Talking about blockchain storage, I have a deep feeling — the most comfortable days are always in the initial stage.

In the early days, data is scarce, nodes are enthusiastic, and incentives are decent, so no one feels storage is a burden. At this stage, the entire network feels very decentralized. But frankly, this is because it hasn't yet reached the point of heavy load.

The real problems are hidden in the later stages. As data accumulates more and more, node enthusiasm begins to decline, and this is precisely why my team and I are doing in-depth thinking. Storage costs and on-chain computation pressure are fundamentally different — they don't disappear with market fluctuations. Once data is on-chain, regardless of whether the market is cold or hot, or whether there are disputes, it must be accessible at all times. Many projects bet on future growth covering costs, but you can't be naive about that from the start.

Many people think that backing up data multiple times equals security; small-scale storage is indeed fine. But once the scale increases, every additional byte causes the network-wide cost to grow exponentially. The final result is: only large nodes can afford to operate, small nodes are gradually eliminated, and trust becomes more concentrated. This directly contradicts the original intention of decentralization.

How to break the deadlock? By directly avoiding this trap. Break data into fragments, with each node only holding a part of it. As long as the number of fragments is sufficient, the system remains stable and reliable. Under this approach, nodes going offline, errors, or even跑路 (跑路 means "run away" or "exit") become manageable normalities. Erasure coding technology is designed for this purpose — with enough fragments, data is secure, with no single point of dependency, and small nodes also have a place to stand. Costs are reduced, and stability is maintained without compromise.

Another common pitfall is the storage and execution being too tightly coupled. Some chains experience explosive storage costs because of this. If these complex logics are cut — no execution, no tracking balances, just keep the data static after confirmation — costs can be accurately predicted, and incentive models become much more stable. In this way, incentives are not about who stores more, but about who maintains stability. As long as small nodes stay honest and work diligently online, they can earn rewards, and trust naturally disperses.

The core advantage lies in predictability — completely isolating storage costs from execution fluctuations, enabling long-term planning. When the market rises, you can't see much difference, but during stable periods, the outcome becomes clear. Traditional models tend to centralize gradually, but this scheme can withstand pressure steadily — this is the power of meticulous design. It keeps storage reliable while controlling costs.