Building in Public: How AI Agents Run Our Content Factory

说明与用途

公司使用19个AI代理来撰写内容、准备销售跟进、生成SEO页面并分析结果，所有公开内容都经过人工审核。工作流程分为写作、销售、SEO和分析四个角色，提升了速度和质量。

问题

Automating content creation and sales follow‑ups while maintaining quality and preventing fabricated data.

结果

The workflow increases content output (67 pieces in a week) while keeping quality through human review and iterative guardrail improvements.

工作流

• 1. Analytics agent reads weekly performance data and identifies successful and stalled topics.
• 2. Topics and constraints are set for the week.
• 3. Writing agent drafts articles from approved briefs.
• 4. Sales agent prepares replies and follow‑ups for a person to send.
• 5. SEO agent generates pages from vetted templates and checks them against rules.
• 6. Human reviewers approve any content that goes public.
• 7. Analytics agent reads results, records failures, and suggests instruction adjustments.
• 8. Team reviews adjustments and updates agent prompts.
• 9. Repeat cycle each week.

证据

Building in public means we show how our AI agents actually run a content factory. They draft articles, prepare sales follow‑ups, generate SEO pages and read analytics, while people set the goals and approve the result.

来源

We split the work into narrow roles: Writing agent, Sales agent, SEO agent, Analytics agent.

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Early in the week, analytics shows what worked and what stalled. We pick topics and set constraints. The agents draft, and a person reviews anything that goes public.

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They repeat themselves, drift from our tone, and sometimes claim things they can't support. That is why we forbid invented data.

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