Obsidian + AI: How to Do It The Right Way (Claude Code + Obsidian)

Overview

The video argues for using AI with Obsidian in a way that protects Obsidian’s core strengths—offline use, privacy, and user-owned Markdown vaults—while still gaining AI’s benefits for research and analysis. It frames AI adoption as “offense + defense”, rather than adopting AI everywhere.

Key technological concepts & approach

Why not just add AI everywhere in Obsidian

• Obsidian is positioned as a “sacred thinking space / idea verse.”
• The emphasis is on preserving the user’s own voice, rather than generating or diluting it with outside content.
• AI is still valuable, but only when used in narrowly scoped workflows.

IDI framework (for safer + more effective AI use)

1. Imagine: Use AI to propose possibilities.
2. Discern: Verify and reject inaccuracies, while keeping useful parts.
3. Integrate: Connect results back into the user’s broader life/work (their “idea verse,” including roles and creative archetypes).

Barbell strategy for AI

• Defense

  • Avoid overgenerating: prevent AI-written text from overwhelming the user’s own writing.
  • Privacy policy spectrum
    • Local (safest): no network communication.
    • Cloud services like ChatGPT (riskiest): training risk; not private.
    • Middle ground: cloud-hosted execution without training on user data, only for limited time (example described later).

• Offense

  • Use AI for reflection (surface themes from past work).
  • Use AI as the “tip of the spear” for deep research.
  • Create a dedicated “AI zone” (e.g., separate folder/vault) so AI-generated content has friction before it’s merged into the core notes.

Product/tool recommendation: Claude Code + Obsidian

The main practical setup is Obsidian + Claude Code (Anthropic).

Claude Code is described as an LLM tool that can:

• Chain multiple steps and execute tasks using the user’s local files/folders
• Analyze, edit, restructure notes directly in the Obsidian vault (since notes are local)
• Optionally spin up sub-agents and do web research (described generally)

The video highlights benefits tied to Obsidian’s storage model:

• Notes remain simple Markdown files owned by the user
• Reduced lock-in compared to proprietary online tools

Demonstrated workflows (examples)

1. Analyze the last ~45 days of notes

   • Claude Code generates a summary stored in a separate AI-dedicated Obsidian vault/folder
   • Example outputs include themes like:
     • focus areas (e.g., writing)
     • emotional/trajectory descriptions
     • reflections on modes such as “producer mode vs creative mode”
     • routines, environment, business, workshop insights

2. Text pattern / to-do style analysis

   • Claude Code searches for every mention of a phrase (e.g., “idea verse”)
   • Produces findings like:
     • occurrence count
     • peak usage timeframe
     • a structured table of results
   • The key point: AI outputs must still be reviewed for truth (“discernment”).

3. Metadata enrichment via online lookup

   • Example: for person notes with a metadata field like image
   • Claude Code goes online per entry to fetch images and populate fields automatically

4. “Good friction” approach

   • AI output is written to an AI vault/zone, not directly into the main idea verse
   • This requires deliberate human review/selection before merging

What the video claims about Obsidian’s future (AI inside Obsidian)

Current state

• No built-in AI in Obsidian
• AI is described as “not on the road map”

Kapano’s arguments (quoted/cited)

• Avoid the “arms race” mentality of adding AI to everything.
• Only add AI if it can be private (no training on user data).
• Privacy principles are central, contrasting Obsidian with cloud suites that mine data.
• End-to-end encrypted mention is included as part of the privacy framing.
• Obsidian should preserve user confidence and thinking ownership.

Philosophical context

• “Pen and paper” remains one of the best tools for thought.
• Obsidian’s core value is linking notes via links—a simple, durable form of sensemaking.

Guides/tutorial cues & “how-to” structure

The video provides a method built around:

• Applying the IDI framework
• Using the defense/offense barbell
• Implementing with Claude Code + Obsidian
• Maintaining an AI-dedicated vault/folder for generated content
• Backing up notes before running automated edits

It also references additional details available via a QR code to a related “build”/series (not included in the subtitles).

Main speakers/sources

• Nick Milo — host; narrator
• Kapano — Obsidian CEO; quoted about Obsidian’s AI philosophy and roadmap
• Claude / Claude Code (Anthropic) — the AI system described as used in the workflow