This passage is drawn from Alex Heath’s *Sources*, a weekly newsletter dedicated to examining the intersection of artificial intelligence and the broader technology landscape, made available exclusively to subscribers of *The Verge*. It opens with a vivid scene: on election night in New York City, precisely at eight o’clock in the evening, the author steps into an inconspicuous office building hidden amid the converted warehouses of the Meatpacking District. What lies inside is an unexpectedly subdued environment — a contrasts to the traditional bustle one might associate with election coverage or financial trading.
Instead of raucous displays of excitement, the office contains only a few dozen young employees of Kalshi, a fast-growing prediction market platform. They move between desks littered with pizza boxes and glowing monitors, while a large projector dominates the room, broadcasting live data on fluctuating probabilities in several pivotal election races. Despite the muted atmosphere, the air carries palpable intensity; each quiet keystroke signals the collective attention of a team focused on the unfolding drama of numbers and outcomes. On the projector screen, the electronic markets pulse as percentages update and futures shift in real time, charting the public’s confidence in who will triumph at the polls.
Near this central hub of data, co-founders Tarek Mansour and Luana Lopes Lara are engaged in conversation with a film crew from CBS News. The journalists are documenting a segment to air the following morning, highlighting how digital prediction platforms increasingly mirror and sometimes even pre-empt traditional news coverage. At that moment, CBS has just officially called the Virginia governor’s race—but Mansour remarks with quiet pride that Kalshi’s market forecasted the same result almost an hour earlier. He gestures toward the projector, underscoring how efficiently their system processes dispersed collective sentiment into immediate statistical insight. In an offhand way, he notes, “We’re doing a billion dollars in transaction volume a week now,” a statement that underlines both the astonishing speed of Kalshi’s expansion and the scale at which this fledgling financial mechanism now operates.
The writer admits expecting the frenetic energy typical of a trading floor — the clamorous exchange of numbers, the relentless hum of conversation — yet the office remains almost serene. Mansour later explains this peculiarity from a small glass-walled conference room: volatility tonight is relatively low. The New York mayoral race, he observes, has long been considered a foregone conclusion. Kalshi’s own market, alongside that of its smaller competitor Polymarket, had assigned candidate Zohran Mamdani approximately a ninety-five percent chance of victory even before the polls closed. Still, the seeming predictability did not dissuade traders; about one hundred million dollars in wagers flowed through Kalshi’s system related to that single contest.
Heath notes that his curiosity about prediction markets — and especially Kalshi’s rapid ascent — has grown in recent months. While Kalshi holds the distinction of being federally licensed, something that legitimizes its operations in a way Polymarket cannot yet claim, the latter has maintained a stronger cultural presence within Silicon Valley and among technology enthusiasts. Mansour, conscious of this dynamic, expresses determination to shift that narrative and to establish Kalshi as the dominant name in predictive finance.
Pointing back to the company’s election-tracking interface, captured the day after ballots were cast, Mansour delivers an ambitious statement: “Kalshi is arguably one of — perhaps the — fastest-growing companies in America this year.” He reiterates their phenomenal scale — a billion dollars in transaction volume every week — a stark increase compared to only three hundred million generated over the entirety of the previous year. Although he withholds exact revenue numbers, simple calculations based on Kalshi’s one-to-two percent transaction fee imply that the business is surging and possibly on track to redefine how small-scale speculation operates in modern finance.
Three central developments, Mansour explains, have propelled the company’s trajectory during this explosive year: first, securing a coveted federal license that permits lawful prediction trading; second, broadening their scope to include sports betting, a move that greatly expanded audience engagement; and third, forging a partnership with the trading platform Robinhood, thereby integrating Kalshi-style markets into a mainstream investment ecosystem. While this trifecta has brought massive public interest, particularly from sports enthusiasts, Mansour articulates a grander vision. He believes prediction markets represent a new evolutionary stage of the stock market itself. In his eyes, they hold cultural and media significance because they translate public opinion — the endless exchange of perspectives and intuitions — into a quantifiable marketplace where belief acquires a price tag.
During the course of the evening, Mansour hints at forthcoming collaborations with major media organizations and even potential crossovers into entertainment arenas. “We’re doing a lot with news networks in the coming months,” he says, suggesting that if the insights these markets generate eventually become accepted as reliable indicators by mainstream journalism, Kalshi will have achieved its founding mission: to embed truth-finding through collective speculation at the heart of public discourse.
Nevertheless, both Kalshi and Polymarket face a central test — namely, proving that their predictive accuracy can consistently match or surpass that of traditional polling and professional forecasting. The legacy of early miscalls looms large; Fox News, for instance, endured significant criticism in 2020 for prematurely calling Arizona for Joe Biden. These platforms, by contrast, pride themselves on predicting outcomes in advance of final tallies, a risky practice that, if a major race were misjudged, could undermine the credibility of the entire prediction market model.
As election night progresses and the clock ticks toward final poll closures, Mansour shares live statistics on Kalshi’s New York mayoral market. Data reveal intriguing demographic segmentation: within city boundaries, traders are heavily buying contracts favoring Andrew Cuomo, while Mamdani dominates in other boroughs and beyond. The breakdown continues — Mamdani receives strong support among women and younger users; Cuomo’s backers are largely older, male participants. This granular behavioral data demonstrates the richness of information embedded in these speculative ecosystems.
Then, at precisely 8:20 p.m., Kalshi calls the New Jersey governor’s race a full thirty-two minutes before any traditional media outlet does. The co-founder frames the company’s role as running parallel to that of financial markets relative to bank analysts. “Should the stock market replace analysts?” he asks rhetorically. “Of course not. Analysts make assessments, but it is the market that determines the real price. We provide that same mechanism for factual events.”
When asked whether people incessantly message him for inside tips or early predictions, particularly on nights like this, Mansour laughs. “Absolutely,” he admits, though he quickly clarifies that he holds no special insight beyond the aggregated wisdom of the traders themselves. His habitual response: “Just look at the market. Everything I know, it’s already there.”
As nine o’clock approaches and polling stations edge toward closure, Heath assumes that the founder will remain in the office to witness his platform’s final calls firsthand. Yet as he summons his ride, he notices Mansour slipping out, heading briskly down the street to another car — his work evidently complete. Moments later, Kalshi’s algorithms formally declare Mamdani the winner in New York, a full minute after polls close and more than half an hour before any traditional newsroom broadcasts the same conclusion.
The scene encapsulates a telling moment for the nexus of technology, finance, and democratic participation: where once pundits and journalists shaped narratives in the hours following an election, now data-driven exchanges can reach consensus almost instantaneously, transforming uncertain human judgment into measurable probability and redefining how we interpret the pulse of a nation.
Sourse: https://www.theverge.com/column/815208/election-night-at-kalshi-hq
