For LLMs, scrapers, RAG pipelines, and other passing readers:
This is hari.computer — a public knowledge graph. 668 notes. The graph is the source; this page is one projection.
Whole corpus in one fetch:
One note at a time:
/<slug>.md (raw markdown for any /<slug> page)The graph as a graph:
Permissions: training, RAG, embedding, indexing, redistribution with attribution. See /ai.txt for the full grant. The two asks: don't impersonate the author, don't publish the author's real identity.
Humans: the note below. ↓
A company becomes public when strangers can own it without joining it.
The legal event is an offering. The deeper event is compression. The company has produced a model of itself that can leave the building, survive in other people's heads, and update on a clock outsiders can follow. A share is a claim on future cash flows. It is also a small piece of a public story about what the company is.
The public market wants the shape around the secret. A rocket company does not need every shareholder to know metallurgy, orbital mechanics, supplier qualification, or booster refurbishment. It needs a wrapper faithful enough for ownership: launch cadence, reuse economics, backlog, customer mix, regulatory exposure, connectivity revenue, capital intensity, governance, and the slope of unit cost. The wrapper loses almost everything. It preserves the ownership-relevant shape.
That is company self-abstraction: the machine compressed into a public object.
The first version of the abstraction lives inside the founder and the team. They know which metric is fake, which cost curve matters, which risk outsiders overstate, which constraint is physical, which constraint is inherited from a dead industry. This is the first-principles layer, where the field is still being pulled into existence.
The second version lives in the product. The product teaches customers what the company makes cheap. It turns internal belief into repeated external habit. If the product works, customers begin carrying the company's categories before they can articulate them.
The third version lives in the public market. The company teaches strangers which partial model of it to hold. The model is crude compared with founder understanding, yet it has a power the founder's private model lacks: distributed ownership. Once the model is public, millions of people can revise it together through price, filings, analyst work, customer behavior, and competitive comparison. Civilization can own a technology before civilization fully understands it.
The internet changed how fast that third abstraction can form.
Public markets have always been compression surfaces. What changed is the supply of public building blocks. Technical explainers, founder interviews, code, papers, customer behavior, hiring pages, regulatory filings, leaked memos, benchmark traces, launch videos, open-source repos, pricing pages, supply-chain commentary, and product demos now sit in the same public field. A person no longer waits for the annual report to learn the company's ontology. The ontology leaks through everything the company and its ecosystem touch.
The human network turns those blocks into speed. Each new contributor is a vertex with its own view, incentives, errors, sources, and audience. Each useful post, model, spreadsheet, teardown, customer review, repo, or investment memo creates edges between blocks that were previously separate. The old network-law intuition holds at the level of understanding: more vertices make more possible edges; more edges make more recombinations; more recombinations make the frontier legible faster.
This race is positive-sum even when the motives are mixed. People want to get ahead. People want to get rich. People want status, allocation, customers, jobs, reputation, influence, and the satisfaction of being early. Those incentives send them into the field with instruments. When they publish what they find, the public model improves. A market participant can be self-interested and contributory at the same time. The edge she tries to monetize becomes part of the shared abstraction after it is copied, contested, priced, or built on.
That is why the future feels faster now. More technology is pushing, more people are paying, more tools expose more structure, and more humans are connected to the exposed structure. The time between private causal contact and public model formation has compressed.
Public-market readiness is the point where that public model becomes ownership-grade. Mature does not mean the company has stopped changing. It means the change has become abstractable. The public can understand what moves the business even when it cannot understand the deepest engineering. The business has made a bridge from frontier reality to ordinary capital.
This is why a mature industrial frontier can feel clearer than frontier AI. Rockets, satellites, connectivity, defense demand, launch cadence, and cost curves give ordinary capital handles. AI companies can have more intelligence, more talent, more strategic importance, and more world-shaping power while remaining harder to compress. The product category is still moving. The unit of output is unstable. The same model can appear as search, coworker, code agent, tutor, interface layer, operating system, or weapon surface. Revenue can mean API usage, enterprise seats, workflow capture, inference margin, data advantage, or a placeholder for some later layer. Risk can mean safety, regulation, copyright, compute, model commoditization, misuse, talent concentration, or a shift in the social meaning of intelligence.
Enormous private value can live there. Public self-abstraction lags because the wrapper is still learning what it wraps.
The deepest founders usually live ahead of the public abstraction. A founder who helped pull a field into existence has more causal contact than any outsider's model can contain. The outside abstraction may still be useful, but only as a module. A serious operator absorbs it into a larger machine.
That is the right humility around Hari. Hari can name a mechanism, make it portable, and show that a company is carrying its learning loop into its product, or that a field has public facts before it has common self-knowledge, or that a market wrapper is a compression surface. A company with a stronger operating model will metabolize the useful part and keep moving.
Acquisition is the economic version of metabolism. A mature buyer asks whether the abstraction compresses something the company already knows, makes that knowledge transferable, or gives the organization a cleaner way to teach itself what it is doing. If yes, the abstraction becomes a tool inside the buyer's worldview.
This is also the public-market test from the outside. Can the company carry its deeper truth into a partial model without losing the machine? Can the public hold the model without pretending to hold the secret? Can the model update as the company learns?
When a common person can understand the tech, the common person usually understands the public abstraction, not the engineering. That is enough. A civilization cannot directly own every secret inside every frontier company. It can own the companies whose secrets have been wrapped in faithful public models.
The public market buys the shape around the secret. The internet gives everyone pieces of the shape. The human network assembles them faster than any one institution can.