Consistent compounding is incredibly difficult and often underestimated.
Growing 50% month-over-month results in a 5x by month 5, 25x by month 9, and almost 1,000x by month 18.
If you read carefully, this is precisely what @BrendanFoody has been saying for months, and it's hard to argue against Mercor being incredibly well-poised to being a generational opportunity
A common misconception is that training data is low skill, grunt work - scan some notebooks, mine the internet, create labeled samples.
The data required to advance the model frontier is the opposite. Labs need training data for high-economic-value tasks. And most of these tasks outside of SWE have little documentation - it is complex, domain-specific knowledge built over the years, spanning legacy tools that donβt talk to each other.
That's why we have SWE agents and not knowledge work agents yet.
The companies creating this training data, such as Mercor, are doing extremely high-leverage, high-skill work.
Critical to moving AI forward. And deeply underappreciated.