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Train GPT to speak your brand’s language. A structured framework that teaches LLMs how to match tone, style, and messaging — using persona anchors, prompt chaining, and calibration examples.

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Brand Voice Trainer 🗣️🤖

An AI-powered system that ensures brand voice consistency using structured GPT-4 prompts and training data. Built with an agent-first architecture that blends LLM automation with human review to eliminate bottlenecks without sacrificing tone integrity.


💡 Overview

Brand Voice Trainer ensures messaging consistency by analyzing content against a founder’s tone and narrative style. It streamlines content QA and empowers teams to write with clarity and alignment - especially useful in fast-paced, high-volume environments.

🧩 Problem → Solution → Results

Problem:

Podcast asset production was tedious and manual, requiring multiple rounds of review and formatting each week.

Solution:

Built an AI-driven workflow that parses transcripts, extracts key takeaways, suggests clips, titles, captions, and thumbnail prompts, with a human QA layer before publishing.

Results:

  • Saved 4+ hours/week in manual asset creation
  • Streamlined collaboration between editors and marketing
  • Maintained consistent branding across episodes

✨ Key Features

  • Analyzes drafts for tone and phrasing alignment
  • Provides actionable feedback and rewrite suggestions
  • Trained on custom brand voice briefs and narrative samples
  • Accelerates review cycles without diluting personality

🛠️ Tools Used

  • GPT-4 (Core prompt engine for tone analysis and rewrite generation)
  • Claude (Used for prompt testing, refinement, and QA comparison)
  • JSON (Structured format for persona, voice principles, and examples)
  • Google Docs / Notion (Source documentation and collaborative editing)

🔧 Technical Highlights

Prompt Engineering:

  • Uses a 10-step voice alignment framework
  • Evaluates clarity, tone, authenticity, and founder match
  • Offers inline edits + strategic rewrite options

Training Data:

  • Brand voice brief (3–4 pages)
  • Founder-authored posts and storytelling samples
  • Generic examples labeled for filtering and correction

Workflow Integration:

Creator → Draft → Brand Voice Trainer → Self-Edit → Publish

📊 Results

  • ⏱️ 60% reduction in content review time
  • 🧠 Increased copywriter autonomy and consistency
  • 📝 Protected founder voice even under resource constraints
  • 🚀 Zero delays in content publishing after rollout

📌 Project Status

  • ✅ Voice Training + Prompt Architecture Complete
  • 🟡 Prompt Refinement Ongoing
  • 🔴 Automation/UI Layer: Next phase (n8n or Replit)

🔗 Related Projects


👤 Creator

Ros Talbot — AI Workflow Architect | Creative Project Manager
Building systems that enhance creative output through automation + authenticity.

🌐 rostalbot.com
💼 LinkedIn
📧 ros.talbot@gmail.com

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Train GPT to speak your brand’s language. A structured framework that teaches LLMs how to match tone, style, and messaging — using persona anchors, prompt chaining, and calibration examples.

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