Developer builds LLM router that assigns different AI models based on article type

A developer has built an automated content pipeline that routes article generation to different AI models depending on content type and priority, with premium pieces going to stronger models and high-volume drafts to cheaper, faster ones. The system includes a cascade failover to prevent stalls when a provider hits rate limits. Before publishing, every draft passes through anti-AI-language cleanup, a quality scoring judge, and a structural schema check. A daily job re-scores recently published content and automatically regenerates pieces that fail quality thresholds. The pipeline currently powers two live niche content sites, with the developer targeting a $30,000 monthly run-rate across 30 sites within two years.