I built a tier list that re-rates 245+ AI tools every week — the automation behind it

AI tool reviews rot faster than anyone can rewrite them. A tool that was S-tier in March ships a broken pricing change in June, a "top 10" listicle from last year recommends products that no longer exist, and every directory slowly turns into a graveyard of dead links. I run AI Tier List , a bilingual (EN/KO) directory that ranks 245+ AI tools from S to D. My answer to review rot: don't re-review by hand. Make a pipeline re-rate everything weekly, and let humans only approve or reject. The architecture Everything runs on one weekly GitHub Actions cron (Next.js 16 + Prisma + Neon Postgres + Vercel): weekly cron (Sun 00:00 UTC) ├─ collect Google Trends per tool → trend scores ├─ collect OpenRouter usage rankings → weekly LLM leaderboard ├─ deactivate dead tools → site checks + trend slump ├─ discover new tools → search + AI triage ├─ re-evaluate tiers (LLM) → PendingUpdate rows └─ generate weekly blog draft → MDX The key design decision: the LLM never writes directly to the live site. Re-evaluations land in an approval queue ( PendingUpdate table). I review diffs in an admin panel and approve batches. The pipeline proposes; a human disposes. That one boundary is what keeps automated content from becoming automated garbage. Two collectors do the heavy lifting: Trend collector — Google Trends per tool, weekly. A tool in a sustained slump gets flagged; if its website also starts failing health checks, it gets deactivated automatically. Dead products remove themselves from the directory. OpenRouter collector — real token-usage data powers a weekly LLM leaderboard . No opinions, just "which models did people actually route traffic to this week," with usage share, pricing, and context length. What the tier actually means Each tool stores bilingual tierReason , strengths , and weakness fields, and the tier maps S→5 … D→1 into review schema markup. When the weekly re-evaluation moves a tool, the reason is regenerated with it — so the rating and its justification never drift a