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Now, the focus is on what the company does with the additional capacity AI has created. Six months ago, Cubeia’s experiment was essentially about replacing human-written code with AI-generated code.
Since then, it has evolved into something broader: a different development pipeline, a different role for developers and quality assurance (QA), a different way of organising teams and, increasingly, a different relationship with customers.
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.
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But he acknowledges the possibility that faster customer losses could eventually test the sustainability of the model.
“They lose quicker, dry up quicker, recruitment or re-recruitment,” he says. “If the recruitment of players dries up, then what are you going to do? Definitely there can be components like that.”
For now, the growth provides room for multiple market makers. Marantelli expects margins to “stay good during the growth period” before contracting as competition intensifies. The more complex RFQ and parlay markets may offer the best protection against that compression.
