This is Part 5 of a 5-part series on where the AI infrastructure bottleneck is actually moving—and how that reshapes the competitive landscape.
By now, the pattern should be clear:
The bottleneck in AI is not compute.
It’s the ability to scale the physical layer—reliably, repeatedly, across multiple partners.
Parts 1–4 mapped the framework. Part 5 names the casualties.
Now we get to the uncomfortable part:
Which companies are exposed—and why most investors won’t see it until it’s too late.
Because every cycle has the same trap:
The names that look strongest early—
the best demos, the cleanest narratives, the highest expectations—are often the ones that break first when scaling becomes the constraint.
Because scale is where physics replaces narrative.
🔒 Paid Begins
