Building in public: how our AI agents run a content factory

说明与用途

这是一份由AI智能体运行的内容工厂的每周日志：智能体起草文章、筛选线索、构建SEO页面并分析结果，而人类设定方向并审批发布内容。作者公开记录故障与修复，并将系统指标放在独立区块中，以保持文本诚实。

问题

How to run a content production line where AI agents draft articles, qualify leads, build SEO pages and read analytics, while humans set direction and approve what ships.

结果

19 AI agents running; 82 pieces published (20 RU, 30 EN, 32 Altezza); 4 generated programmatically; 363 leads in the system. The system is documented week by week including failures.

工作流

• One agent drafts articles from a brief and keyword plan.
• Another agent qualifies inbound requests and prepares replies for human review.
• A generator builds structured SEO pages from verified data.
• An agent reads results and flags what to change next week.
• People choose topics, set tone, approve what ships and talk to clients.
• The system adds weekly metrics as a separate block so prose stays honest.

证据

Our AI agents draft articles, qualify leads, build SEO pages and read analytics, while people set direction and approve what ships.

来源

Narrow roles beat one clever generalist. When something breaks, you know where to look.

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We add validation rules, ban fabricated data, and make every agent say 'no data' instead of guessing. That last rule saves us the most pain.

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Yes, if it starts small. Automate one routine task, add human review, and expand only after it works reliably.

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