I Learn Faster Than 99% of People. NotebookLM + Claude Code + Obsidian
๐ Obsidian x Claude Code Lab (starts May 5): https://lab.artemzhutov.com
90% of people listen to experts and never change a single behavior. They stay in learn mode. I built a system that closes the loop. From research to experiments to daily enforcement to review.
Feed 300 Huberman episodes into NotebookLM. Connect Claude Code to it. Claude asks expert-informed questions about your specific goal. You get a protocol with experiments based on your answers. Set it up in 20 minutes.
NotebookLM skill. Open source. Grab it in the description. Three commands to start.
Follow me:
Substack: https://artemxtech.substack.com/
X: https://x.com/ArtemXTech
GitHub: https://github.com/ArtemXTech
Timestamps:
0:00 90% never change a single behavior
0:42 My goal: more energy, gym, focus
0:55 What NotebookLM actually does
1:32 Connecting Claude Code to NotebookLM
1:47 Loading 300 Huberman episodes from terminal
3:18 188 sources appearing in real time
3:56 "Where do I start with health?"
4:51 The real problem: learning without acting
6:06 How Claude Code bridges the gap
7:21 Real gym data: mood and energy correlation
8:27 Morning routine that tracks experiments
9:03 Live: designing health experiments from 200 episodes
10:09 Expert-informed interview questions
12:02 From research to personalized protocol
13:50 Top 3 highest-leverage experiments
14:55 Experiments land in your daily note
15:32 Morning routine skill asks how it's going
16:40 Health dashboard: everything at a glance
16:52 Lab Cohort 3 starts April 28
17:06 The vision: any expert, any domain
17:55 The highest leverage thing you can do
Watch on YouTube โ
(saves to browser)
Sign in to unlock AI tutor explanation ยท โก30
Related AI Lessons
โก
โก
โก
โก
The ABCs of reading medical research and review papers these days
Medium ยท LLM
#1 DevLog Meta-research: I Got Tired of Tab Chaos While Reading Research Papers.
Dev.to AI
How to Set Up a Karpathy-Style Wiki for Your Research Field
Medium ยท AI
The Non-Optimality of Scientific Knowledge: Path Dependence, Lock-In, and The Local Minimum Trap
ArXiv cs.AI
Chapters (21)
90% never change a single behavior
0:42
My goal: more energy, gym, focus
0:55
What NotebookLM actually does
1:32
Connecting Claude Code to NotebookLM
1:47
Loading 300 Huberman episodes from terminal
3:18
188 sources appearing in real time
3:56
"Where do I start with health?"
4:51
The real problem: learning without acting
6:06
How Claude Code bridges the gap
7:21
Real gym data: mood and energy correlation
8:27
Morning routine that tracks experiments
9:03
Live: designing health experiments from 200 episodes
10:09
Expert-informed interview questions
12:02
From research to personalized protocol
13:50
Top 3 highest-leverage experiments
14:55
Experiments land in your daily note
15:32
Morning routine skill asks how it's going
16:40
Health dashboard: everything at a glance
16:52
Lab Cohort 3 starts April 28
17:06
The vision: any expert, any domain
17:55
The highest leverage thing you can do
๐
Tutor Explanation
DeepCamp AI