How to survive in the exponential age

I’d like you to meet Sid Karunaratne. When I was building a data analytics and predictive start-up in the 2000s, we hired Sid when he was just a year or so out of university. He had the casual air of a techie – ponytailed hair and a start-late, work-late approach to his professional life. When he wasn't out rock-climbing, he was at his day job, tending to the cluster of servers that ran our business. These machines were the computing horsepower we needed to back up our large-scale calculations.

In his first few months, looking after this batch of powerful computers was a full-time job. Bugs in the software would cause servers to crash. Inconsistencies in the data might break our programming, causing the servers to crash. The volumes of data might fill up the storage space, causing – you guessed – the servers to crash. Every couple of days our developers needed to update the core code that powered our business, with bug fixes, optimisations and updates for new features. Sid was responsible for putting changes into production. This meant making perhaps hundreds of little tweaks to the code, and “pushing” it to the powerful servers that our customers accessed. And then there were all the security vulnerabilities that cybersecurity groups warned us of – new weaknesses discovered in the database we were using, or backdoors into the operating system. All these chinks needed to be patched up: more code that needed to be uploaded to our servers. Morning to night, Sid was busy.