LawnCare.center is an automated content engine for a niche most people forget about until a dandelion appears. A Python pipeline turns keywords and YouTube videos into QA-scored, affiliate-linked articles. A Next.js site renders them. Research, draft, hero and section images, internal links, schema — all unattended. What stays human: whether the grass is worth the article.
Scope at a glance
Started November 2025 with a keyword-first generator. Five months later: two pipelines, twice-weekly ships on GitHub Actions, 74 articles across 14 categories, twelve cents per article.
By the numbers
74
Articles
$0.12
$
Per article
2/wk
/wk
Auto-publish
14
Categories
34
Affiliate SKUs
8.0+
+
QA floor
11
Python modules
30d
d
YouTube cache
Referring domains, last 14 days — the discovery surface in one chart.
Search Console, five months in — 4.7K impressions and the March turn.
Systems, not screens
Two pipelines feed the engine. Keyword-first: take a search term, dedupe against everything published, draft 1,500 words with Claude, score against a 30-point SEO rubric, reject anything under 8.0. Video-first: pull trending YouTube uploads, cache thirty days, have Claude evaluate the transcript, send survivors through the same draft. Both land in `drafts/` for a human look before `site/content/posts/`.
Topic page — 52 articles in one grid, filtered by season. Every card, hero, and excerpt generated by the pipeline.
A second surface
Every article gets a second life. I packaged everything — 74 articles, the product catalog, the QA rubric — into a custom GPT that answers lawn-care questions in conversation, grounded in the same content. Personalized by location and season. Same affiliate-aware recommendations. New pieces ship; the GPT knows the next day.
The Lawn Care Center GPT — the same content, in conversation form.
