Obsidian + Claude Code: Making Sense of the Chaos of Human Thought

"I know I had that brilliant idea about the sensor design. Was it in Tuesday's meeting notes? Or was it during that call with Caglar? Or maybe I just thought about it in the shower and never wrote it down?"

That was me, three weeks ago, staring at my Obsidian vault containing 47 daily notes, 23 meeting logs, and approximately 3,000 half-formed thoughts scattered across markdown files like confetti after a particularly chaotic party. The worst part? I knew the answer was in there somewhere. I just couldn't find it.

The Beautiful Mess of Human Documentation

Here's the uncomfortable truth that no productivity guru will tell you: human thoughts don't arrive in neat, categorised packages. They show up at 2am when you're trying to sleep, during boring Zoom calls about Q3 projections, or whilst you're supposed to be listening to your partner talk about their day.

I started using Obsidian eighteen months ago with the noble intention of "building a second brain." What I actually built was more like a digital representation of my actual brain: chaotic, interconnected in ways that only made sense at the time, and filled with cryptic notes like "sensor + membran = patent???" that seemed brilliant at 3am but incomprehensible two weeks later.

My vault became my everything-bucket. Every meeting, every conversation, every random thought that might be useful someday. Take my meeting with Caglar Cengizler about hardware design. In twenty minutes, we covered power management, MEMS vs piezo sensors, sampling rates, and whether ESP32 chips consume too much power. I captured it all in Obsidian, but three weeks later when I needed to remember our discussion about patent opportunities, I couldn't remember if it was in that meeting, the one with Semih about VCs, or buried in a daily note somewhere.

The system worked perfectly for capturing information. It was absolutely useless for finding it again.

The Daily Notes That Became a Diary

My daily notes folder tells the story of building SUNA Health better than any pitch deck ever could. Each file is timestamped with precision (2025-10-14.md, 2025-10-15.md), but the contents are pure stream of consciousness.

Look at my note from October 14th. It starts with "Met interesting people at Harvard event," jumps to warm introductions for VCs, then suddenly there's a massive list of European health tech investors pasted in. No context. No structure. Just raw information dumped into markdown because I didn't want to forget it.

This is how human memory actually works. We don't think in structured databases. We think in associations, in random connections, in "oh, that reminds me of..." moments. Obsidian captures this perfectly with its linked mentions and graph view, but finding specific information becomes like searching for a specific conversation you had at a party six months ago. You know it happened, you can almost remember who you were talking to, but the actual content? Gone.

Enter Claude Code: The Pattern Recognition Layer

Picture this: It's 11pm on a Sunday. I'm preparing for a VC pitch on Monday morning and I need to find every conversation I've had about medical device classification over the past three months. The traditional approach would be opening dozens of daily notes, skimming through meeting logs, hoping my past self used searchable keywords.

Instead, I opened my Obsidian vault in VS Code and typed into Claude Code CLI:

# Me at 11pm, slightly desperate
$ claude "Search through all my daily notes and meeting logs for any discussion about medical device classification, Class 2a, FDA, or regulatory pathways. Show me the actual conversations, not just where they're mentioned."

What happened next felt like magic but was actually just pattern recognition applied to chaos. Claude didn't just search for keywords. It understood context. It found the conversation with Semih where we discussed pivoting from Class 2a medical device to consumer wearable first. It found the note buried in a daily journal where I'd questioned whether athletic performance monitoring needed FDA approval. It even found a throwaway comment in a VC meeting note about "regulatory de-risking through consumer launch."

The real power wasn't in the search. It was in the synthesis. Claude presented these scattered thoughts as a coherent narrative: "Your thinking on regulatory strategy has evolved from pursuing immediate Class 2a certification (July) to a consumer-first approach that delays regulatory requirements (September) to a hybrid model targeting athletes while preparing for medical certification (October)."

I hadn't realised my thinking had evolved. I thought I was being inconsistent. Claude showed me I was actually iterating.

The Correlation Engine

The most valuable moments come from correlations I never saw coming. Last week, I asked Claude to analyse my vault for patterns in failed investor conversations. The prompt was simple:

$ claude "Look at all my meeting notes with VCs and investors. What questions keep coming up that I'm not answering well?"

Claude's analysis was brutal and brilliant. It found that every time someone asked about our competitive moat, I'd launch into technical specifications about acoustic monitoring. But when they asked about go-to-market strategy, I'd give clear, concise answers about targeting athletes and GLP-1 users. The pattern was obvious once Claude pointed it out: I was hiding behind technical complexity when I felt insecure about our differentiation.

The Implementation Reality

Let me show you the actual structure that makes this work. My Obsidian vault isn't sophisticated. It's deliberately simple:

# My vault structure - nothing fancy
/chad-meta-data
├── 2 - Areas/
│   ├── INVESTOR-RELATIONS/
│   ├── CONTENT-CREATION/
│   └── PRODUCT/
├── 5 - Daily notes/
│   └── [Every single day, documented]
├── 8 - Network/
│   └── [One file per person I meet]
└── 9 - Resources/

Each daily note follows the same non-structure. Date at the top, then whatever happened that day. Meetings get headers with double brackets to link to people. Thoughts get dumped wherever they land. No templates. No complicated properties. Just markdown and mess.

The Network folder is similarly simple. One file per person. Their LinkedIn if I remembered to grab it. Which meetings we've had. That's it. But when Claude analyses these connections, it can tell me things like "You've met with seven hardware engineers but only two have biomedical experience" or "Three of your advisor conversations mentioned the same competitor you've never researched."

The Forgotten Connections

The real magic happens when Claude finds connections I'd completely forgotten. Two months ago, in a daily note, I'd written a single line: "What if we could detect dehydration through bowel sound changes?" No context. No follow-up. Just a random thought dropped into markdown.

Last week, Claude connected that throwaway line to:

A meeting note where an athlete mentioned tracking hydration was their biggest challenge
A research paper I'd saved about acoustic signatures of intestinal fluid
A competitor analysis where I'd noted nobody was solving the hydration monitoring problem well
A conversation with a VC who said "find the one thing Whoop can't do"

Suddenly, that random 2am thought became a potential product differentiator. Without Claude's pattern recognition, it would have stayed buried in a daily note file, forgotten forever.

What Still Drives Me Mad

This system isn't perfect. Claude Code can't fix the fundamental problem that I still have to remember to write things down. The brilliant idea I had in the shower this morning? Gone forever because I didn't immediately capture it in Obsidian.

Claude also can't interpret my most cryptic notes. "Jim - sensor thing - Belgium???" means absolutely nothing to Claude (or to me, three weeks later). The correlation engine is only as good as the data I feed it, and sometimes my data is just terrible.

The most frustrating limitation is that Claude analyses what I write, not what I mean. When I write "Meeting went well," Claude takes that at face value. It can't detect the sarcasm, the disappointment, the fact that "went well" is my code for "absolute disaster but I'm too tired to process it right now."

The Uncomfortable Truth About Augmented Thinking

Here's what nobody tells you about using AI to analyse your thoughts: it's like having a therapist who's read your entire diary. Claude has shown me patterns I didn't want to see.

The fact that I avoid hard technical problems on Mondays. The reality that I'm more creative when I'm slightly tired. The uncomfortable truth that my best insights come when I'm not trying to have insights.

It's also shown me how much of my thinking is just recycling the same ideas in slightly different words.

Lessons Learned (The Hard Way)

Write everything down, even if it seems stupid: That random thought about membrane acoustics turned into a potential patent opportunity. But only because I captured it.
Don't try to organise while capturing: My attempts to categorise thoughts in real-time always failed. Dump now, organise later (or let Claude do it).
Link people obsessively: Every person gets a note. Every meeting links to people. Claude can map your network better than you can.
Date everything: Without timestamps, Claude can't show you how your thinking evolved. With them, it can show you your own intellectual journey.
Accept the mess: My vault is chaos. That's fine. Human thoughts are chaotic. The organisation happens at analysis time, not capture time.

The Integration That Changed Everything

The technical setup is embarrassingly simple. Open vault in VS Code. Run Claude Code CLI. Ask questions. But the workflow becomes profound when you realise you're not searching your notes anymore. You're having a conversation with your documented thoughts.

# A typical Sunday night session
$ claude "What did I promise to deliver this week?"
$ claude "Which investors showed genuine interest vs polite interest?"
$ claude "What technical problems am I avoiding?"
$ claude "Find ideas I've had but never followed up on"

Each query returns not just search results but synthesised insights. Patterns I didn't see. Connections I didn't make. Promises I forgot I made.

What Comes Next

Next week, I'm experimenting with having Claude generate weekly summaries of my thought patterns. The week after, I'm going to try using it to predict which investors are most likely to write cheques based on conversation patterns.

But honestly? The biggest value is simpler than that. It's knowing that every random thought, every meeting note, every 2am frustration journal entry is no longer lost to the chaos of human memory. It's all there, waiting to be understood, connected, synthesised into something useful.

My Obsidian vault is still a mess. But now it's a mess with a pattern recognition layer. And that makes all the difference.

Note: If you're thinking about trying this yourself, start simple. One folder for daily notes. One folder for people. Write everything down. Don't worry about structure. Let the mess accumulate for a month, then point Claude at it and ask: "What patterns do you see?" The answers will probably disturb you. They'll definitely surprise you. And occasionally, they'll show you something brilliant you didn't know you knew.

Technical Setup:

Obsidian for capture (any version)
VS Code as IDE
Claude Code CLI (installed via npm)
No plugins, no complex workflows, no proprietary systems
Just markdown, mess, and machine learning

The revelation isn't in the technology. It's in discovering that your chaotic thoughts, properly analysed, contain more wisdom than you realised. You just needed help finding it.