Classico

What is Classico?

Across markets in Latin America, Europe and Asia, Yashin says the average stakes for swipe games display a pattern closer to sports betting than crash gaming. In one market, the average Swipe Games bet was 20 times higher than the average crash-game bet with the same operator.

Retention has provided another encouraging signal. Depending on the market, Yashin says day-one, day-seven and day-30 retention can range from around the crash-game benchmark to between five and 10 times higher. The number of rounds played during a session can also be significantly greater.

The explanation, he believes, comes back to the behaviour that inspired Swipe Games in the first place. Crash players may experience a different outcome each time, but visually they repeatedly encounter much the same thing. Social media has conditioned its users to expect something new with every swipe.

About Classico

His analogy is a poker table at which the weaker participants sustain the game. If those players disappear, the fourth-best professional at the table can suddenly become a loser because only the three strongest remain.

The US addressable market is vastly larger and customer recruitment remains strong. Marantelli says Kalshi increased its number of clients fivefold during the World Cup, while White Swan predicts that NFL prediction markets could generate between $5 billion and $7 billion of liability in a single week.

But he acknowledges the possibility that faster customer losses could eventually test the sustainability of the model.

What is Classico?

Cubeia’s first phase was an open approach to AI. Developers could use it whenever they wanted. Phase two brought structure, with everyone using the same agents and working through the same AI-driven pipeline. That required Cubeia to solve questions around quality, reliability and how agents could work together, while getting employees comfortable with the new way of working. Grenstad believes that work has largely been completed.

“During the hybrid period in Q1, Cubeia solved 259 issues. Once it moved to the AI-driven process, that figure rose to 421 – a 62% increase. Larger projects increased from 17 to 58. So the answer is yes: moving to AI-driven development has increased our output tremendously,” Grenstad says.

But the more important question now is what Cubeia does with that capacity. “Because we’re not spending as much time coding, we’re spending more time on the business: talking about value and understanding the domain,” he says.