After several rounds of narrative switching, discussions about public blockchains seem to become increasingly data-driven. Recently reviewing the market, I increasingly feel that when evaluating the value of public chains, we have been overly reliant on one indicator for a long time: the flow of funds. TVL and DEX trading volumes are certainly important, but the problem is also very clear. In this market, funds have almost no loyalty and tend to go wherever the returns are higher. This kind of prosperity often comes and goes quickly. This made me start thinking about whether there are any other perspectives that can reflect the long-term survival ability of a chain in the mature cycle of 2026. A very simple business concept that I recently agree with is conversion cost. If a chain only provides another trading or financial option, then it is essentially replaceable. But if it were written into real-world business processes, especially in cross-border trade, logistics, or administrative systems, the situation would be completely different. The strategic report recently released by @ iota appeared on my timeline, and the discussion in the English section was very high. There are several specific numbers that I am very interested in: In Kenya, the data related to flower exports covers approximately 7 million physical goods per day and has entered a stable on chain processing flow. In the UK, trade pilots with the EU have covered thousands of real shipments, and the relevant data is used in actual cross-border customs clearance and regulatory processes, providing visual records of goods flow for border agencies. These are not just making a statement about an NFT as a 'exhibition collaboration'. For government agencies or large supply chains, replacing such an underlying system means reconnecting processes, training personnel, and repeating compliance audits. This cost itself constitutes a moat. Another point that concerns me is how these real businesses are reflected in on chain behavior. According to public information from IOTA, an average of about 26 transactions are generated on the chain for a shipment, including document uploads, status updates, and more. If we zoom in on this model, just digitizing 1% of global trade processes, the IOTA mainnet could generate 650 million non speculative transactions annually. The characteristics of this type of transaction are stability, repetition, and inevitability. IOTA, as a transaction fee, has been burned at the protocol level, introducing deflationary pressure to some extent, more like infrastructure usage fees. At the same time, trade documents and assets on the blockchain need to lock tokens as storage or existence guarantees, and as long as the business is still ongoing, these IOTA tokens cannot be withdrawn from circulation. Looking at these points together, you will find an interesting phenomenon: When the business itself has high conversion costs, and the on chain mechanism converts usage behavior into continuous consumption and locking, the value source of this chain is no longer entirely dependent on market sentiment. The flowing water is not competitive, the competition is endless. It is expected that by 2030, the annual amount of funds operating on blockchain will exceed 393 billion US dollars. But the market will not pay for all hype, and most blockchain networks that lack clear goals, unique selling points, and application cases will eventually be eliminated by the real world. So now looking at public blockchains, I will deliberately ask one more question: Besides how much money is on the chain, how many businesses are running on this chain that are difficult to replace once used? This perspective may not necessarily bring short-term stimulation, but it may have more reference value than a single financial indicator when filtering noise and assessing long-term survival ability.