A lot of DePIN projects can prove one thing quickly: people are willing to add devices.
The harder question is whether anyone is willing to keep using them.
For a compute network, supply and demand need to be separated. More processors mean more potential capacity, but an idle network is still just unused capacity. The metric I care about is not only how many devices are online, but who is paying for computation and how often that demand returns.
@Acurast has already shown that its network can run different workloads, from APIs and scheduled jobs to LLM inference and confidential computing. Laya/System One also shows that specific AI inference workloads can run on the network. That proves execution capability.
It does not automatically prove a mature demand market.
The next thing I would watch is the structure behind deployments: what kinds of workloads keep coming back, whether developers are willing to continue paying compute costs, and whether the protocol can turn available compute into recurring usage.
Supply decides how much capacity exists.
Demand decides whether that capacity matters.
That’s the part I’m watching.
#Acurast https://hub.acurast.com/rebellion?ref=u09wbr