Insight Vault

We express our understanding with labels like “insight”. Yet, this kind of clarity happens in a moment and usually doesn’t register until later. It cannot be fully captured, but we can keep a distilled piece of it as valuable data.

The Insight Vault is learning infrastructure for these instances. It’s an evolution of note-taking, a compression of trial and error, stored within a specific app or framework. There are private vaults to be used only internally and external vaults for the public to keep alive or let die. (You can gather around the campfire and share but if no one repeats it or writes it down, it is lost.) 

How you record your Insight Vault is unique to your line of work. It can be inside an HTML file, something physical, or some other container. You’ll gradually select what to fill the vault with, designing the entry as it happens. You cannot plan the context or takeaways and you can’t force insights with templates. 

There is also a difference between lived insight and secured insight. The highest signals are in the live sensations as they happen in real time. The recollection is for relaying to others. It’s the treasure you found after the adventure, not the story. Sure, what gets recorded is a degradation of the original but by changing it from an abstraction into something we can see, you provide everyone else with optionality. 

What does this look like with artificial intelligence in 2026? 

I’ll share a real example of setting up my Hermes agent on my private server. The process included screenshotting phases of challenging steps as I encountered them. Eventually, I used Claude Code to create an app for putting me in touch with like-minded professionals. It’s called Infrabot. Essentially, my agent researches people I would like to work with or connect with using a set of criteria and filters. After selecting prospects for a certain city it organizes the contact information inside the app and when I open it, bam! Everything is there ready for me to draft a message and send. That’s exactly what I did. And a few days later I was on a phone call with a real builder, having a real talk about publishing, marketing and AI/human dialogue. 

The insight for me here was that learning infrastructure will always be about demonstrating human skills in the real world. My agent proved it could research, select, and provide all the details of someone I could have a professional conversation with. Of course, I still had to answer the phone and discuss ideas on adapting with these new tools, still, the AI orchestration layer made the contact possible.

Naturally, with more intelligence there will be more tension between the buyers of this technology and the sellers. So, it’s worth addressing the elephant in the room, the economic value of sharing knowledge with the creators of frontier models. Microsoft’s CEO Satya Nadella recently wrote a great piece breaking this down called “The Reverse Information Paradox”. The thesis being that businesses have to feed models their proprietary knowledge, prompts, corrections, workflows, evaluations, and ‘exhaust’ to fully make them useful. Providers absorb this unique know-how, leaving companies paying twice: with dollars and their competitive edge. Learning flows primarily one way.

If you’re using the strongest models from Anthropic, xAI, OpenAI, and so on, we can look at a private Insight Vault as the proprietary knowledge Nadella is warning you about providing. Also, when the government forcefully suspended Anthropic’s Fable 5 on June 12th, only to bring it back a few weeks later, the approach of running models locally instead became more compelling. It grants privacy and consistency. The catch is, these open source models you run on your own machine are nowhere near as effective or capable as the latest available LLMs.

The silver lining is that artificial intelligence leaves us no choice but to get used to being wrong. Even in public. What stays true is what becomes our collection of doctrines, patterns and traps found the hard way. Call it anything you’d like, it’s still an asset, your very own infrastructure component.