I took a look at the token economics of $OPEN. From a token distribution perspective, OpenLedger's design is quite radical: 61.71% is allocated to the community and ecosystem, an extremely high proportion among current AI projects. But there are a few issues that really concern me. 1/ Technical Challenges While the community allocation accounts for the majority, the breakdown includes: Proof of Attribution Rewards Inference Rewards OpenCircle Funding Data Network Funding Airdrops etc. Whether this complex distribution mechanism can effectively operate depends largely on whether OpenLedger's attribution technology can accurately track the impact of data on model outputs. From a technical perspective, OpenLedger's Proof of Attribution system is its core selling point. By tracking which datasets influence model outputs, it directly rewards high-impact data contributors. While theoretically ideal, its practical implementation is extremely challenging. The decision-making process of AI models is inherently a black box. How can we accurately quantify the contribution of individual data points? 2/ Ecosystem Development The token unlocking design is relatively reasonable: 21.55% will enter circulation at the TGE. The team and investors will each have a 12-month lockup period followed by a 36-month linear unlock. Community tokens will unlock linearly starting in the first month. This design avoids significant selling pressure at the opening. In terms of use cases, $OPEN carries multiple functions, including gas fees, inference payments, governance, and model deployment. However, the core question is: Can OpenLedger truly attract enough developers and data contributors to build the ecosystem? 3/ Future Outlook The biggest risk lies in the vast amounts of data and computing resources controlled by traditional AI giants. The issues OpenLedger seeks to address stem not only from technology but also from vested interests and legal frameworks.