Observing on-chain applications reveals an interesting phenomenon—many projects seem stagnant, but the real reason often isn't with the users, but with the system itself.

Contracts can be modified, front-end interfaces can be redesigned, so where's the problem? It's in the data. Once the data structure becomes chaotic, recovery is almost impossible. Applications that need to preserve state over the long term are especially affected, as data gradually becomes a drag.

Walrus is working on making "how data is referenced long-term" a top priority, rather than simply pursuing immutability of data. In its architecture, objects are maintained collectively by multiple nodes in the network, allowing for direct integrity verification when retrieving data. The test results are promising—under high concurrency reads, response times remain stable at the second level.

What does this mean for application development? It means data can be confidently stored within the system without relying heavily on off-chain backups or centralized caches.

Honestly, I am cautiously optimistic about this direction. It aims to solve a long-term problem; it may not have much presence in the short term, but in the long run, it could have a huge impact. The main uncertainty lies in whether the ecosystem can keep pace with the iteration speed of this approach. If the application layer can't keep up, even the strongest storage models are useless.

However, from a long-term perspective, there are really not many projects heading this way. This path is worth exploring.