content-media.md

Content and Media Ingestion

Goal

YouTube videos, social media, PDFs, and documents become searchable brain pages with the agent's own analysis and full cross-references to every entity mentioned.

What the User Gets

Without this: media links are bookmarks that decay -- you remember watching a video but can't find what was said, who said it, or why it mattered. With this: every piece of media is a permanent brain page with the agent's analysis layered on top, every mentioned entity gets a back-link, and the full content is searchable forever.

Implementation

on user_shares_media(url_or_file):

    # PATTERN 1: YouTube Video Ingestion
    if media.type == "youtube":
        # Step 1: Get FULL transcript with speaker diarization
        #   WHO said WHAT -- not just a wall of text
        #   Use Diarize.io or equivalent service
        transcript = diarize(video_url)  # speaker-attributed transcript
        # NEVER use YouTube's auto-generated summary or AI summary

        # Step 2: Agent writes OWN analysis (this is the value)
        #   NOT a summary. NOT regurgitation. The agent's TAKE:
        #   - What matters and why (given the user's worldview)
        #   - Key quotes attributed to specific speakers
        #   - Connections to existing brain pages
        #   - Implications and follow-up angles
        analysis = agent_analyze(transcript, user_context)

        # Step 3: Create brain page
        slug = f"media/youtube/{video_slug}"
        gbrain put <slug> --content """
            # {title}
            **Channel:** {channel} | **Date:** {date} | **Link:** {url}

            ## Analysis
            {agent_analysis}

            ## Key Quotes
            - **{Speaker}** ({timestamp}): "{quote}" -- {why_it_matters}

            ---
            ## Full Transcript
            {diarized_transcript}
        """

        # Step 4: Extract and cross-reference entities
        for person in transcript.mentioned_people:
            gbrain add_link <slug> <person_slug>
            gbrain add_link <person_slug> <slug>
            gbrain add_timeline_entry <person_slug> \
                --entry "Discussed in {video_title}: {what_was_said}" \
                --source "YouTube: {url}"

    # PATTERN 2: Social Media Bundles
    elif media.type == "tweet" or media.type == "social":
        # Don't just save a tweet -- reconstruct FULL context
        bundle = {
            "original": fetch_tweet(url),
            "thread": reconstruct_thread(url),        # quoted tweets, replies
            "linked_articles": fetch_linked_urls(),    # fetch and summarize
            "engagement": get_engagement_data(),       # what resonated
        }

        slug = f"media/social/{platform}-{author}-{date}"
        gbrain put <slug> --content """
            # {author}: {topic}
            {agent_analysis_of_full_bundle}

            ## Thread
            {reconstructed_thread}

            ## Linked Articles
            {article_summaries}

            ---
            ## Raw
            {original_tweet_text}
        """

        # Extract entities and cross-reference
        for entity in bundle.mentioned_entities:
            gbrain add_link <slug> <entity_slug>
            gbrain add_link <entity_slug> <slug>

    # PATTERN 3: PDFs and Documents
    elif media.type == "pdf" or media.type == "document":
        # OCR if needed (scanned PDFs)
        content = ocr_if_needed(file) or extract_text(file)

        # For books and long-form:
        slug = f"sources/{document_slug}"
        gbrain put <slug> --content """
            # {title}
            **Author:** {author} | **Date:** {date}

            ## Chapter Summaries
            {per_chapter_summary}

            ## Key Quotes
            - p.{page}: "{quote}" -- {why_it_matters}

            ## Cross-References
            {links_to_brain_pages_for_people_and_concepts}

            ---
            ## Source
            {full_text_or_key_sections}
        """

        for entity in document.mentioned_entities:
            gbrain add_link <slug> <entity_slug>
            gbrain add_link <entity_slug> <slug>

    # Always sync after ingestion
    gbrain sync

Tricky Spots

1. Always FULL transcript, never AI summary. YouTube's auto-summary and AI-generated summaries lose the texture: who said what, exact phrasing, tone, what was left unsaid. The full diarized transcript is the evidence base. The agent's analysis goes above it.
2. The agent's OWN analysis is the value, not regurgitation. "The video discussed AI safety" is worthless. "Dario made a specific claim about compute scaling that contradicts what Ilya said in the NeurIPS talk -- see media/youtube/ilya-neurips-2025" is useful. The analysis connects the new media to the existing brain.
3. Social media is a bundle, not a single tweet. A tweet without its thread, quoted tweets, linked articles, and engagement context is a fragment. Reconstruct the full context before creating the brain page.
4. Cross-references make media pages alive. A YouTube page without back-links to the people and companies mentioned is a dead archive. Every mentioned entity gets a link and a timeline entry.
5. Over time, media/ becomes a searchable archive. Every video, podcast, talk, interview, article, and tweet the user has consumed, with the agent's commentary layered on top. This is the memex at full power.

How to Verify

1. Ingest a YouTube video. Run gbrain get media/youtube/{slug}. Confirm the page has: the agent's analysis (not just a summary), key quotes with speaker attribution, and the full diarized transcript.
2. Run gbrain get_links media/youtube/{slug}. Confirm back-links exist to brain pages for every person and company mentioned in the video.
3. Pick a person mentioned in the video. Run gbrain get <person_slug>. Confirm their timeline has a new entry referencing the video with specific context.
4. Ingest a tweet. Confirm the brain page includes the thread context, linked article summaries, and entity cross-references -- not just the tweet text.
5. Run gbrain search "{topic_from_video}". Confirm the media page appears in search results (verifies the content is indexed and searchable).

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Part of the GBrain Skillpack.