When you have a front-row seat to the most secure scripts in the country, turning that knowledge into a side hustle is a fast track out of a job. Gabriel Perez learned this the hard way.
The longtime White House teleprompter operator who managed Donald Trump's speeches since 2016 is officially out of federal service. Behind this exit is a bizarre financial crossover between inside government access and online prediction markets. Perez allegedly pulled in more than $100,000 by betting on specific words and phrases the president would use during major addresses like the State of the Union.
That payout is a hefty chunk of change, especially when compared to his standard federal salary of $175,000. But the math didn't add up for long.
How the Scheme Unraveled
Prediction platforms like Kalshi have exploded in popularity. Instead of just betting on election winners, users can jump into specialized "mentions" markets. You can literally wager money on whether a public figure will say a specific phrase, drop a certain policy buzzword, or reference a particular country during a live speech.
If you control or edit the text on the glass screen right in front of the speaker, you have an unfair advantage.
Investigators flagged unusual activity. Kalshi's internal surveillance team caught onto the pattern. They noticed trades that tracked too closely with speech drafts, including instances where wagers were mysteriously modified or canceled right as the president drifted off-script. Kalshi handed the data over to the U.S. Commodity Futures Trading Commission (CFTC).
The White House reacted swiftly. Press Secretary Karoline Leavitt called the allegations "deeply unfortunate and, frankly, a disgrace." Perez was initially dropped onto unpaid administrative leave. By late July, a federal official confirmed he no longer worked in government.
The Broader Problem With Prediction Markets
This incident exposes a gaping loophole in how modern financial speculation operates. Prediction markets are booming, scaling up from modest trading volumes to billions of dollars. Proponents argue these platforms provide real-time public sentiment data. Critics point out they look a lot like unregulated gambling with zero structural barriers against insider trading.
Think about the incentives. When government employees, political aides, or corporate insiders have advance access to non-public information, the temptation to monetize that access is massive.
The CFTC regulates these markets, but enforcement is tricky. Platforms like Kalshi have started requiring users to disclose their places of employment. They prohibit betting based on job-related knowledge. Yet, catching violators relies heavily on automated algorithms spotting weird spikes in trading volumes after hours.
States are scrambling to figure out rules too. Minnesota tried to ban prediction markets entirely earlier this year, though federal judges hit pause on that law. Meanwhile, political figures defend the industry while federal agencies try to police the edges.
Why This Matters Moving Forward
You can't treat government employment like a day trading simulator. Ethics rules inside the executive branch explicitly forbid using internal information for personal financial gain.
Perez's case isn't just a quirky news story about a rogue staffer. It serves as a warning shot for anyone handling sensitive material in public service. As speculation markets expand into everyday culture, monitoring digital footprints will become standard practice across federal human resources.
If you're betting on what someone will say, make sure you're guessing like everyone else. If you wrote the speech, close your browser and walk away.
