A One-Person Content Factory: The SOP for 30 Short Videos a Day with AI

OOPCMan 编辑部2025-10-15约 8 Min. Lesezeit6715 Aufrufe
A One-Person Content Factory: The SOP for 30 Short Videos a Day with AI
TL;DR

A Changsha creator runs a pipeline producing 30 short videos daily: n8n for topics, LLMs for scripts, Dreamina/Kling for visuals, AI voiceover, scheduled distribution — about 300 CNY per month with 2 hours of daily human time. In 30 days: 912 videos and 24M views, with 3% of videos driving 70% of views. The pipeline solves volume; taste still makes hits. Master the manual process before automating.

The Pipeline: Five Stages

The goal is not full automation but freeing the human from repetitive work: topics accumulate automatically, scripts are AI-drafted, visuals are template-generated, distribution is scheduled across platforms, and analytics flow back for review. The human does exactly two things — final topic approval and key on-camera or voiceover judgment.

Tool Stack per Stage

StageToolsMonthly Cost
Topic sourcingn8n scraping hot lists and RSS50 CNY
Script draftingKimi / ChatGPT0-99 CNY
VisualsDreamina + Kling + CapCut templates100 CNY
VoiceoverMoyin / ElevenLabs60 CNY
Distribution and reviewPlatform schedulers + Feishu dashboards0 CNY

Total cost is about 300 CNY per month, with output comparable to a 4-person short-video team.

Three Quality Gates

  • Topic gate: of 50 AI-suggested topics, the human keeps 10 — an 80% rejection rate;
  • Fact gate: every script with data or citations gets manually verified — AI drafts carry roughly 5% factual errors;
  • Platform gate: each video passes a sensitive-word and compliance check before publishing.

One Month of Production Data

In 30 days the pipeline produced 912 videos — 30 per day — with 24 million total views. Three percent of the videos drove 70% of the views. The creator spent about 2 hours daily, mostly on topic review and hit analysis. The lesson is clear: the pipeline solves volume; hits still come from human taste.

Advice for copycats: run the full process manually 20 times before automating anything. Automating a broken manual process only produces garbage faster.

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