The pace at which artificial intelligence companies are scaling their recurring revenue has no precedent in recorded business history, according to a widely discussed claim making the rounds on Hacker News. The post, submitted by user silexia, argues that neither OpenAI nor Anthropic has a historical comparator in how quickly they have grown their revenue base, and that this velocity signals something far more consequential than a typical tech boom.
The Revenue Curve That Defies Comparison
The central claim is straightforward: no company in the history of recorded business has scaled recurring revenue as fast as OpenAI and Anthropic. While the post does not cite specific revenue figures, the assertion aligns with publicly available data points that have emerged over the past year. OpenAI, for instance, reached an annualized revenue run rate well above $10 billion within roughly three years of launching ChatGPT, a milestone that took companies like Google and Meta significantly longer to approach. Anthropic has followed a similar trajectory, securing massive enterprise contracts and consumer subscriptions at a pace that has surprised even seasoned analysts.
The implication is that the demand for frontier AI is not growing incrementally. It is compounding. The author of the post frames this as an exponential curve rather than a linear one, meaning each successive period of growth is larger than the last, not merely a continuation of the same rate.
What Frontier AI Actually Feels Like Day to Day
The post includes a firsthand account from someone who says they are building a serious software program using AI without writing a single line of code themselves. According to the account, AI resolved 99.9 percent of bugs and generated 95 percent of the features and roadmap. The cost of this workflow is described as a few hundred dollars. Whether this experience is representative of all AI-assisted development or reflects a particularly favorable setup, it points to a broader shift: the barrier between a concept and a working product is collapsing.
For developers who have not integrated paid frontier AI tools into their daily workflow, the post argues that their mental model of what AI can do is likely outdated. Even those who use it daily report being shocked by the magnitude of capability gains between releases. This observation echoes a common sentiment in the developer community that the pace of model improvement is outstripping the ability of most organizations to adapt.
Institutions Built for Linear Thinking Face an Exponential Problem
The post raises a pointed concern about governance. Human institutions, including Congress, were designed to operate on linear timelines and incremental policy cycles. An exponential technology curve does not fit neatly into that framework. The author urges direct action, calling on readers to contact their representatives and warning that the window for meaningful intervention may be extremely narrow.
The post also references estimates from prominent AI researchers, citing a 10 to 50 percent probability that advanced AI could pose an existential threat to humanity. While this figure is drawn from surveys of AI researchers rather than a single definitive study, it has been a recurring data point in discussions about AI safety. The post uses this range to argue that the stakes are not hypothetical and that the time to act is immediate.
What This Means for the Industry
Regardless of where one falls on the spectrum from cautious optimism to existential alarm, the underlying fact is difficult to dispute. AI companies are growing faster than any technology companies in history, and the practical capabilities of their products are advancing at a rate that challenges conventional planning horizons. For software teams, enterprise buyers, and policymakers alike, the question is no longer whether AI will reshape their operations. It is whether they are moving fast enough to keep up.
The post ends with a blunt recommendation: those working inside AI companies should consider whether they are comfortable with the direction their work is taking. It is a provocation, but it reflects a real tension that many in the industry are grappling with privately. The speed of commercial success in AI is not just a financial story. It is a signal about how quickly the technology is moving past the point where slow, deliberative oversight is sufficient.