Something fundamental has changed in software.
For decades, the growth of software was constrained by a simple bottleneck: the number of developers available to write it. Organizations simply couldn't scale their engineering teams fast enough to keep up with software requirements due to constraints related to human capacity.
That limit has now been removed.
Artificial intelligence is dramatically increasing the rate at which software can be produced. AI coding tools are not just assisting developers - they are amplifying them.
The data already reflects this shift. According to the GitHub Octoverse 2025 report:
This is not simply a productivity improvement.
AI has removed the bottleneck on code creation.
Most organizations have not addressed the impact on quality.
Software abundance introduces a dangerous new imbalance.
When code production accelerates faster than validation, risk compounds exponentially. Codebases grow rapidly. Dependencies multiply. Integration risks rise. The volume of potential edge cases explodes.
Organizations must begin scaling their test infrastructure at a faster rate than its software growth immediately.
The consequences will be severe:
If your organization is adopting AI development tools (and most should be), the speed of software creation will continue to accelerate. Without a corresponding evolution in testing infrastructure, teams may unintentionally be racing toward failure at scale.
Fortunately, the same technologies accelerating development can also transform testing.
AI-driven testing can:
In other words, AI can scale verification just as effectively as it scales creation.
The key insight is simple: in the age of AI-assisted development, testing must evolve from a bottleneck into a force multiplier.
will unlock software abundance.
Those that don't will simply
produce faster failures.
Don't let your code production outpace your ability to validate it.
Invest in your test infrastructure with urgency. The age of software abundance demands it.