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Scaling LinkedIn content without losing the brand voice

An AI content engine drafts posts and visuals on schedule, with a human approval gate and engagement data feeding back into the prompts.

80%of drafts, visuals and ideas generated by AI
20%human review for brand accuracy
100%of posts pass a human approval gate

The challenge

Manual LinkedIn content was too slow and inconsistent to build lasting brand authority.

What we built

  • Brand voice, content pillars and goals defined up front and stored as context for the AI.
  • An n8n workflow drafts copy and visuals for each scheduled slot.
  • A Slack approval gate means nothing publishes without human review.
  • Engagement is tracked nightly and the best-performing patterns feed back into the prompts.

Results

  • Consistent posting at scale
  • Manual content effort cut sharply
  • Brand voice kept consistent through human review
How it works

Step by step.

01

Schedule

A content-calendar trigger fires for each posting slot.

02

Draft

AI drafts copy and visuals using the brand context.

03

Review

A human approves, edits or rejects in Slack.

04

Publish

Approved posts go out through the LinkedIn API.

05

Learn

Engagement data improves future drafts.

Similar challenge?

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