Woofun AI reports that Gabriel Perez, a longtime teleprompter operator at the White House, was placed on unpaid administrative leave on July 16 after ABC News revealed allegations of insider trading involving President Donald Trump’s prepared remarks. The core accusation centers on Perez allegedly leveraging advance access to nonpublic information to generate profits exceeding $100,000 on the prediction market platform Kalshi.

The financial magnitude of the alleged trades triggered an automated response from Kalshi’s surveillance systems, which detected unusual account activity and initiated an investigation. Evidence was subsequently forwarded to a federal regulator, though critical details regarding the specific timestamps of each step remain undisclosed. This gap in temporal data obscures the precise sequence of events between the alleged bets and the regulatory referral.

Structurally, this incident aligns with Trump Media’s July 16 announcement of the Truth API, a paid data feed launching on Aug. 1 designed to deliver posts from Truth Social’s most influential accounts to institutional customers in milliseconds. Per Woofun AI, the service targets high-frequency trading firms and algorithmic trading firms, entities for which even minor information delays impose significant costs. Unlike the Perez case, which involves pre-publication access, the API facilitates faster post-publication data consumption.

The convergence of these events highlights adjacent markets built around the commodity of receiving Trump’s potentially market-moving words before slower participants can react. While surveillance mechanisms successfully generated a referral, freeze, and ban, the absence of clear timestamps leaves the speed and deterrent effect of the response unproven. This marks a critical test for regulatory efficacy in monitoring nonpublic remarks.