A solo founder’s AI content pipeline for fixing slow SEO work
The first product was a , but it lost momentum because people could not find it. There was no ad budget and no existing audience, so search content became the main growth option, but one article could take a full evening and still might not rank. Content agencies were costly and slow, and managing them took time away from getting users.
SwiftlySEO was built to reduce that bottleneck: it takes a keyword or short brief, checks the live search results, creates an optimized article, scores it automatically, improves it until it meets a quality bar, and then sends it to the CMS. Nothing goes live until a person reviews it. The core view is that AI can do much of the heavy work, but a step is needed to keep useful content from becoming low-value mass output.
The stack uses React, TypeScript, Supabase, N8N, and Stripe, and the next planned feature is scheduled content refreshing so older articles can be flagged and updated when search results change.
Key points
- The earlier product struggled because people could not find it through search or an existing audience.
- Content agencies were too expensive, slow, and management-heavy for a .
- SwiftlySEO combines keyword input, live search analysis, article generation, automatic scoring, revision, and CMS delivery.
- still requires before publishing.
- A planned feature will refresh older articles when search results change.