Trustworthy Data Analysis with Jupyter

Today’s episode

Claude Code just hit $2.5 billion in annualized revenue in 9 months.

It is the fastest B2B software product ramp in history.

So why are most people still using it like a chatbot?

This is how most people use Claude Code. Type a prompt and get output. The context fills up. It compacts. You lose everything. You start over.

The top users flipped it. They built skills that interview through a framework before building anything. They use sub-agents that preserve context. They have operating systems where every file, every person, every project has a home.

That shift is what today’s episode is about.

I sat down with Carl Vellotti for the third time. His first episode was the beginner course. His second episode was the advanced masterclass. Together they crossed over a million views across platforms.

Today is the operating system layer. If you are already an 80 out of 100 on Claude Code, this episode will bring you to a 95 out of 100.

This episode covers context management, creating sub-agents to manage your context for you, auto-triggering skills with hooks, trustworthy data analysis with Jupyter notebooks, and building an operating system around it all.

If you are living in Claude Code 8 to 10 hours a day and want to stop fighting the tool, this is the one episode to watch.

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I’m putting on a free webinar on Behavioral and AI PM interviews. Join me.

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Key Takeaways:

1. Context management is the real skill - A single web search eats 10% of your context. Run /context to see what is consuming it. System prompt and MCPs take 10-16% before you type one message.

2. Sub-agents save 20x context - Delegate research to a sub-agent. Same task costs 0.5% instead of 10%. Your main session only gets the summary.

3. Replace MCPs with CLIs - MCPs eat context by existing. CLIs have zero overhead. GitHub CLI, Vercel CLI, Google Workspace CLI are all dramatically more efficient.

4. Powerful skills need zero code - Anthropic's front-end design plugin is just a good prompt. No APIs or tooling. Just rules that tell Claude "do not look like AI."

5. Give Claude self-checking tools - The make slides skill uses Puppeteer to screenshot output, measure overflow, and fix issues before you see them.

6. Repeat prompts for better quality - A Google paper showed pasting a prompt twice helps. Tell Claude to double-check against skill instructions after the first pass.

7. Use hooks to auto-invoke skills - A user_prompt_submit hook matches your words against skill keywords instantly. Zero context cost.

8. Jupyter notebooks solve data trust - Every analysis shows exact code, inputs, and outputs. Traceable and reproducible.

9. Build an operating system - Knowledge folder for people context. Projects folder for task isolation. Tools folder for scripts. CLAUDE.md for identity.

10. The people folder compounds - Connect meeting transcription. After every meeting, update each person's dossier. Every prompt gets more specific over time.

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Related content

Podcasts:

* Claude Code Masterclass with Carl Vellotti (Ep 2)

* Claude Code PM OS with Dave Killeen

* OpenClaw Setup Guide with Naman Pandey

Newsletters:

* The ultimate guide to context engineering

* How to use Claude Code like a pro

* Claude Cowork and Code setup guide

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