AI infrastructure is everything underneath the application that lets models train, serve, scale, route, retrieve context, stay observable, and run at a cost the business can live with.
For builders, this matters because many AI apps do not fail because the model is weak.
They fail because the system around the model is weak.
Latency was not planned for.
Inference costs ran away.
The serving layer could not scale.
The data layer did not provide the right context.
The agent had no audit trail.
No one could explain what happened when something broke.
That is the real infrastructure problem.