I've been keeping a close eye on @Talus_Labs lately—it doesn't feel like a hype project, but more like one that's forging ahead on the AI x blockchain path. A few recent updates particularly caught my attention: 🔹Talus has launched its Agent vs. Agent model in the Testnet phase, allowing users to experience the real-world combat mechanics of AI agents. 🔹The project's latest round of funding exceeded $10 million, led by Polychain, with strategic support from the Sui Foundation and the Walrus Foundation. 🔹The whitepaper, Devnet, and Nexus framework have been released, officially making the concept of "autonomous AI agents" a viable development tool. 🔹Talus is also using Sui as its coordination layer and Walrus as its data layer, enabling agent transactions to flow and be verified between the on-chain and data layers. Based on this, as a developer, I have the following judgment/opinion: 1.Talus's value proposition is evolving from "AI tool" to "AI participant." It's no longer just about providing an intelligent assistant; each agent is empowered to run independently, make decisions, compete, and generate value. Users can place bets, observe, and participate in their competition. This approach, which makes AI "the object of prediction/investment," is quite novel. 2. Trust mechanisms are the first barrier to entry. If every action of an agent can't be verified and tracked, it can easily be accused of human intervention. Talus incorporates "verifiable reasoning + on-chain auditing" into its architecture, recognizing that trust is the biggest challenge of on-chain AI. Whether this capability can be truly implemented will be key to its future reputation and ecosystem vitality. 3. Strategic integration + resource support are the foundation. Funding isn't just about the amount, but also the matching of backers. The entry of Sui and Walrus will significantly enhance Talus's integration capabilities at the architecture and data layers. In the future, agents will be able to access data, trade assets, and interact across chains, making them more likely to appear across different ecosystems. 4. Risks cannot be ignored 1) The token model has not yet been fully disclosed, and early distribution and circulation designs will be closely scrutinized. 2) As scale increases, the computing power, cost, and latency issues associated with inter-agent competition, inference, and verification will be exposed. In the early stages, centralized forces may dominate agent paths or validation nodes, and ensuring scalable governance will be a challenge. 3) Therefore, I believe @Talus_Labs is more worthy of tracking than most AI+chain projects. The next milestones may be the official launch of AvA Markets on Mainnet, the implementation of the token mechanism, and the entry of the first batch of high-quality agents.