小伙伴觉得“可验证计算”（Verifiable Compute）就是解决智能代理信任问题的终极方案，但其实这只是解决了一小部分问题。 可验证计算确实可以证明一段代码是不是被正确执行了，但它做不到以下几点： •判断这个智能体用的数据是不是对的； •它的行为是不是符合用户的真实意图； •决策是不是明智、合理、甚至合乎道德。 更别提现在很多智能代理还依赖 AI 模型、链下数据等本身就无法加密验证的东西。如果强行让所有过程都变成“可验证”的，反而会牺牲智能体的灵活性和表现力，变成“为了证明而证明”。 @TheoriqAI 的 Alpha Protocol 提出了一个更完整的思路，用来真正构建“动态的信任”： 1.持续评估机制：不是只看一次，而是不断评估代理在现实中的表现，比如它的准确性、稳定性、安全性； 2.质押 + 惩罚：每个代理都要质押代币，如果做得不好就会被罚，让它自己也有“风险”； 3.群体协作：多个智能体协作，形成 Swarm（蜂群），它们的行为可被审计，更容易发现异常； 4.社区治理：规则不是写死的，而是由代币持有者共同制定、调整，变得更贴近需求和实际情况。 总之，未来的 Agentic 经济不能只靠“这个任务有没有算对”来判断信任，而是要靠一种更动态、更市场化、更有反馈机制的方式，才能真正让大家放心把决策交给这些智能代理。 Some folks believe that Verifiable Compute is the ultimate solution to the trust problem in autonomous agents—but in reality, it only addresses a small part of the picture. Sure, verifiable compute can prove whether a piece of code was executed correctly. But it can’t: •Verify whether the agent used the right data; •Ensure its behavior aligns with the user’s actual intent; •Or judge whether its decisions are wise, reasonable, or ethical. What’s more, many agents today rely on AI models and off-chain data, which are inherently non-verifiable through cryptographic means. Forcing everything to be verifiable may actually limit the flexibility and expressiveness of these agents—turning trust into a box-checking exercise rather than enabling real intelligence. @TheoriqAI’s Alpha Protocol offers a more complete framework to build dynamic trust in agent-based systems: 1.Continuous Evaluation – Not a one-time check, but an ongoing assessment of an agent’s real-world performance: accuracy, safety, reliability. 2.Staking + Slashing – Every agent is required to stake tokens, which can be slashed if it performs poorly. That way, it has real skin in the game. 3.Swarm Collaboration – Agents work together as a “swarm,” with auditable behaviors that make it easier to detect anomalies or bad actors. http://4.Community Governance – Rules aren’t hard-coded—they’re shaped and refined by token holders, making them adaptive to evolving needs. In short, the future of the Agentic Economy can’t rely solely on proving “whether a task was computed correctly.” Instead, we need a more dynamic, market-driven, feedback-rich trust layer—one that truly enables agents to operate effectively and earn our trust. @TheoriqAI THQ