The Rhesus Chart by Charles Stross Read Free Book Online

capitalism.
    Until we get to the Scrum.
    A scrum—generic—is, depending on which dictionary you look it up in, either an elaborate way of restarting play in a rugby match (rugby: sort of like American football only with less body armor and more biting and gouging—I was forced to play it at school: did wonders for my character),
or
one of the quirkier cognitive disorders to which software project management is prone. The rugby version involves getting head-down and having a shoving match with the other side, sometimes involving ear-chewing, scrotum-grabbing, and neck-breaking (although the latter is frowned upon); the software variant is not dissimilar. It has its origins in Agile methodology, although it’s Agile hopped up on crystal meth and spoiling for a fight: exactly the sort of thing you’d expect a bunch of city high-flyers to find appealing (at least in principle, and as long as it didn’t look likely to detonate a large landmine under their bonuses).
    The
Scrum, singular, was the brainchild of Oscar Menendez, the vast unsympathetic brain at the heart of
The
Bank’s Data Analytics Support Division, and sometime Algorithmics star. Back in the prehistory of the early noughties they headhunted him from Google to show them how to apply map/reduce to the very large data sets they were processing in real time—
    (You’re not listening, are you? Damn it, I suffered through the briefing. I don’t see why you shouldn’t have to suffer, too!)
    Moving swiftly forward: the Bank set up the Scrum to try and bring some of the culture of an agile, highly responsive software start-up to bear on the job of developing new and improved tools for high-frequency trading. The Scrum was elite; the Scrum had esprit up to
here
; the Scrum’s long-term planning threshold was about twenty-four hours, marching to the beat of the daily stand-up meeting. They had a monstrous array of high-power data mining tools, live feeds from every exchange on the planet, their own individual compute-server farms. They had a PhD to headcount ratio close to 1:1 among the pigs—the hard core of math quants and algorithm developers. And every day they went in search of new and better techniques for identifying patterns in the data, trends that might be good for an extra 0.1 percent margin on every transaction for the handful of seconds it took before their competitors cottoned on.
    They were brilliant, widely read, incisive, and effortlessly effective analysts and programmers. Which is another reason why, ultimately, so many people died.
     • • • 
    PICTURE ALEX, ALONE IN THE OFFICE ONE EVENING.
    Picture a twenty-something with spectacles and the remnants of a late heavy bombardment of acne cratering the ’80s designer stubble under his jaw. The spectacles are, of course, aggressively black-rimmed and thick-lensed. His suit is expensively tailored, his shirt of finest quality linen, and the collar is just slightly askew, because Alex has an image to defend: that he is a quant, that he is Oscar’s intellectual successor, that his mind soars as high above such mundane preoccupations as the City institution’s dress code as an SR-71 roaring on Mach 3 afterburner across the abstract vistas of category theory and algebraic topology.
    It’s actually a total bluff. Like many truly brilliant minds, Alex suffers from an inordinate case of impostor syndrome, with mild hypochondria on top. He routinely arrives in the office each morning as a sweaty, seething blob of fear, certain that at any moment one of his colleagues will expose him as a fraud, unable to prove something as basic as A n = B n + C n for any arbitrary integer
n
. He’s convinced that the reason he doesn’t have a girlfriend is that he has halitosis. (He doesn’t; the real reason is that he works over fourteen hours a day, six days a week, and spends the leftover hours sleeping, eating, and trying not to fall apart.) And he used to think that his acne was a symptom of malignant