Current:
New: While the existing plan covers content automation with Claude Code, this new reel specifically demonstrates the integration of Google's NotebookLM CLI *within* Claude Code to generate visual assets (infographics, slide decks) and structured PDFs from source documents, which is a new dimension of content automation beyond just text or video scripts.
Current:
New: This reel introduces 'grounding' visual generation in NotebookLM using uploaded brand assets (CLAUDE.md, marketing docs) to ensure on-brand output for infographics and slide decks. The existing plan focuses more on scraping and general build automation, not the nuanced, multi-modal asset generation from structured brand documents.
Current:
New: The existing plan discusses Meta Ads at a strategic level for B2B scaling and lead quality. This new reel provides a direct, tactical automation for producing Meta Ads *creative assets* (square/vertical visuals) directly from technical product documentation using NotebookLM Studio, solving a content bottleneck for ad creation rather than just tracking performance.
Automate visual proposal and content asset generation by integrating NotebookLM CLI into Claude Code commands, eliminating manual design work for TFWW and DDB collateral.
Create /proposal-gen Claude tool that takes TFWW service specs + client requirements, uploads to NotebookLM, generates custom PDF proposal with portfolio infographics instead of static Google Docs
Build DDB knowledge base in NotebookLM (content pillars, brand guide, past posts) and create Claude tool /content-brief that generates carousel outlines and visual direction for Instagram content
Auto-generate updated system architecture PDFs from Express route files and Supabase schemas using NotebookLM CLI hooked into deployment pipeline
We should integrate this into our ReelBot execution pipeline — use NotebookLM to synthesize knowledge base docs before generating HTML execution plans
The Agent Playbook PDF you showed at the end — is that generated entirely from your repo's CLAUDE.md or do you curate the sources manually? Looking to automate our technical docs.
pip install notebooklm-py, pip install "notebooklm-py[browser]", playwright install chromium enables headless NotebookLM automation.claude/commands/ or skills directory that wrap notebooklm-py CLI calls/docs/ folder/lead-magnets maps to complex multi-step generation (sources + studio + export)What it is: Integration of Google's NotebookLM Python CLI with Claude Code custom tools to programmatically generate visual marketing assets (infographics, slide decks) and documentation PDFs from curated source documents. Uses NotebookLM's Studio feature for visual output and browser automation via Playwright.
How it helps us: We already use Claude Code extensively (Claude Upgrades project). This adds capability to auto-generate TFWW service guides, DDB content playbooks, and AIAS documentation from our existing markdown specs. ReelBot already analyzes videos; NotebookLM would synthesize our existing knowledge bases into client-facing PDFs and portfolio presentations without manual design work.
Limitations: Requires Python/Pip stack addition whereas our backend is Node/Express. We already have automated content analysis via ReelBot and could replicate PDF generation via Puppeteer/Playwright ourselves. NotebookLM has usage limits and requires uploading proprietary docs to Google (potential data sensitivity for AIAS client data). The visual output may not match TFWW's specific branding without heavy customization.
Who should see this: Dylan for content strategy (DDB/TFWW lead magnets), Dev team for documentation automation, potentially AIAS for client report generation if data sensitivity is addressed
| Step | Prompt | Completion | Cost |
|---|---|---|---|
| analysis | 11,715 | 2,532 | $0.0108 |
| similarity | 1,509 | 600 | $0.0006 |
| plan | 7,936 | 5,720 | $0.0162 |
| Total | $0.0276 | ||