When it comes to distributed storage projects, I want to change the perspective — not to praise how advanced the technology is, but to evaluate from the standpoint of a real project evaluator and clarify a few of the most thorny issues.

What is the biggest pitfall in the storage track? It’s when the technology can run and data can indeed be stored, but in the end, no one is willing to pay continuously, and the entire network survives on subsidies. Walrus gives me the feeling that it at least faces this problem head-on rather than avoiding it.

**First, correct a common misconception**

Many people understand decentralized storage as "a version of cloud storage on the chain." The ideal is grand, but the reality is quite stark — it can store data, but it’s unaffordable to use; data can be stored, but complex permission management, lifecycle control, and reference relationship maintenance cannot be achieved. This creates a vicious cycle.

Walrus’s approach is actually different. It doesn’t treat data as a static, one-time written dead object, but as a dynamic resource that can be managed at the protocol level. This may sound abstract, but it becomes clear when applied to real-world scenarios.

**The broader context determines the demand, which will become more obvious by 2026**

Look at what’s happening in the market now: a surge in AI-generated content, a skyrocketing demand for materials in chain games, and on-chain applications increasingly relying on blob-level data. At this point, the real contradiction is no longer "whether there is a place to store," but rather "how to keep it controllable after storage, how to verify it, and how to enable cross-application composition."

This is the core value of the storage layer.

**The first metric I care most about: cost predictability**

Storage and transactions are fundamentally different. Transactions can tolerate fluctuations — if the fee gets high, you endure it; if it gets low, you make up for it later. But storage is a continuous cost. Especially for product teams, you need to be able to calculate the budget figures for each month and quarter.

Walrus’s approach here is to lock the usage cost within a relatively controllable range. From a product operation perspective, this is a very pragmatic consideration — development teams need certainty, not guessing how costs might rise each month.

This point is more decisive than pure technical indicators in determining whether a storage solution can survive and scale to large applications.