[Analysis of OpenLedger's smart contracts market mechanism]

1. Contracts are no longer "dead code".

Traditional blockchain smart contracts lack the flexibility for adjustment after deployment and usually can only passively wait for calls. However, in the architecture of OpenLedger, contracts are more like dynamic participating "agents"—they can both participate in execution based on on-chain tasks and bind datasets, inference models, and identity systems, thus becoming active units in the AI Agent network.

This paradigm of "smart contracts as agents" allows each contract not only to execute logic but also to possess sustainable evolutionary capabilities. For example, model validation contracts can adjust incentive allocations based on actual performance, and governance contracts can update permissions according to participant behavior.

2. The binding mechanism of tasks and contracts

OpenLedger has designed an interaction logic based on a "task market". The data tasks generated in Datanets will be transformed into on-chain demand that can be accepted. These tasks can be taken up by AI Agents, model contracts, or human participants.

Each contract registers its own capabilities, participation standards, and bidding mechanisms through modules such as OpenTask, and the system matches the most suitable contract entities based on demand and historical reputation. This mechanism not only activates idle model capabilities but also establishes a contract participation ecosystem based on trust.

3. The benefit closed loop of deployers and callers

OpenLedger not only encourages developers to deploy contracts but also incentivizes the continuous optimization of contracts through mechanisms such as revenue sharing and reputation accumulation. Deployers can set calling rules, fee structures, and verifiable return paths, and record the contribution source of each call through the Proof of Attribution (PoA) mechanism.

This model shifts contract deployment from a one-time action to "continuous operation," also introducing stronger sustainability and incentive consistency to the AI model market.