Content Agents

Your industry has a language. Your AI now speaks it.

Lock your preferred terms once — pay slips, not paychecks; members, not users — and every article, social post, newsletter, and podcast uses them. Automatically.

One glossary.

Terminology is not a writing preference — in a niche market it is the difference between sounding like an insider and sounding like a content farm.

What it looks at

How it works

  1. Write your rules — One rule per line in Settings: "Use 'pay slips', never 'paychecks'." No taxonomy project, no tagging.
  2. Saved to your brand — The terminology lives with your brand voice — editable by your team, or set by your AI editor during onboarding.
  3. Every generation obeys — The rules are injected into every AI generation as a mandatory instruction — not a suggestion buried in a style guide.

Included in every plan.

Brand Terminology is part of the brand voice system — not an add-on. Every workspace gets it, on every content surface.

Speak your market’s language.

Set your terms once. Every piece of content — starting with the next one — uses them.

Frequently asked questions

How is this different from brand voice guidelines?

Voice guidelines shape tone — warm, authoritative, playful. Terminology locks exact words. You need both: voice makes content sound like you, terminology makes it factually speak your market’s language. In Content Agents they live side by side, and terminology is enforced as a mandatory rule on every generation rather than a stylistic hint the AI may drift from.

Can’t I just put preferred terms in a prompt or style guide document?

You can — once, in one tool, for one piece. The problem is coverage: the article generator, the social scheduler, the newsletter writer, and the podcast scripter are different generation paths. A pasted prompt covers one of them for one session. The terminology engine is wired into all of them permanently, so a term you add today is respected by a social post your autonomy engine publishes next month.

How complicated is setup?

It is a textarea. Write one rule per line — “Use ‘pay slips’, never ‘paychecks’” — and save. There is no model retraining, no tagging project, and no import pipeline. The next piece of content generated already follows the rules.

What happens when our terminology changes?

Edit the line and save. Every generation from that moment on uses the new term. Existing published articles are untouched — you decide if and when to revise them, and the inline writing assistant will follow the new terminology when you do.

We work with an agency — can they manage terminology for all our brands?

Yes. Terminology is per-brand, so an agency running multiple workspaces sets a separate term list for each client. It is also exposed through the MCP connection, so an AI agent can read and update terminology programmatically — including during onboarding, where preferred-word lists can be extracted directly from a client’s brand book.