Earlier this year, I was working through a “Hot AI 100” target list for my last client.
Companies like World Labs and xAI were on it. So were Databricks, Glean, Anthropic, Clay, Baseten, Cursor, Perplexity, Harvey, Sierra, ElevenLabs, Runway, Lovable, Scale AI, Abridge and Decagon. We also had the likes of Cognition, Mercor, OpenEvidence, Thinking Machines Lab, Reflection AI, Safe Superintelligence and others in the same constellation.
Half these guys, I’d never heard of. The other ~30% I’d never used but heard mentioned, with a remaining ~20% that I’d either tried or knew about for some reason or another.
These companies all do different things, and a few of them — Databricks and Anthropic in particular — are already operating at a scale far beyond the rest.
As we stood up the ABM motion around that list, I became more and more interested in a strange mismatch I kept seeing among the younger names:
The degree of buzz surrounding them was wildly disproportionate to the amount of actual business underneath them.
A company could have a relatively small team, a still-forming go-to-market motion, a handful of reference-able logos and a valuation built largely on a future claim. Yet its name was already everywhere: founder conversations, product demos, investor notes, hiring discussions, newsletters, podcasts and other people’s feeds.
People who had never used the product had a view on it. People who barely understood the category could tell you which company they thought was winning it.
That is a peculiar kind of leverage.
Of course, these companies were AI-native and absurdly well funded. That buys attention and can buy some initial distribution. It can buy a very loud first year.
But it does not automatically cause a market to start treating a company as the default answer before it has actually earned category-level penetration, revenue, or longevity.
Some other mechanism was at work.
I wanted to understand what it was and how it happens.
More specifically:
How does a nascent company become the name buyers associate with a category, then convert that early perceived leadership into real adoption, durable market share and upwards of nine-figure ARR?
That is the question behind Ubiquitous — my next book, the essays I’ve been publishing here, and now the YouTube channel.
I made a short first video to introduce the thesis:
The channel will be a mix of original visual essays and deeply researched, documentary-style interviews with the founders, executives and operators behind companies that made that jump.
For the founders and brands I’ll be profiling (I’m going to be getting big names), I want to go back to the beginning of each story: the original wedge, the first believers, the early product, the first real signs of density, the positioning decisions that changed how the market understood the company and the moment its name started carrying more force than its actual size should have allowed.
I want each episode to become the best asset online for understanding how that founder or company moved from interesting startup to default category choice — and what had to become true operationally, commercially and culturally for the revenue to follow.
I’m in the lab cooking now and hope to have the first slew of “business breakdowns” and interviews up by the end of the quarter. If this is the question you’ve been tracking too, subscribe to Ubiquitous on YouTube.