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The rejection of the Clarity Act can be viewed as a victory for gaming stakeholders in their fight against prediction markets, which are closely intertwined with the crypto world. Crypto markets have long been the second-largest category of prediction market trading, behind sports, and many crypto exchanges also now offer predictions. These include Crypto.com, Coinbase, Gemini and many others.
On 16 June, a coalition of gaming lobby groups, state associations and labour unions sent a letter to the Senate urging lawmakers to include language in the bill banning sports and casino-related contracts. Among the signatories were the American Gaming Association, the Indian Gaming Association, the Association of Gaming Equipment Manufacturers and the UNITE HERE unions.
“Litigation may eventually clarify the law, but this is ultimately a question of congressional intent. Congress should not wait while this nationwide expansion of gambling continues,” the letter said. “It should use crypto legislation to reaffirm a simple principle: sports betting falls outside the CFTC’s remit and cannot be offered through prediction market platforms.”
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The drafting of the text is reportedly in the hands of the Civil House, with some believing that it serves an electoral purpose, meaning Lula potentially riding the wave of criticism against the sector.
The Brazil betting industry has faced increasing scrutiny of late over claims that families are falling into debt because of gambling.
The president is not seeking to introduce the measures through a full bill, as the legislative process in Congress could reduce their immediate political impact ahead of the elections.
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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.
