Tim asked me the other day about Claude getting YT video content. I haven’t had any problems with Claude Code or Jarvis doing this for me, but it relies on me searching YT. So, I just built a YT Info Diet. It runs locally using Apify (free plan) and my Claude Code subscription. It runs every 12 hours, excludes Shorts and send the summary with a reco to my Slack. I gave it a list of channels to “watch” YouTube Channel Intelligence Monitor — Setup Guide Auto-summarize new YouTube videos from your favorite channels every 12 hours, with watch/skim/skip verdicts delivered to Slack. No API costs (uses Claude Code subscription). What You'll Get Every 12 hours, the monitor checks your favorite YouTube channels. When a new long-form video drops, it: 1. Fetches the transcript 2. Sends it to Claude for analysis 3. Posts a structured intelligence brief to Slack with WATCH / SKIM / SKIP verdict, summary, key insights, and an actionable playbook 4. Saves a markdown report locally YouTube Shorts are automatically filtered out. --- Prerequisites - macOS (this guide; Linux works too with cron instead of launchd) - Python 3.9+ - https://claude.com/claude-code installed and logged in (claude command working) - https://github.com/yt-dlp/yt-dlp — pip install yt-dlp - An https://apify.com account (free tier is fine — used as transcript fallback) - A Slack workspace where you can create webhooks --- Step 1 — Install Python Dependencies pip3 install feedparser youtube-transcript-api slack-sdk pyyaml Step 2 — Get Your Apify Token 1. Sign up at https://apify.com (free) 2. Go to Settings → Integrations → API tokens 3. Copy your token (starts with apify_api_...) Step 3 — Create a Slack Incoming Webhook 1. Go to https://api.slack.com/apps → Create New App → From scratch 2. Name it "YT Monitor", pick your workspace 3. In sidebar: Incoming Webhooks → toggle ON

Token management is real. I've seen people burn $10 in 2 minutes without realizing it. Here's the framework: → NEVER use your expensive model (Opus) for heartbeat/monitoring. Use Gemini Flash or a cheap local model. That alone can save you hundreds per month. → Use sub-agents for simple tasks. Your main brain should delegate, not do everything itself. → Watch your context size. The bigger the context, the more tokens every single message costs. Keep it lean. → Set up token tracking. Run /status regularly. Know what you're spending. → Don't paste your entire chat history into every prompt. Be surgical with context. Realistic budget: If you're smart about routing, you can run a solid AI agent setup for $100-200/month on API. If you're sloppy, you'll hit $500+ easy. The golden rule: if it makes money, there is no budget. Do more of it. But TRACK what's making money vs what's just cool. Don't trip over dollars to pick up pennies.

So Anthropic announced they built a new model called Claude Mythos and then decided NOT to release it to the public because of safety concerns. First time a major AI lab has done this. And honestly, the ecom community should pay attention to why this matters. Here's the thing. This tells us these models are getting seriously powerful, fast. If a lab is building something they're scared to ship, you can bet the stuff they ARE releasing is already more capable than most sellers are using day to day. Most people in this community are still using AI to write a product bullet or two. The gap between what's possible and what people actually do is massive. For our businesses, the practical takeaway is this: don't wait for the "perfect" model before you build real AI workflows. The tools we have right now, Claude, GPT-4o, Gemini, are already good enough to cut your customer service ticket time in half, generate 30 ad creative variations in an hour, and rewrite your entire listing catalog in a weekend. The ceiling keeps moving up but the floor is already high enough to build on. The other thing worth thinking about is trust. Anthropic choosing not to ship something because it wasn't safe yet is actually a signal that they take the reliability of their tools seriously. For sellers running automated review responses, AI-generated ad copy, or supplier negotiation scripts, that matters. You want the company behind your tools to have some standards. Bottom line, the AI race is moving faster than any of us expected. The sellers who win aren't going to be the ones who waited for the best model. They're going to be the ones who built repeatable systems with what's available right now and iterated from there. What's one workflow in your store, could be ads, listings, support, anything, where you know AI could help but you just haven't set it up yet?

Mondays: 11am phx time - Getting Started with ClaudeCode Thursdays: 11am phx time - Advanced Strategy All call links are in the Calendar tab

Both pdfs have been added to the Classroom