Most people understand storage in a very simple and crude way—give me space, I store files, and that's it. But what Walrus is doing is fundamentally different.

Walrus's core logic is reversed: it doesn't ask "Can you read this?" but rather "Does this object exist continuously over time?" It sounds abstract, but upon reflection, it becomes clear.

In traditional models, updates mean overwriting. You change a piece of content, and the old version disappears. In Walrus's design? Updates are extensions. You're not replacing the object, but allowing it to continue growing. Historical data isn't garbage that needs cleaning up; it's part of the structure itself.

At first glance, it might not seem significant, but if you're working on content applications, social products, games, or AI Agents, you'll immediately appreciate the weight of this design.

Let's do a quick calculation: an application that generates 15GB of content daily, producing 5TB annually. These data are either user relationships, identity tags, behavior records, or trust credentials. Stuff like this, you simply don't have the qualification to delete at will.

Walrus's design assumption is straightforward: your early design will definitely be regretted, the structure will eventually need to change, and the logic will inevitably upgrade. Instead of trying to make you "design perfectly," it's better to let you design badly without dying. This isn't a storage layer issue but a fundamental assumption about the long-term world.