PRODUCT
Most AI tools generate output. Cognit builds a personal knowledge graph from your writing and uses it to make your judgment compound.
THE AI ENGINE
Each level builds on the one below. Together they create an intelligence layer that compounds with use.
Level 1
35 canonical business and investing concepts. Network effects, scale economies, switching costs, cold-start dynamics. This is what lets Cognit say "you're circling network effects" rather than "you mentioned Uber a lot."
Level 2
Built silently from your writing. People, companies, arguments, contradictions, evolving positions. After six months, your Cognit knows who Sarah Chen is, that she works at Acme Corp, what you thought about their partnership dynamics. You never filled in a field.
Level 3
Processes your thinking against everything it knows about you and your domain. Surfaces connections between today's note and something you wrote three months ago, not because the words match, but because the structures rhyme.
Level 4
Analysis across your entire body of work. Blind spot detection. Conviction tracking: positions that drifted without you noticing. Coherence checking: arguments that contradict each other across different documents.
KNOWLEDGE GRAPH
The graph contains entities (people, organizations, events), relationships between them, concept mappings, and claims. An "everything about Acme Corp" view is always current, never manually maintained. Every note you write can enrich it.
Retrieval is hybrid: semantic and structural. When you ask "what have I written about marketplace dynamics?" Cognit returns genuine synthesis from notes months apart, not a list of keyword matches.
Example
You write about Sarah Chen in a meeting note. Three weeks later, you mention Acme Corp's partnership strategy in a different note. Cognit connects them: Sarah works at Acme, you've written about her perspective on their Stripe integration, and your earlier analysis flagged partnership dependency as a risk. When you open the Acme Corp view, all of this is there. You never created a "Sarah Chen" contact or an "Acme Corp" folder.
THE WRITING SURFACE
A rich text editor built for serious thinkers. Daily notes for capture, dedicated notes for deeper work. Typography is the product. The writing experience is designed to disappear so your thinking can take center stage.
As you write, entities appear as subtle underlines. Connections to earlier thinking surface contextually. You can ask the AI questions grounded in your full history. None of this interrupts the flow.
Templates for structured thinking: meeting notes, decision logs, research notes. Import from Notion, Obsidian, or Markdown. Voice capture for when typing isn't practical. Everything feeds the same knowledge graph.
HOW INTELLIGENCE SURFACES
Daily synthesis. Patterns, resurfaced connections, meeting prep, blind spots. Not a summary of what you wrote. A briefing on what it means.
Persistent conversation grounded in your knowledge graph. Ask questions about your own thinking and get real synthesis, not keyword matches.
Connections to earlier thinking. Emerging themes across scattered notes. Structural parallels. Claim evolution over time.
Every note enriches the graph. Every entity mention densifies relationships. Every concept connection strengthens the model. The product gets specifically smarter about you and your domain.
This is the depth strategy. Not a productivity hack you use for a week and forget. A cultivated intelligence layer built from years of serious use. It doesn't export to a competitor because the value is in the accumulated understanding, not the data format.