How We Built a YouTube SEO Pipeline with AI Agents

Описание и применение

Автоматизированная система из трёх AI‑агентов управляет исследованием тем, созданием сценариев, рендерингом видео, SEO‑оптимизацией, загрузкой и аналитикой, позволяя публиковать более 250 видео без облачных сервисов.

Задача

Running a YouTube channel requires continuous research, scripting, rendering, uploading, and analytics, which becomes overwhelming for a solo developer team.

Результат

Deployed 250+ videos across 7 waves with zero cloud TTS/rendering costs, 95% metadata issue detection before upload, and a 48‑hour analytics loop driving data‑driven topic selection.

Рабочий процесс

• 1. Agents scan tech trends and competitor channels for topics, fact-verify and tag keywords.
• 2. AI generates scripts following a strict blueprint (hook, content, engagement, anti-CTA, debrief, timeline).
• 3. Piper TTS generates voiceover offline; FFmpeg renders video with subtitles and effects.
• 4. SEO optimization applies description blueprint, hashtags, timestamps, and title A/B testing.
• 5. Upload scheduling script manages resumable uploads, quota tracking, scheduled publishing, and quality gates.
• 6. Analytics pulls daily reports via YouTube Reporting API, feeding back into topic selection and title optimization.

Доказательства

250+ videos deployed across 7 waves

Источник

Zero cloud APIs for TTS and rendering (100% offline)

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Automated quality gates catch 95% of metadata issues before upload

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