Written by: Haotian
Many people believe that the Ethereum Layer2 ecosystem is beyond recovery, but that's not necessarily true. If viewed solely from the TPS arms race perspective, there is indeed a sense of decline. However, after the Pectra technical upgrade, some Layer2 solutions might still have a chance if they can reposition themselves correctly. Recently, @MetisL2 released an "All in AI" strategic roadmap. Can this alternative choice break through the current Layer2 predicament? Let me share my observations:
1) To be honest, the fundamental problem facing the current Layer2 ecosystem is not a lack of technical capabilities, but the solidification of narrative boundaries. Most projects are still using the linear thinking of "faster speed, cheaper gas", which leads to a homogeneous competitive landscape with too many generic Layer2 solutions. The technical differences are becoming smaller, while the users' real pain point—the lack of killer applications—remains unresolved.
After in-depth research into METIS's technical route, I discovered that its true innovation lies not in breakthrough of a single technology, but in systematic architectural reconstruction. The dual-network strategy (Andromeda + Hyperion) is essentially a clever solution to the classic trade-off between "generality vs. specialization".
Clearly, METIS aims to maintain the stability and reliability of Andromeda, its existing Layer2, providing mature DeFi and Web3 application infrastructure. On the other hand, it seeks to develop a high-performance execution layer specifically serving AI scenarios, transitioning from a generalist technology stack to specialized AI infrastructure. This approach not only avoids homogeneous competition with other Layer2 solutions but also finds a technical implementation path for AI+Web3 integration (providing Ethereum ecosystem with a viable breakthrough strategy?).
2) Many were already familiar with METIS's decentralized Sequencer and Hybrid Rollup technological innovations on the Andromeda chain. What's special about this brand new Hyperion AI chain?
1. MetisVM, a virtual machine deeply customized for AI applications, improves execution efficiency by 30% through dynamic opcode optimization, which is a qualitative leap for AI inference scenarios. More critically, the MPEF parallel execution framework resolves the contradiction between blockchain's serial processing and AI's concurrent demands;
2. MetisDB, using memory-mapped Merkle trees and MVCC concurrency control, achieves nanosecond-level state access. This design completely eliminates storage bottlenecks, providing hardware performance guarantees for high-frequency AI computations.
Based on the above background, understanding MetisSDK becomes easier. Simply put: MetisSDK, based on modular components and standardized interfaces, has built a development toolkit specifically serving AI applications, abstracting complex chain-level technologies into composable building blocks, effectively lowering the development threshold for AI applications.
3) From my personal observation of the web3AI industry, the current biggest problem is not a lack of technical capabilities, but a distorted value distribution mechanism. Large platforms monopolize most of the value, with data providers receiving almost no benefits. In other words, current AI is a black box: Where do training data come from? How do algorithms work? Can the results be trusted? These questions remain unclear.
LazAI attempts to change this situation through three core innovations:
1. iDAO model, redefining AI governance structure. Unlike traditional DAOs, iDAO makes every individual or AI agent a governance participant, not a passive data provider. To some extent, this is a "replacement" of the current centralized AI governance model.
2. DAT (Data Anchoring Token), with a particularly clever design approach. Unlike traditional Non-Fungible Tokens that only record static ownership, it tracks the entire lifecycle of AI assets. This innovation can directly solve the fundamental problem of difficult data value quantification in the AI economy.
3. Verifiable computation provides transparency for AI behavior. It's like installing a "black box" for AI, where all inference processes can be verified, traceable, and accountable. This "verifiable AI" approach provides a trust foundation for decentralized AI applications.
This combination design is like building a brand new "value distribution engine" for AI+Web3 integration. If DeFi established a financial value system through metrics like TVL and APR, LazAI is constructing a similar quantification framework for AI.
In summary, the current METIS technical framework, in my view, is like a sandwich structure: the bottom layer is METIS itself, providing unified governance mechanisms and token incentives; the middle layer is Hyperion, specifically handling high-performance AI computations; the top layer is LazAI, defining value flow rules. This layered design is not a simple technical stacking, with each layer being both independent and collaborative, avoiding the "omnipotent" trap of traditional single-chain architectures.
Regarding the token economics that everyone is most concerned about, the $METIS token will naturally be upgraded simultaneously. As the native token of the dual network, METIS's income sources are more diverse than traditional Layer2: besides transaction fees, there are also new income sources like computation fees and data verification fees. The introduction of the Holders Mining income sharing model transforms token holders from passive speculators to ecosystem value sharers.
Overall, METIS's exploration has opened a new path for Layer2 development. In the current context of severe technological homogenization, scenario differentiation might be the key to breaking through. Whether it will succeed depends on specific execution, but at least the direction seems well-chosen. (Looking back, the narrative positioning of the decentralized Sequencer was at least successful).
