Our working hypothesis
The first signal might not be private jets leaving the US.
A hypothesis, stated plainly so you can judge it — tested against public data, revised when the data disagrees.
What we will — and won't — do
No predictions
We never declare a threat, and never tell you when to prepare.
Your thresholds decide
A text means your signal crossed your line. Nothing else.
Better signals, not answers
Our job is better data. The decision stays yours.
01 · The question
Who moves first?
In a true worst case, a handful of people learn early — and word doesn't stay contained. One call becomes ten bookings within the hour.
+Why word can't stay contained
The first-informed warn the people closest to them — aides, colleagues, family, friends-of-friends. Each of those people has a circle of their own. No announcement required.
Washington and New York hold the densest concentration of first-informed people in the country: government, intelligence, defense, finance, media. That's where the ripple starts.
02 · The usual suspects
Jets and military flights lag.
A jet needs a crew, a flight plan, and fuel. A seat needs a phone. The truly early are wheels-up hours after the first bookings.
+Why private jets take hours
Even the best-connected owner waits on crew callouts, positioning, and clearances. The oligarchs fly hours after they find out — and the circle that owns jets is tiny. The far larger circle around them can't summon a Gulfstream. They book a seat.
+Why military surges read late
Military movement is operational and often deliberately dark, and it blends into a constant background of exercises. By the time a surge is unambiguous in public feeds, the earliest hours are gone. When transponders go quiet, the blackout itself is a signal — a later one.
Time until wheels-up · the seats move first
03 · The hypothesis — stated plainly
The first public ripple is executive-cabin bookings out of Washington, DC and New York — visible in fare and availability data before any jet leaves the ground.
Premium cabins hold about a dozen seats, priced by algorithms that react in real time. A few urgent bookings show up in public data within minutes.
+Why business class shows it first
A last-minute business-class seat is the fastest exit money can buy from a phone — no crew, no flight plan, no waiting. Because inventory is tiny and pricing is algorithmic, a handful of price-insensitive bookings moves fares and availability immediately, in data anyone can see.
+Why Washington and New York
They're where early knowledge lives — the seat of government and intelligence, and the center of finance and media. The person who hears first is disproportionately likely to be standing in one of these two cities.
04 · The corridors
Three doors out.
If the hypothesis is right, the earliest movement concentrates on a few corridors — to places with the ties to receive.
+Toronto — the close door
Under two hours from New York or DC airspace, a dozen departures a day, and a land border you can still drive to if flights stop. Same language, straightforward entry, deep family and business ties. It's the exit that requires no plan.
+London — the second home
For American money and power, London isn't a foreign city — it's the other office. Widebodies leave for Heathrow nearly every hour, and an entire infrastructure of homes, banks, schools, and firms is ready to receive.
+Switzerland — the neutral haven
A century of other people's crises built the Swiss role: political neutrality, hard-currency banking, private-wealth infrastructure. When the goal is moving family and capital at once, Zurich and Geneva light up.
The corridors we watch first
05 · The test
Tested against the news, in public data.
We track major world events and look for movement on the escape routes. Consistent so far — and nowhere near proof.
+What we're tracking right now
Correlations between international political threats and movement on immediate escape routes. As the dataset grows we add signals — more corridors, aviation behavior, market stress — and keep testing. Where the data disagrees with us, the hypothesis changes. That's the job.
+2.7% vs +0.9%
Exit routes moved 3× more than control routes on event days
r = 0.684
Bigger events produced proportionally bigger spikes
Day-before
High-severity events showed movement before the announcement
2,383
Route-date-cabin series analyzed across live flight data
A hypothesis, honestly held
We publish it so you can judge it.
A FleeFirst text means one thing: a signal you chose, crossing a threshold you set. The better our signals get, the better your decisions can be — and the decisions stay yours.