Last night, feeling bored, I dived deep into the data panel of TokenTable, a token distribution tool under Sign, and saw that it clearly stated that in the past year, it had processed up to 40 million addresses for airdrops and unlock distributions.
Generally, retail investors seeing such exaggerated on-chain data would definitely get excited and start hyping up the explosive growth of the Sign ecosystem. However, as a practical person, my first reaction was to quickly grab the calculator at hand and furiously calculate the underlying transaction fees. Anyone with a bit of common sense can think about it; given the current congestion level of the mainnet and the high toll fees, executing 40 million point-to-point token transfers would cost at least one or two hundred million dollars. Meanwhile, Sign's publicly disclosed annual total revenue is only a little over ten million. If this business is forced to go ahead, it’s bound to lose everything.
To figure out how this account achieves a balance of income and expenditure, I directly went to the Sign developer documentation and code repository to dig deeper. It turns out that Sign did not foolishly resist these high-frequency, low-net-value transfer requests on the mainnet, but instead, they very intelligently adopted a strategy of batch distribution along with deep aggregation on a second-layer network.
In simple terms, Sign first temporarily records the massive user reception limits in an off-chain database or on a low-fee second-layer network. Once the data accumulates to a sufficiently large volume, it packages the Merkle tree root node containing all transaction records and uploads it to the main network for confirmation all at once. Moreover, to balance users' psychological expectations and interaction experience as much as possible, Sign has also implemented a very clever optimistic distribution mechanism; when you log in to the front end, you see that there is money in your account, but in reality, this asset still has to go through a twenty-four-hour confirmation withdrawal period before it can truly be liquidated.
This raises a deadly hidden cost issue in the Sign ecosystem that an ordinary investor cannot see. Now, the Sign full-chain distribution platform not only needs to be backward compatible with the large and complex Ethereum Virtual Machine system but also has to expend a huge amount of effort to manage those completely different heterogeneous chains. Even the extremely peculiar asset protocol standards from the Bitcoin ecosystem must be supported by Sign.
This means that the Sign project team must support an extremely large full-stack engineering team with very high salaries, monitoring the operational status of different public chain nodes and potential vulnerabilities in a large number of smart contracts day and night. I followed the clues to check the commit history of Sign's open-source code repository and indeed saw several urgent patches that precisely addressed errors in the underlying calculations caused by the extremely complex phased unlocking logic proposed by the project team.
So I don't pay attention to how many partners the Sign marketing department boasts about on social media anymore; I am only focused on the operational data from the upcoming quarterly financial report.
If the distribution cost for the next forty million addresses by Sign can be significantly reduced through technological iteration, it indicates that their underlying architecture has been thoroughly tested and can greatly empower the Sign token. If the marginal cost continues to rise, then this multi-chain distribution model faces expansion bottlenecks.