What does the article mean by 'failure becomes cheap' in the context of parallel AI development?

In earlier stages, human time was expensive and serial, so failures were costly. With the 2025 H2 leap, agents can autonomously debug, iterate, and try multiple approaches in parallel. This makes failure cheap and experimentation viable—you can launch multiple paths simultaneously, let agents test and fix themselves, and only have humans intervene for final acceptance or tricky architectural trade-offs.