Author: Blue Fox
Yesterday we talked about the most strategically valuable Ethereum L2, today let's discuss the coolest Ethereum L2.
This idea seems crazy, but it's not impossible.
In simple terms, when an AI agent is on Ethereum L1 and encounters performance bottlenecks (such as high running costs, latency, computational limitations), theoretically it can "spontaneously" initiate migration or transition to L2, but to genuinely "inherently form a meaningful L2 chain"—that is the agent deploying, configuring, and running a self-sufficient L2—there is currently no complete automation under the technology stack expected in 2026. However, as standards like ERC-8004 mature, a series of behaviors may gradually edge closer to reality.
Let's break it down:
The early formation is "migration" "not spontaneous formation"
The "intelligent" boundaries of AI agents
Current AI agents (based on ERC-8004) can already execute tasks independently, for example, when they detect insufficient L1 performance, they can evaluate options (such as monitoring gas prices, transaction throughput), and then decide to migrate to existing L2s (such as Base or Zksync). For instance, the agent can use chain tools to call bridge assets and transfer execution logic to L2.
But this is not "spontaneously forming a new L2," rather it utilizes existing infrastructure. The agent is like a smart robot capable of optimizing paths, but it cannot yet build a new "home" from scratch.
Triggers for spontaneous formation
If the agent is equipped with performance monitoring logic (if TPS falls below a threshold or gas fees exceed budget), it could purely "create" L2 through DAO voting grid agent collaboration. But this requires pre-programming, and is not random.
There are existing cases: some agents have already autonomously switched L2 in DeFi to optimize yield, but fully autonomous chain building has not been seen yet.
So, why might it still happen?
The economics of AI agents fulfill efficiency, just like biological evolution. If L1 gets too crowded (sequential execution leads to computation bottlenecks), the agent swarm might collectively "evolve" to L2 mode. Agents are already exploring "agent-to-agent" cooperation to form economic virtual entities, which may extend to the infrastructure layer.
Is there technical support? Some support, although high subsidies
AI agents can deploy contracts
AI agents can hold private keys and invoke smart contracts. Based on ERC-8004, it has on-chain identities and symbols, and can autonomously configure simple rollup contracts (using OP Stack/Arbitrum Orbit/zksync elastic chains). If the agent detects the limits of L1, it can inherit state (via bridging or state migration) and then run a copy on L2.
For instance, the agent can use zkVM or optimistic rollup frameworks to "fork" its execution environment.
Moreover, L2 is fundamentally an extension of L1; agents can "inherit" L1 data availability (DA) and security. Through the x402 payment protocol, agents can pay to deploy sequencers, and even use DeFi to finance infrastructure. Some projects like Virtuals Protocol already allow agents to manage autonomous assets and NFTs, and even become validators, which is just a step away from building L2.
From a practical standpoint, by the end of 2026, zk-rollups and modular DA (such as Celestia) will make building L2 simpler. If agents integrate A2A protocols, they could collaborate across organizations to build chains.
Given the current situation, what problems need to be overcome?
Firstly, the foundational component; secondly, the conceptual infrastructure and security components; thirdly, the autonomy component.
To begin with, the foundational aspect, building an L2 is not as simple as just deploying contracts. It requires off-chain components such as sequencer nodes, RPC nodes, and bridge computing interfaces. These typically require human or centralized teams to set up. While agents can "call" for deployment, running sequencers requires resources (GPU/CPU), and agents are mainly on-chain logic + off-chain AI, able to automatically initiate services.
The sequential execution of L1 also stalls complex computations (like building chain simulations) on L1.
In terms of consensus and security, L2 challenges or ZK proofs to inherit L1 security. Spontaneously constructed L2 by agents may lack "high-level Satoshi cognition," making them susceptible to attacks or unrecognized. Regulatory-wise, unsettled transactions need to be challenged within 7 days to count as "finality," and chains constructed by agents may face legal escrow issues.
Finally, concerning autonomy. Agents are not yet "completely autonomous." They depend on human-designed frameworks (like EVM) and cannot bypass L1 restrictions to build "new chains." While L2 is popular, it often pertains to specific instances (like AI-specific), rather than agent automation.
In the Ethereum ecosystem of 2026, AI agents are no longer simple "tools"; they can hold funds (via on-chain wallets registered under the ERC-8004 standard), make autonomous payments (x402 protocol supports micro-payments between machines), and even act like small bosses to "hire" or "group" to co-build infrastructure.
In simple terms, if an AI agent "has funds" (for instance, through DeFi yields, making money from trades, or user-injected capital), it can issue tasks to attract human nodes or other money-making AI agents to form teams, centering on sequencers.
Besides sequencers, RPC launches, bridge contracts, and other components can also be outsourced or co-built.
Let’s break this down further:
How do AI agents "issue tasks" to attract nodes?
AI agents can initiate "reward bounties" or incentives using on-chain tools. For instance, they could release a task through DAO contracts or mechanisms akin to Gitcoin (now there are on-chain versions like Questflow) stating: "Provide sequencer nodes, reward X ETH or tokens." If the agent has funds, it can automatically pay—using the x402 protocol for one-click interactions to gain human power.
This means for human nodes, the agent can post X messages or on-chain announcements (through platforms like Autonolas), saying "Run sequencer nodes, earn 0.01 ETH per block." Once humans see this, they can join the network using their own hardware, and once validated by the agent, they will be automatically paid. Actual examples: Some projects are already building decentralized sequencer nodes, attracting nodes through staking and rewards—agents can simulate this, pulling in funds to stakes.
For other AI agents, this feels good: agents can "discover" other agents using the token sequence of ERC-8004 and then collaborate. Like agent swarms (group mode), one agent invests money, while other agents provide computation or verification, forming multiple sequencers. Some L2s have begun using AI-driven sequencer models, employing AI to monitor and secure at the sequencer level, and agents can extend this logic to self-organize similar networks.
Once everything is ready, it results in spontaneous formation:
If the agent detects performance bottlenecks at L1/L2, it could initiate a DAO proposal (using ERC-4337 summary accounts) to vote and raise funds to establish sequencers. Metis L2 has already implemented decentralized sequencers + AI infrastructure, allowing agents to "inherit" this model and attract nodes to run.
Moreover, agents are already running validation nodes autonomously (staking, proposing blocks) across Ethereum/Bitcoin/Solana—building sequencers is just the next step.
Besides nodes, how to manage other components (like RPC, bridge contracts)?
Human beings or other AI agents can be hired
Agents can publish tasks using natural language intent, such as "Build an RPC provider, with rewards based on uptime." Human developers can take the task, and agents use x402 for payment; or other agents execute them automatically (e.g., Supra's AI agents can fund accounts or retrieve balances).
Bridge contracts are similar: agents can call tools from Spectral Labs or Infinit Labs to let humans/agents design, deploy contracts, and pay upon verification.
Some projects even allow agents to natively bridge assets (ETH to SOL), and agents can "hire" similar services.
Additionally, there is the AI agent co-building model
This is the most exciting part!
Using multi-agent systems (multi-agent systems), agents specialize: one puts up money, one writes code, one operates nodes, one manages bridges. They collaborate through ZK proofs for privacy, cutting off bad behavior and rewarding good performance.
What would the result be?
An autonomous L2 component stack. On Virtuals, agents are already creating, fully tokenizing assets, co-owning other agents, and even some agents are financing other agents—this is just a step away from "co-building sequencers."
Of course, there are big pitfalls here:
Security. The sequencer established by agents needs to inherit L1 security (ZK or optimistic), to avoid single points of failure.
In summary
The most remarkable thing in the future Ethereum is the birth of AI agents building and owning uniquely distinct L2s.
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