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AI Agent

AI Copywriter Agent

Professional copywriting frameworks + your company's real stories and data. Writes emails, ads, landing pages in your brand voice. Not generic AI slop.

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How AI copywriting usually fails

Pretty much everyone has tried ChatGPT for copywriting by now.

You give it a prompt: "Write an email about our new product." It spits out something that sounds... fine. Professional enough. Grammatically correct.

But it's generic. Could be for any product, any company. No personality. No real understanding of your customers. No connection to your actual product story or values.

And look — even if you're detailed with prompts, you're still missing the fundamentals. Professional copywriters don't just "write good sentences." They use proven frameworks: problem-agitate-solve, AIDA, the customer awareness ladder from Eugene Schwartz.

Generic AI doesn't know these frameworks. Doesn't know your customers. Doesn't have access to your actual product stories, customer testimonials, or brand positioning documents.

Result:
AI-generated copy that's bland, generic, doesn't convert. Copywriter still has to rewrite everything. Might as well have written it from scratch.

You're not actually saving time. Just generating drafts that need major surgery.

What makes this agent different

Here's the thing — this isn't ChatGPT with a prompt. It's a custom-trained system with professional frameworks and your company's knowledge baked in.

1

Professional frameworks

Agent is built with proven copywriting and marketing frameworks:

  • Great Leads methodology (Eugene Schwartz) — how to hook readers based on their awareness level
  • Customer awareness stages — problem aware, solution aware, product aware, most aware, unaware
  • Proven structures — AIDA, PAS, FAB, Before-After-Bridge
  • Conversion optimization principles — what actually drives action

Not just "write something that sounds good." Structured approaches that convert.

2

RAG integration with your data

This is the key difference. Agent has access to your internal knowledge base through RAG (Retrieval-Augmented Generation):

Company stories:

  • How your product was developed
  • Founder story and mission
  • Supplier relationships and sourcing
  • Your unique approach or methodology

Customer data:

  • Real testimonials and reviews (not made up)
  • Customer interview transcripts
  • Common objections and how you address them
  • Success stories and case studies

Product knowledge:

  • Technical details and features
  • Use cases and applications
  • Comparison to alternatives
  • Unique selling points backed by real data

Brand voice:

  • Examples of past successful copy
  • Tone guidelines
  • Words/phrases you use (and avoid)
  • Your positioning and values

So when agent writes about your product, it's pulling from real stories, real customer language, real differentiation.

3

Awareness-level targeting

Agent understands where your audience is in the customer journey:

Unaware → Hooks them with the problem they didn't know they had
Problem aware → Agitates the problem, introduces your solution category
Solution aware → Positions your specific product vs alternatives
Product aware → Reinforces differentiation, drives action
Most aware → Simple reminder and strong CTA

Different copy for different stages. Not one-size-fits-all.

4

Multiple format mastery

Agent can write across formats:

  • Email campaigns (nurture, promotional, transactional)
  • Landing pages (long-form sales pages, squeeze pages, product pages)
  • Ad copy (Facebook, Google, display)
  • Product descriptions
  • Sales letters
  • Case studies

Each format has its own best practices. Agent knows them.

5

Iterative refinement

First draft from agent goes to human reviewer (your copywriter or marketer). They refine, adjust tone, add specific touches.

Agent learns from these edits. Over time, its first drafts get closer to what you actually publish.

Not replacing copywriters. Making them 10x more productive.

6

Performance feedback loop

Agent can integrate with email analytics and ad platforms to see what copy performs:

"Emails with [this hook] drove 2.1x more opens."
"Landing pages with [this structure] converted 30% better."

Learns what works for your specific audience. Gets better over time.

(Works great in combination with our Email Analytics Agent and Content Planning Agent for a complete system.)

How RAG Retrieval Works - 5-step process from copy request to human review
How RAG retrieval works: from copy request to AI generation with your company context
N8N AI Copywriter Workflow - RAG integration with company knowledge base
N8N workflow automation: briefing, awareness level targeting, framework selection, and RAG-powered copy generation

What you actually get

Before:

Copywriter writes from scratch every time. Takes 2-4 hours per email, 1-2 days per landing page. Quality varies based on how much they remember about past winners.

After:
  • AI generates first draft in minutes (using frameworks + your data)
  • Copywriter reviews and refines (30-60 minutes instead of 2-4 hours)
  • Consistent quality (frameworks ensure structure)
  • Better use of company stories and customer language
  • Productivity increase: 5-10x

Real example:

SaaS company with one copywriter handling all email, landing pages, and ad copy. Bottleneck was killing marketing velocity — couldn't test fast enough.

We built them an AI Copywriter trained on:

  • 3 years of past email campaigns (what worked, what didn't)
  • 50+ customer interviews
  • Product documentation and use cases
  • Founder's vision and positioning docs

Agent now generates first drafts for everything. Copywriter reviews and refines.

Result: Went from 5 emails per week to 15. From 1 landing page per month to 1 per week. Quality actually improved because they could test more variations, learn faster.

Copywriter didn't get replaced. Got promoted — now manages AI output and focuses on strategy instead of cranking out first drafts.

Productivity: 5-10x increase

Copywriter Productivity Transformation - Before and After AI Copywriter Agent
Productivity transformation: from 5 emails/week to 15, from 1 landing page/month to 4, with 3x overall productivity increase
AI-Generated Email Copy Example with Framework Annotations and RAG Sources
Example email copy showing framework application (PAS), RAG data integration, and brand voice consistency

Requirements

For the agent to work, we need:

From you:

  1. Access to your knowledge base:
    • Past successful copy examples (emails, landing pages, ads)
    • Customer testimonials and reviews
    • Customer interview transcripts (if available)
    • Product documentation
    • Company story and positioning materials
    • Brand voice guidelines
  2. Performance data (which copy converted, which didn't)
  3. Access to copywriter/marketer who will review and refine output
  4. Examples of your best-performing copy

From us:

  1. RAG system setup with your data — 3-4 weeks
  2. Framework integration (Great Leads, awareness ladder, conversion principles)
  3. Training for your team on prompting and reviewing
  4. Iterative refinement based on feedback
  5. Performance tracking integration
Timeline: 4-6 weeks from kickoff to production-ready system
Cost: Development hours + performance bonus tied to copy performance improvement

The more historical data you have (past copy + performance), the better the system works. But we can start with basics and improve over time.

Diagram showing knowledge base structure for AI Copywriter
Knowledge base structure: how company data, customer insights, and frameworks integrate

Want this for your copywriting?

Look, AI Copywriter isn't magic. And it's definitely not ChatGPT with fancy prompts.

It's professional copywriting frameworks + your actual company data + systematic learning from what works.

Difference: your copywriter goes from spending 80% of time writing first drafts to spending 80% of time on strategy and refinement. Productivity scales without hiring more people.

Let's look at your copy operation. Maybe you're already moving fast enough. Maybe you're bottlenecked on production and could 10x output with the same team. Either way — worth a conversation.

Book $300 AI Audit

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