How to teach an AI your brand voice (and keep it on-brand)

On-brand at scale is the hardest problem in automated marketing. Generate a thousand assets and the brand drifts. Here is a practical, repeatable playbook for getting a model to sound like you — every single time.

The five-step loop

1. Feed it your best. Import the content you are proudest of, not everything you have ever shipped.
2. Name the voice. Write down the three adjectives you are and the three you are not.
3. Set the guardrails. Banned words, claims you cannot make, the structures you love.
4. Review the edges. Approve or reject at the margins — that is where the model learns fastest.
5. Lock a reference. Keep a canonical set of on-brand examples the engine always checks against.

Encode the rules

Give the engine machine-readable brand rules so nothing drifts. A minimal style contract:

{
  "voice": ["warm", "confident", "plain"],
  "avoid": ["hype", "jargon", "exclamation!!"],
  "reading_level": "grade 8",
  "claims": { "allow_superlatives": false }
}

Then review at the edges and keep claims specific: say "set up in minutes", not "blazing fast".

The goal is not content that passes review. It is content that never needed the review to catch anything.

Common mistakes

• Training on everything instead of your best work.
• Describing the voice in your head but never writing it down.
• Approving in bulk, so the model never learns the edges.

Ready to see it on your brand? Book a demo and we will import your best work and show you the first drafts.