Bat & Ball → Coding in the age of abundance
When access to the scarce tool once decided who made the rules, what changes when software creation becomes abundant?
AI makes coding tools abundant, but abundance does not make engineering outcomes automatic. It moves the advantage away from simply having the tool and toward practicing the fundamentals: understanding the problem, designing resilient systems, communicating clearly, and shipping reliably.
The bat-and-ball power law
In the India of the 1980s, the child who brought the cricket bat and ball often made the rules. That child was not necessarily the best player. The source of the advantage was ownership of something scarce: without the equipment, there was no game.
As India became more prosperous after 2000, cricket equipment became accessible to many more children. The bat owner’s automatic authority faded. Yet the basic result on the field did not change: teams with players who had practiced still tended to win.
Software’s scarcity is collapsing
Coding once worked a little like that scarce cricket kit. Access to a computer and a short programming course could be a meaningful differentiator because the ability to write software was itself relatively rare.
That barrier has been falling for years. Devices and internet access are cheaper, open-source software and cloud services are widely available, and AI can now generate code in seconds. More people can enter the game, and one person can move across requirements, implementation, testing, and operations with far more leverage than before.
But access is not the same as an outcome. When everybody has a bat and ball, the questions change. Can you identify the real problem? Can you design a system that will not fail under scale? Can you respond calmly when production breaks at 2 a.m.? Can you simplify complexity, explain decisions, and deliver something dependable?
Abundance changes the game, not every rule
Greater individual capability does not mean large organisations will collapse every responsibility into one role. Risk controls, audits, segregation of duties, and compliance still matter. AI changes what a person can do; it does not automatically remove the reasons organisations separate certain decisions and checks.
What abundance can create is more activity: more people building, more products tested, more startups attempted, and richer software ecosystems. The scarce thing is no longer merely the ability to produce a line of code.
The durable advantage
The winners will still tend to be the people and teams who practice. The useful practice now includes system design, problem framing, product thinking, communication, and operational discipline. AI can put the equipment in many more hands. It cannot decide which game is worth playing or replace the work of learning to play it well.
This essay was first published on LinkedIn on 17 February 2026.