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Generic AI copy is poor because LLMs learn from the internet's vast, low-quality content. The key to effective AI-generated copy is training it on a user's specific values, personality, and brand voice, moving beyond generic prompts to create something that resonates authentically with a target audience.

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Despite running an AI company, Clay's co-founder warns against using LLMs for marketing. He argues that AI models are designed to synthesize information and find the average, which is the opposite of marketing's goal: to stand out and be original. His team is discouraged from using it for marketing copy.

Develop superior AI-generated copy by first using an AI agent to research and deconstruct the frameworks of top marketers. Then, feed the AI examples of your own writing to distill a unique brand voice. Combining these into a custom 'skill' produces consistent, high-converting copy that feels authentic.

AI doesn't replace copywriters; it transforms their role. By automating the menial task of generating countless variations, it frees them to focus on high-level strategy: defining brand voice, guiding the AI, and acting as the expert who orchestrates the machine rather than being the machine.

AI models fail at great literary writing because they lack an authentic "voice." This voice isn't just a stylistic quirk; it's the product of an individual's unique life experiences and perspective. Since AI lacks this grounding, its writing feels inauthentic, like an imitation of a style without the substance behind it.

Eoin Clancy of Airops defines low-quality AI content, or 'slop,' with three indicators: 1) It isn't unique and fails to advance the conversation. 2) It doesn't sound like your brand. 3) It uses robotic language, such as 'utilize' instead of 'use' or excessive em-dashes.

As platforms like LinkedIn become saturated with generic AI content, authentic human voices stand out more than ever. A distinct, personal writing style—even with occasional typos—is becoming a powerful differentiator that cuts through the noise and builds trust.

To avoid generic AI-generated text, use the LLM as a critic rather than a writer. By providing a detailed style guide that you co-created with the AI, its feedback on your drafts becomes highly specific and aligned with your personal goals, audience, and tone.

GM's CMO warns that AI in creative often produces average results because it finds the "most likely next answer," reflecting the category norm, not a distinctive brand voice. Simple edits can also trigger a full re-render, introducing new errors and creating more work.

AI makes it easy to generate grammatically correct but generic outreach. This flood of 'mediocre' communication, rather than 'terrible' spam, makes it harder for genuine, well-researched messages to stand out. Success now requires a level of personalization that generic AI can't fake.

LLMs function by predicting the most probable next word, effectively averaging out language. Over-relying on them for content creation will systematically strip away the unique aspects of your brand's voice, leading to homogenization and risking a 'dead internet' effect.

AI Copy Fails Because It's Trained on the Mediocre Internet, Not Your Unique Voice | RiffOn