Best AI for Copywriting - The Problem Is Input, Not Model
Best AI for Copywriting - The Problem Is Input, Not Model
People keep asking which AI model writes the best marketing copy. They are asking the wrong question. The difference between good and bad AI copy is almost never the model - it is the input.
The Model Comparison Trap
Switching from GPT-4 to Claude to Gemini hoping for better copy is like switching pens hoping for better handwriting. The output quality is dominated by what you put in, not which model processes it.
Give any modern LLM a vague prompt like "write a landing page for my SaaS product" and you get generic, forgettable copy. Give the same model a detailed brief with your customer's exact pain points, their language from support tickets, and three examples of competitor messaging you want to differentiate from, and you get copy that actually resonates.
What Good Input Looks Like
Customer language, not marketing language. Pull actual phrases from customer reviews, support conversations, and sales calls. When a customer says "I spent three hours every week copying data between spreadsheets," that is better input than "streamline your workflow."
Specific constraints. Tell the model the reading level, the word count, the tone, and what claims to avoid. "Write a 150-word product description at an 8th grade reading level, conversational tone, no superlatives, no claims we cannot prove" produces dramatically better output than "write a product description."
Context about what failed. If you have previous copy that did not convert, include it with an explanation of why. "This headline got a 0.3% CTR because it was too vague" teaches the model what to avoid.
The Real Workflow
The best AI copywriting workflow is not model selection - it is input preparation. Spend 80% of your time building the brief and 20% generating and editing. Most people do the opposite: they spend 80% of their time tweaking prompts and switching models and 20% on the brief.
Any current-generation model will produce good copy from good input. No model will produce good copy from bad input.
Fazm is an open source macOS AI agent. Open source on GitHub.