/youtube-pipeline

Extract knowledge from YouTube videos and store permanently in BrainLayer.

Pipeline

YouTube URL
    ↓
1. exa web_search (full URL as query)
    → title, transcript, metadata
    ↓
2. brain_digest (raw transcript + metadata)
    → entities, relations, action items, decisions
    ↓
3. brain_store (structured conclusions)
    → searchable knowledge forever

Usage

When user shares a YouTube link:

Step 1: Extract via Exa

web_search_exa(query: "https://youtube.com/watch?v=VIDEO_ID", num_results: 1)

Exa returns: title, URL, full transcript text, publish date, author.

IMPORTANT: WebFetch does NOT work for YouTube. Always use exa.

Step 2: Digest raw content

brain_digest(content: "<title>\n<author>\n<date>\n\n<full transcript text>")

This extracts: entities (people, tools, companies), relations, sentiment, action items, decisions, questions. Creates a searchable chunk with source='digest'.

Step 3: Store conclusions

brain_store(
  content: "Video: '<title>' by <author> (<date>)\nURL: <url>\n\nKey findings:\n1. ...\n2. ...\n3. ...\n\nAction items:\n- ...\n\nRelevant to: <projects>",
  tags: ["youtube", "<author-slug>", "<topic-tags>"],
  importance: 6-8
)

Step 4: Report to user

Summarize:

• Video title and author
• Top 3-5 key takeaways
• Action items (things to build/try/investigate)
• How it connects to current projects
• BrainLayer chunk IDs for future reference

Batch Mode

For multiple videos (e.g., a playlist or "process these 5 videos"):

1. Run exa searches in parallel (up to 5 concurrent)
2. Digest each transcript
3. Store individual conclusions + one synthesis
4. Report all findings in a single summary

Tag Convention

Tips

• Exa sometimes returns partial transcripts for very long videos (3h+). Note this in the summary.
• For livestreams/podcasts, extract the segments that matter — don't store 3 hours of chat.
• If exa returns no transcript, try web_search_exa("<video title> transcript") as fallback.
• Cross-reference findings with existing BrainLayer knowledge: brain_search("<key topic>") before storing to avoid duplicates.