| name | ai-engineer-learning |
| description | YouTube transcript ingestion pipeline and RAG query interface for the AI Engineer persona. All 763 @aiDotEngineer channel videos indexed in Qdrant. Run weekly to stay current. |
| compatibility | Created for Zo Computer |
| metadata | {"author":"marlandoj.zo.computer"} |
AI Engineer Learning Skill
Consumes, indexes, and queries the entire @aiDotEngineer YouTube channel — a leading source of AI engineering talks from Google DeepMind, Anthropic, OpenAI, Hugging Face, and more.
Current Status (2026-06-15)
- 822 Qdrant points across 763 unique videos
- 44 videos — full transcript-backed (deep chunk embeddings)
- 719 videos — metadata-indexed (title + duration + URL, still semantically searchable by topic)
- Collection:
ai-engineer-videos @ 127.0.0.1:6333
When to Use
- The AI Engineer persona is working on Zouroboros and needs current best practices
- Building agents, RAG systems, evals, MCP servers, or AI infrastructure
- Need to reference talks on: agent architecture, context management, evaluation, MCP, RAG, model deployment, voice AI, multi-agent systems, observability
- Weekly: run the update pipeline to ingest new videos
Query the Knowledge Base
bun Skills/ai-engineer-learning/scripts/query.ts "how to build durable agents"
bun Skills/ai-engineer-learning/scripts/query.ts "context management" --top 10
bun Skills/ai-engineer-learning/scripts/query.ts "evaluation frameworks"
Ingestion Pipeline
Add New Videos (weekly sync)
cd /home/workspace/Skills/ai-engineer-learning/scripts
bun update-channel.ts
python3 ingest-metadata.py
bun process-transcripts.ts
Upgrade Metadata → Transcript (when articles are available)
bun Skills/ai-engineer-learning/scripts/process-transcripts.ts
NotebookLM Path (richer knowledge, needs Google session)
Use this for natural language deep-dives on topics. Requires valid NotebookLM cookies.
cd /home/workspace/Skills/notebooklm-skill/scripts
python3.12 nlm.py status
python3.12 /home/workspace/Skills/ai-engineer-learning/scripts/load-to-notebooklm.py
python3.12 nlm.py ask --notebook <nb_id> --question "best practices for agent memory"
Files
scripts/ingest-metadata.py — Metadata-only Qdrant indexer (no YouTube access needed)
scripts/ingest-batch.py — Full transcript Qdrant indexer (requires residential IP / save_webpage)
scripts/process-transcripts.ts — Embeds Articles/ markdown saves into Qdrant
scripts/load-to-notebooklm.py — Bulk-add YouTube URLs to NotebookLM notebooks
scripts/query.ts — Semantic search + research notebook generator
Projects/ai-engineer-learning/channel-videos.txt — Video metadata catalog (763 videos)
Projects/ai-engineer-learning/processed.json — State file (tracks ingested videos)
Projects/ai-engineer-learning/notebooklm-notebooks.json — NotebookLM notebook IDs (after load)
Scheduled Agent
Weekly agent [ZBR] Ingest AI Engineer Videos runs every Monday at 0200 UTC:
source /root/.zo_secrets && python3 /home/workspace/Skills/ai-engineer-learning/scripts/ingest-metadata.py
This indexes new videos from channel-videos.txt and embeds them into Qdrant.