point
- Insider Moves: The "Uncanny Valley" Audit
This isn't about pedantic grammar rules. It is a UX crisis. Large Language Models operate on Reinforcement Learning from Human Feedback (RLHF). They are trained to be helpful, harmless, and honest. To achieve this, they default to the "safest," most statistically probable words. They hedge. They smooth out the edges.
The result is a textureless, beige soup. It lacks burstiness—the jagged, unpredictable rhythm of human speech. When you use AI to write your pitch without heavy editing, you are stripping away the lexical diversity that signals human intelligence.
Think about the last time you saw a "Lorem Ipsum" placeholder. Did you read it? No. Your eyes slid right over it. That is exactly what happens when a B2B buyer sees words like "tapestry," "testament," or "landscape" in an opening sentence. Their brain tags the content as "zero-information filler" and signals the finger to click delete.
The cost isn't just stylistic. It is financial. If your copy sounds statistically probable, your product feels statistically insignificant.
The 17% Saturation Point
The infection is already systemic. A 2024 study by Liang et al. at Stanford University used adjective frequency analysis to scan academic workflows. They estimated that nearly 17% of computer science peer reviews were substantially modified by AI.
In academia, that gets you a bad grade. In enterprise sales, it destroys your sender reputation. Tools like GPTZero and Turnitin now hunt for these patterns by measuring perplexity—a score of how random and complex a text is. AI aims for low perplexity (high predictability). Humans are chaotic.
If your writing lacks that chaos, you fall into the "uncanny valley" of text. The reader feels the artificiality before they can explain it. They don't think, "This is AI." They think, "This person is lazy/lying/hiding something."
Insider Moves: The "Uncanny Valley" Audit
- The "Four Horsemen" Purge. Run a search on your marketing copy for these four words: delve, tapestry, landscape, and testament. These are the primary vectors of the "Delve Index." If you find them, rewrite the sentence immediately using active verbs.
- Break the RLHF "Politeness" Loop. AI wants to be verbose and Latinate (e.g., "facilitate," "utilize"). Force it to be Germanic. Add this constraint to your prompt: "Use high burstiness, zero hedging, and Anglo-Saxon roots." This forces the model to say "buy" instead of "facilitate a transaction."
- Watch for Linguistic Drift. The danger isn't just sounding like a bot today. It's that as humans start mimicking AI to sound "professional," the baseline of English will shift. To stay persuasive, you must stay weird. If your sentence flows too perfectly, break it.
ð Worth Noting: " This forces the model to say "buy" instead of "facilitate a transaction