GENERATIONAL
UN-FUMBLE

a life in San Francisco · the AI wave · real statistics

Twelve years in San Francisco, as someone you did not choose. Every six months, a decision only you can make. Some of them will turn your whole life.

$0
of venture money deployed worldwide so far today
$0
of San Francisco rent paid so far today
0
tech workers laid off so far today, at this year's pace
01Who you arrive as
02Romance

01

Your fate collection: every turning point, high point and easter egg you have met, across all your lives.

02My lives
Lives you finish are kept in this browser only.
03Data and methodology

Every life is drawn from these distributions, then your choices and a seeded random number generator do the rest. Measured means a published statistic; estimate means the game interpolates between published figures. Gathered October 30, 2026.

Calibration check

500 lives played by a neutral autopilot that also takes the half-year decisions, twelve years each. Median net worth ~$580k; 37% end above $1M, 4% above $10M, 5% below zero. Tech workers: median $3.4M. 5% leave the country when a visa lapses; 2% leave the city broke; the autopilot marries 79% of the time when it wants a family. Across a strategy grid (cautious, moderate, aggressive, founder, and a cheat that knows the sector winners), no strategy wins more than ~65% of head-to-head lives on the same draw, and the cheat does not beat a moderate player. Founders have the highest mean and the lowest median, as in the Carta and Horsley Bridge data.

How story decisions work

A model writes the situation and the options from your current state, but it only proposes effects from a fixed schema (cash, burnout, skill, network, relationship, job risk, offer odds, a few actions), each clamped to bounds the engine enforces, and risky options carry an explicit probability the engine rolls. No story decision can hand you a company, a windfall above two months of income, or a job. The calibration harness, which has no model, plays a handwritten deck under the same rules.

How turning points work

Every few years a turning point may open: a faint signal in the feed, a moment to act, and a reveal months later. Each is modeled on something that really happened (Silicon Valley Bank, FTX, DeepSeek, Klarna's AI assistant, Google's 2023 layoffs) and names it when it lands. Some omens are false alarms, so caution has a price. Effects are bounded like story effects, and the calibration check above includes them.

The companies are fictional; the numbers are not.