The overusage of “It’s not A, it’s B” or “It’s not about A, but it’s about B” is driving me crazy.

2026-05-04 · Source: Artificial Intelligence · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Emerging Technologies & Innovation · Depth: Intermediate, medium

Summary

A growing sentiment among internet users highlights frustration with the pervasive and formulaic language patterns generated by AI, particularly the "It's not A, it's B" structure and excessive emoji use. Users report encountering these patterns across various platforms, including social media, news articles, and YouTube videos, often finding them "deafening" and prompting them to disengage. Some individuals actively prompt large language models (LLMs) like ChatGPT, Perplexity, and Claude to avoid such structures, though it's noted that LLMs, especially Claude, can mirror user input styles. The discussion also touches on the broader implications of AI-generated content, suggesting that the internet's content corpus is increasingly dominated by AI, leading to feedback loops in search engines and a fundamental shift in how truth and knowledge are evaluated when human and AI origins become indistinguishable. This raises concerns about the future of expertise and the need for institutions to adapt.

Key takeaway

For content creators and marketers relying on AI for drafting, you must actively edit and refine AI-generated text to remove formulaic expressions like "it's not A, it's B" and excessive emojis. Your audience is increasingly sensitive to these AI-isms, and failing to humanize your content risks alienating readers and diminishing your perceived authenticity. Focus on transforming AI drafts into unique, voice-driven pieces rather than publishing raw outputs.

Key insights

AI-generated content's formulaic language and pervasive patterns are causing user fatigue and raising concerns about digital information integrity.

Principles

• LLMs often mirror user input styles.
• AI-generated content can create feedback loops.
• Volume of AI content challenges traditional epistemology.

Method

Users can prompt LLMs to ban specific linguistic structures like "not X but Y" and minimize emojis, though models may adapt or revert over time.

In practice

• Add "ban all 'not X but Y' structures" to prompts.
• Avoid using emojis first when interacting with Claude.
• Edit AI drafts to inject human voice and nuance.

Topics

• AI Content Generation
• Large Language Models
• Rhetorical Antithesis
• Prompt Engineering
• Digital Information Integrity

Best for: Machine Learning Engineer, NLP Engineer, Prompt Engineer, AI Engineer, AI Ethicist

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Editorial summary, takeaway, and curation by AIssential. Original article published by Artificial Intelligence.