I used to think Nillion’s biggest opportunity was simply keeping sensitive data private. But the more I looked into its model, the more I realized the interesting part is what happens after the data is stored.

With Nillion, encrypted data can potentially be processed without exposing the underlying information. That creates a different possibility for DeFi: trading strategies, AI agents, and financial applications could work with sensitive information without making everything public.

Here’s the detail that changed my perspective: data storage and actual computation are not the same kind of demand. Stored data can sit untouched, while computation can generate recurring usage. That distinction could matter far more than raw storage numbers.

My inference is that Nillion’s real economic test will be whether developers repeatedly pay to compute on private data, rather than simply experiment with the technology. That demand—and how it translates into network fees and $NIL utility—needs evidence, not assumptions.

If private computation becomes essential to AI and DeFi, who captures the value: the network, the applications, or the users who control the data?

@Nillion $NIL #nil