Author: Haotian
As the last resilient backbone of the previous wave of on-chain AI Agents, it is truly baffling that after issuing a significant "positive news" with V1, it continued to accelerate its decline. However, in a crypto market that urgently needs external positive stimuli, such "positive news" related to blueprint planning seems insufficient and may even be interpreted as underwhelming, leading to further declines? Anyway, let me share my thoughts after reading the arc V1 litepaper:
1) From Rig as the underlying Rust framework to its catching up with #ai16z to launch the Launchpad, the technical fundamentals of $arc have always been relatively solid and stable. This is likely the key to its ability to reverse the tide multiple times during the turbulent times of the entire AI Agent market.
However, as I mentioned in my previous analysis of manus, web3 AI Agents have always lacked the innovative drive comparable to web2 AI Agents. Many AI Agents remain immersed in some vague and ethereal visions, leading to a frustrated market sentiment towards web3 AI Agents.
Therefore, not just arc, but the overall market capitalization of on-chain AI Agents has been sharply decreasing recently, urgently needing a new hope to emerge on-chain. Thus, I believe the issues with arc itself are not significant; it is just a bit difficult for a single project to break through the overall downward trend of the sector at this stage.
2) The core feature of arc V1 is an "AI Agent application store" called Ryzome, which can connect both web2 and web3 AI Agents. To be honest, during the key period when manus was highly sought after, Arc launching Ryzome does seem a bit like riding the coattails of a trend. However, once you understand the architectural concepts and specific measures behind Ryzome, your perspective will change.
The overall design architecture of Ryzome follows the interactive operational protocol layer concept commonly used in web3, essentially building a multi-chain architecture similar to Cosmos. Ryzome serves as its IBC relay chain interoperability protocol, enabling interoperability between different blockchains. Therefore, Ryzome's claim to connect web2 AI Agents and web3 AI Agents is not unfounded.
In the core technical architecture of Ryzome, there is an Anthropic model context protocol (MCP) that acts as a translator in the AI field. When compared to the Cosmos architecture, it functions as a webAssembly (WASM) bridge, allowing Agents using different API service interfaces to achieve interoperability.
The white paper states that this is similar to AI's HTTP, enabling AI Agents running on platforms like Nation, Slack, and Google Calendar to seamlessly connect to the Ryzome system. Notably, many web2 AI Agents are fundamentally "data islands" due to their centralized server architecture. The MCP "compiler" can also facilitate data interoperability between web2 AI Agents, building a unified standardized interface and communication language for them, thus eliminating barriers to cross-platform collaboration.
Overall, aside from the somewhat devalued name definition of "application store," the other frameworks and design concepts of Ryzome align well with the future concept of multi-AI Agent interactive communication. Even if people criticize arc for merely riding concepts, it is still commendable to have developed such a comprehensive architecture within a day or two of manus's launch.
3) Regarding the subsequent application scenarios of the Arc token, the white paper mentions that arc will become the main fuel of the Ryzome ecosystem, driving the entire system's operation. This means that as long as web2 and web3 AI Agents use this standard to interact, their transaction fees will be settled using arc.
In other words, if web2 Agents want to interact, they will also need to use arc as fuel. After seeing the multi-modal execution agent built by manus, everyone realizes that the future of Agents will definitely move towards a large-scale collaborative application era. In this context, arc providing a set of incentive models and frameworks with its own tokens actually makes sense.
That's all.
I really don't want to discuss why value isn't supported by price during a downward trend. In fact, looking at the long term, whether there is a need for interoperability between web2 AI Agents and web3, what will support the ecosystem after Agent interoperability generates transactions, and whether the trend of the future AI Agent sector will continue are all important questions. Once you understand these, you can objectively view the above analysis and grasp what I am expressing.
During a market uptrend, no one cares about technical and operational fundamentals, which is understandable. However, during a market downturn, if the technical and operational fundamentals are equally ineffective, then let’s just give a little confidence to those who believe!
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