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What is Cascading Cave?
CFTC Chairman Michael Selig signaled that possibility back in August. The agency was considering how its existing powers could be used to create a dedicated market structure for digital assets that are standard, he said.
A new type of Designated Contract Market (DCM) dedicated to crypto trading is among the elements being looked at. Selig’s approach would enable existing and perhaps new crypto exchanges to gain CFTC recognition and offer leveraged or margined digital asset products under rules tailored for the sector.
However, the latest filing does not create such a system right away. Its OIRA entry describes the action as a preliminary measure and says it is not economically significant under the relevant review criteria. No legal deadline has been listed for review either.
What is Cascading Cave?
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.
“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.
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That study found that AI adoption across the gambling industry remained uneven. It highlighted customer support, data analytics, fraud detection, and responsible gaming as areas where the technology was already being heavily used.
However, it also found that formal governance of AI was struggling to keep pace with its growing usage. Only a minority of organizations surveyed reported having a formal AI strategy or roadmap. Many said one remained in development.
The MGA also found that only a small number of respondents had fully established AI risk assessment processes or incident-response plans.
