An AI content system, and the skill library behind it

Content was being produced the way it is produced almost everywhere: ad hoc, in whichever tool was closest, with quality depending on who happened to pick it up. Nothing was measurable, nothing was repeatable, and institutional voice lived in people's heads.

• Mapped the real lifecycle from first draft to published and logged, including the approval steps people were doing informally.
• Built AI-assisted drafting into the front of the process and automated review behind it, keeping human approval and editing in the middle where judgment matters.
• Connected the tools by API so nothing depended on copy-paste, with a single shared source of truth for what had been published.
• Authored a library of AI agent skills to encode voice and process: a company-page voice skill now on its sixth iteration, separate skills for individual executive voices, a searchable quote bank, a newsletter assembler, and a campaign-tagging tool.
• Built the publishing pipeline itself: an automation that posts to LinkedIn and X through Typefully and announces each post in the right Slack channels automatically.
• Added skills that draft posts automatically, a shared content calendar, and WhatsApp automation for the parts of the process that happen there.
• Added automated daily engagement reporting and weekly competitive intelligence, both still running.

• An ad-hoc process turned into a repeatable, measurable workflow with one source of truth.
• Voice consistency that does not depend on one person being available, and does not flatten into generic copy.
• Teammates able to produce work in the system without needing deep technical skill, which was the point of the whole exercise.