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

Описание и применение

Мы ведем еженедельный дневник работы контент-фабрики, управляемой ИИ-агентами. Агенты пишут статьи, qualify leads, строят SEO-страницы и анализируют результаты; люди решают темы, тон и одобряют публикацию. Мы публикуем ошибки и их исправления, а также системные метрики в отдельном блоке, чтобы текст оставался честным.

Задача

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.

Результат

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.

Рабочий процесс

• 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.

Доказательства

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

Источник

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

Источник

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.

Источник

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

Источник