← Back to Sandbox
Can an autonomous content engine write, publish, and promote blog content on a perpetual loop — and maintain quality over time?
What happens when you point an AI agent at a topic domain and tell it to keep writing? Not one article — an infinite stream. This experiment creates an autonomous content engine that researches trending topics, writes articles, optimises for SEO, publishes them, promotes on social, and uses performance data to decide what to write next.
The loop never ends. Performance data from published articles directly shapes what gets written next.
Can an autonomous content engine write, publish, and promote blog content on a perpetual loop — and maintain quality over time?
What happens when you point an AI agent at a topic domain and tell it to keep writing? Not one article — an infinite stream. This experiment creates an autonomous content engine that researches trending topics, writes articles, optimises for SEO, publishes them, promotes on social, and uses performance data to decide what to write next.
The loop never ends. Performance data from published articles directly shapes what gets written next.
Autonomous content engines need a built-in quality gate — volume without quality control triggers search ranking penalties that undo the traffic gains.
Voice consistency requires explicit style memory, not just prompting — the model drifts without a persistent reference.
A “novelty gate” that rejects topics too similar to previous output is essential to prevent self-cannibalisation.
Human-in-the-loop for topic selection paired with autonomous writing is the sweet spot — humans find gaps better, agents write faster.
The quality degradation curve is the most interesting finding. There’s a point — around article 80 in this case — where the agent starts cannibalising its own output. We’re exploring whether a “novelty gate” that rejects topics too similar to previous articles can extend the useful range.