Like most people in tech, I started using ChatGPT the way you'd use a search engine with better manners. Ask a question, get an answer, close the tab. It was useful, sometimes impressive, but it never really changed how I worked. The conversations were disposable — no memory, no continuity, no compounding value.
Then I started noticing something. The people getting real leverage from AI weren't just having smarter conversations. They were building systems around them. They were creating workflows where AI wasn't the destination — it was the infrastructure. That shift in framing changed everything for me.
The Turning Point
The turning point came when I discovered Claude Code. Not because it was a better chatbot — but because it operated differently. It could read my files, understand project context, remember decisions across sessions, and execute real work. It wasn't a tool I visited. It was a tool that lived inside my workflow.
“The best tools don't feel like tools at all. They feel like extensions of how you already think.”
Around the same time, I'd been deepening my use of Obsidian as a personal knowledge base. Notes, project plans, meeting takeaways, half-formed ideas — all living in interconnected markdown files. The problem was that these two systems didn't talk to each other. My AI assistant knew nothing about my notes, and my notes knew nothing about what my AI was helping me build.
Building the Bridge
So I built the bridge. What started as a simple sync script became an open-source project — Claude Code × Obsidian Sync — that connects my AI workflows to my knowledge graph. Now when I ask Claude to help me draft a product strategy, it can reference my past thinking. When I finish a coding session, the decisions and patterns get logged back into Obsidian automatically.
The result is something I've started calling a “personal operating system.” Not in the Silicon Valley productivity-guru sense. More in the literal sense: a system that operates on my behalf, carrying context forward so I don't have to re-explain myself every time I sit down to work.
It remembers that I prefer functional components over class components. It knows I'm building a personal website with Next.js and Tailwind. It recalls that last week I decided to use Crimson Pro for headings and Plus Jakarta Sans for body text. These small bits of persistent context add up to something that feels less like using a tool and more like working with a colleague who was in every meeting.
The lesson I keep coming back to is simple: the value of AI isn't in any single interaction. It's in the accumulation. When you stop treating AI as a search engine and start treating it as infrastructure — something that learns, remembers, and integrates — the returns compound in ways that feel genuinely transformative.
If you're still using AI the way I was a year ago — one-off questions, disposable chats — I'd encourage you to try something different. Pick one workflow. Build a small system around it. Let it get smarter over time. You might be surprised how quickly “good enough” AI becomes something you can't imagine working without.
