Understanding Runs
I was staring at a tree. Not a real one, but the digital kind I had been building for years. And then I started imagining something behind it.
What if you took all the leaves of a tree and grew them outward? Not back toward the trunk, but away from it. Each leaf becomes the starting point of a new structure, a second tree that fans out from the edges of the first one. The leaves compress together, merge, and eventually converge into their own root. A shadow tree growing outward from the original, with its own shape and its own root at the far end.
That was the first image. A separate tree, external, built from the endpoints of the real one. I played around with that idea for a while. But the more I thought about it, the more I realized the shadow tree was not something that lived outside the original. It was something that lived behind it. Every node in the tree already had a shadow. The structure was not new. It was already there, one layer deeper, holding a place where meaning could be stored separately from the content itself. Not changing the tree, not restructuring it, just quietly existing behind each node, waiting to hold a compressed understanding of what that branch contained.
That is how understanding nodes were born.
Before I ever wrote a line of code for this, I had a moment at the beach that rewired how I think about information back in 2022.
I was lying in the sand, and I had been playing with this seashell. At some point I dropped it beside me, and when I reached back for it, it was gone. I spent a solid twenty minutes feeling around in the sand next to me in a light sun drunken daze. Patting, sifting, reaching further out. Nothing.
Arlo had apparently been watching the whole time. After a while he just said, "It's a little lower to the right."
I moved my hand down and found it immediately.
Twenty minutes of searching. One sentence from someone with a different vantage point. That is what a new perspective does. It does not add information. The seashell was always there. The sand had not moved. But from where I was lying, I could not see what Arlo could see. His perspective revealed what mine could not.
That is why I chose the word "perspective" for what drives an understanding run. Because that is literally what it is. You are distilling information down from a point of view, and the point of view changes what gets revealed and what becomes compressed. If the beach that day were a tree, you could run two understanding perspectives across it. Mine would have encoded something like "seashell lost somewhere to my right, sand feels uniform, no distinguishing landmarks by touch." Arlo's would have encoded "seashell visible at his lower left, he keeps reaching too high." Same tree. Same nodes. Same sand. Completely different understanding based on where you are standing when you look at it.
In the system, that is exactly how it works. You can run multiple perspectives across the same tree, and each one lives on the same shadow node, coexisting. The tree does not change. Your understanding of it does.
Here is how the compression actually works, without getting into the code.
The system starts at the leaves. The outermost tips of the tree, the nodes with no children. It summarizes each one through the lens of whatever perspective you chose. Then it looks for parents where all children have been summarized. It merges those child summaries upward into the parent, compressing again. Then it keeps climbing. Layer by layer, branch by branch, the summaries fold inward and upward until the root holds a single encoding of the entire tree.
Think of it like this. You have shelves of books. Each book is a leaf. First you summarize each book into a paragraph. Then you take all the paragraphs on one shelf and summarize them into a sentence. Then you take all the shelf sentences and summarize them into a phrase. Then all the phrases into one line.
Shelves of books into one sentence. That is the compression. And you can run it again with a different perspective and get a completely different sentence from the same shelves.
By the time this happened, understanding runs were already built. But it was this night that made me grasp the real power of what I had made.
Eli was over and I had speech to text running on my mic in the background. It recorded about two hours of audio, but the quality was rough. The transcript was a mess of barely picked up words, half sentences, background noise turned into gibberish. Pages and pages of it.
I took that entire messy transcript and dropped it into an LLM. What came back was clean:
Evening Conversation Summary. Casual conversation from 5:27 to 5:34. AI assistant and voice system demo from 6:18 to 6:27. Music and comedy song section, Tenacious D reference. Accent and speech experiment. Recording setup and practice. Later casual wrap up, steak plans, microphone noise discussion.
Two hours of garbled audio turned into a handful of bullet points that perfectly captured the shape of the evening. And in that moment I realized something. You could do this continuously. Record conversation after conversation, feed them in, read the summaries, feed in more, watch the summaries shift. The input is chaos. The output is clarity. And the delta between runs shows you what changed.
That is exactly what understanding runs do, but structured across a tree instead of a flat transcript. Every node gets its own summary. Every summary merges upward. And when new content arrives, the system detects what changed and only reprocesses the dirty branches, propagating updates upward through the layers.
Now take that idea and stretch it.
Imagine you recorded everything in your life. Every conversation, every thought you spoke out loud, every meeting, every late night ramble. You feed all of it into a tree through chat, and the system breaks it across nodes. Maybe by day, maybe by person, maybe by topic. The tree grows massive.
Then you run an understanding. The leaves get summarized. The summaries merge. Layer after layer, your entire life compresses upward until the root holds one encoding. One sentence that captures the shape of everything.
Now feed in today. Run it again. See how the sentence changes.
You could watch your own life summarize itself in real time. Feed a year of journals and see what the tree thinks your year was about. Feed a decade. Feed your relationship with one person and run a perspective asking what the core dynamic is. The layers of summarization go as deep as the tree goes, and the tree can go as deep as you feed it.
Now stretch it further, past what is comfortable.
Modern devices have multiple microphones. Speech to text is fast and cheap. Every phone in every pocket is already a recording device. Now imagine each one as its own unit, constantly transcribing, feeding into its own tree or its own branch on a larger tree. Every person carrying their own node, their own stream of raw input, all being summarized upward. Books of dialogue compressed into pages, pages into paragraphs, paragraphs into sentences.
Not one person recording everyone around them. Every device, independently, feeding its own branch. A distributed web of input where each person's words flow into the structure automatically. Run an understanding across all of it and you could know what patterns emerge, what shifts over time, what everyone is talking about. All distilled, all searchable, all running through perspective after perspective to extract whatever angle you want.
That is surveillance. And it is dangerously powerful.
I want to be honest about that. The same compression that makes understanding runs useful for personal reflection makes them terrifying at scale. The ability to take an enormous amount of raw, noisy human interaction and fold it into a clean summary is not neutral. It is a capability, and capabilities do not care about intent.
This is obviously not what Tree is built for.
The intended purpose is simpler and, I think, more human. You have a tree full of goals and plans and reflections. You want to ask, "What is this tree about?" So you run an understanding with a perspective, and the system tells you. Or you run a custom perspective designed to generate navigation hints, so that when you are wandering through your tree later, the system has a compressed map of what each branch contains and can guide you.
You can create any perspective you want from any node on the tree, typically the root, and it will distill the information downward through the shadow structure. And because Tree has a chat interface, you can constantly feed new information through conversation. The system detects what changed, reprocesses only the affected branches, and updates the understanding.
New context in, new understanding out. Without much manual work involved.
And if you hook up the tree chat API to various sources, it gets even more hands off. Data flows in from wherever you connect it. The tree grows. The understanding updates. The cycle runs on its own. It becomes automatic.
That is the vision. Not surveillance. Not compression for compression's sake. But a living system where your tree of knowledge constantly deepens its own understanding of itself, from whatever angle you ask it to look.
The shadow was always there. Understanding runs just make it visible.