Building in public: how AI agents run our content factory

Description and use

Content automation with AI works when each agent has a narrow role and a human checkpoint, but fails without supervision.

Problem

Automating content creation and sales conversations with AI agents risks quality drift, hallucinations, and handoff failures if not properly modularized and supervised.

Outcome

Content automation works when each agent has a narrow job and a human checkpoint; it fails when agents run unsupervised.

Workflow

• 1. Agent 1 researches topic and drafts article
• 2. Agent 2 converts briefs into SEO pages
• 3. Agent 3 handles first‑touch sales conversations
• 4. Agent 4 reads analytics to suggest next topics
• 5. Human reviewers check drafts, validate sources, and approve publication
• 6. System logs failures, adds validation steps, and fixes causes

Evidence

In our content factory, AI agents draft articles, qualify sales conversations, generate SEO pages and read analytics, while people set strategy, review output and own decisions.

Source

Content automation works when each agent has a narrow job and a human checkpoint. It fails when agents run unsupervised.

Source

Drafts drift from our tone. Agents sometimes produce a claim that sounds right but has no source. Handoffs fail quietly when an input format changes.

Source