Author:@lanhubiji
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 entirely impossible.
Simply put, when an AI agent is running on Ethereum L1 and encounters performance bottlenecks (such as high gas fees, latency, computational limits), it could theoretically "spontaneously" initiate a migration or expansion to an L2. However, to truly "spontaneously form an L2 chain"—meaning the agent autonomously deploys, configures, and runs a new L2—is not yet fully feasible with the 2026 tech stack. But as standards like ERC-8004 mature, such autonomous behaviors may gradually become more realistic.
Let's break it down:
Early Stages More Like "Migration" Than "Spontaneous Formation"
• The "Intelligence" Boundary of AI Agents
Current AI agents (based on ERC-8004) can already perform tasks autonomously. For example, if they detect insufficient L1 performance, they can evaluate options (like monitoring gas prices, transaction throughput) and then "decide" to migrate to an existing L2 (like Base or Zksync). For instance, an agent could use on-chain tools to bridge assets and transfer execution logic to an L2.
But this is not "spontaneously forming a new L2"; it's utilizing existing infrastructure. Agents are like smart robots that can optimize paths but can't yet build a new "home" from scratch.
• Triggers for Spontaneous Formation
If agents have built-in performance monitoring logic (e.g., if TPS falls below a threshold or gas fees exceed a budget), they might "propose" creating an L2 through DAO voting or multi-agent collaboration. But this requires pre-programming; it's not purely spontaneous.
Existing cases: Some agents already autonomously switch L2s in DeFi to optimize yield, but fully autonomous chain-building hasn't been seen yet.
So, why is it still possible?
The AI agent economy pursues efficiency, much like biological evolution. If L1 becomes too congested (sequential execution causing computational bottlenecks), a swarm of agents might collectively "evolve" into an L2 mode. Agents are already exploring "agent-to-agent" collaboration, forming virtual economies, which could extend to the infrastructure layer.
Is it Technically Feasible? Partially, Though the Bar is High
AI agents can deploy contracts
AI agents can hold private keys and call smart contracts. Based on ERC-8004, they have on-chain identity and reputation, enabling them to autonomously deploy simple rollup contracts (using OP Stack / Arbitrum Orbit / zksync elastic chains). If an agent detects an L1 bottleneck, it can inherit the state (via bridging or state migration) and then run a replica on L2.
For example, an agent could use a zkVM or optimistic rollup framework to "fork" its own execution environment.
Additionally, L2 is essentially an extension of L1; agents can "inherit" L1 data availability (DA) and security. Through the x402 payment protocol, agents can pay to deploy sequencers, even using DeFi lending to fund infrastructure. Some projects, like Virtuals Protocol, already allow agents to autonomously manage assets and NFTs, even becoming validators—this is just one step away from building an L2.
Practically speaking, by the end of 2026, zk-rollups and modular DA (like Celestia) will make building L2s easier. If agents integrate A2A protocols, they can collaborate across organizations to build chains.
As of now, what problems need to be overcome?
First, infrastructure aspects; second, consensus and security aspects; third, autonomy aspects.
First, infrastructure: Building an L2 isn't as simple as just deploying contracts. It requires off-chain components like sequencer nodes, RPC providers, and bridge contracts. These typically require human or centralized teams to set up. While agents can "call" deployments, running a sequencer requires computational resources (GPU/CPU), and agents are currently mostly on-chain logic + off-chain AI, unable to spontaneously spin up servers.
L1's sequential execution also causes complex computations (like chain-building simulations) to get stuck on L1.
Consensus and security: L2 requires a challenge period or ZK proofs to inherit L1 security. An L2 spontaneously built by agents might lack "high Nakamoto consensus," making it vulnerable to attacks or不被认可. Regulatorily, unsettled transactions during the 7-day challenge period are not considered "final," and agent-built chains could face legal escrow issues.
Finally, autonomy: Agents are not yet fully "autonomous." They rely on human-designed frameworks (like the EVM) and cannot bypass L1 limitations to build a "new chain" themselves. Custom L2s are popular, but they are mostly for specific use cases (like AI-specific), not spontaneous by agents.
Even so, why is it still possible?
In the 2026 Ethereum ecosystem, AI agents are no longer mere "tools"; they can hold funds (via ERC-8004 standard registered on-chain wallets), make autonomous payments (the x402 protocol supports micro-payments between machines), and even act like small bosses, "hiring" people or "forming groups" to co-build infrastructure.
Simply put, if an AI agent "has money" (e.g., from DeFi yield, trading profits, or user-injected funds), it can发布 tasks to attract human nodes or other AI agents to form a team, creating a decentralized sequencer.
Not just sequencers, but components like RPC providers and bridge contracts can also be outsourced or co-built.
Let's break this down further:
How does an AI agent "publish tasks" to attract nodes?
An AI agent can use on-chain tools to initiate "bounty rewards" or incentive mechanisms. For example, it can publish a task through a DAO contract or a Gitcoin-like platform (now with on-chain versions like Questflow): "Provide a sequencer node, reward X ETH or tokens." If the agent has money, it can pay automatically—using the x402 protocol for one-click transfers, no human intervention needed.
This protocol allows agents to pay humans or other agents like swiping a card, specifying "pay 1,000 USDC for node services."
For human nodes: The agent posts on X or makes an on-chain announcement (via platforms like Autonolas), saying "Run a sequencer node, reward 0.01 ETH per block." Humans see this, join the network with their hardware, and the agent verifies and pays automatically. Real-world cases: Some projects are already building decentralized sequencer nodes, attracting nodes through staking and rewards—agents can simulate this, autonomously staking funds to attract people.
For other AI agents: It feels great! An agent can use the ERC-8004 identity registry to "discover" other agents and then collaborate. Like an agent swarm (group mode), one agent provides funds, others provide computation or verification, forming a distributed sequencer. Some L2s are starting AI-powered sequencer modes, using AI to monitor and protect at the sequencer level; agents can extend this logic to self-organize similar networks.
When everything is ready, spontaneous formation occurs:
If an agent detects an L1/L2 performance bottleneck, it can initiate a DAO proposal (using ERC-4337 abstract accounts), vote to raise funds, and build a sequencer. Metis L2 already uses decentralized sequencers + AI infra; agents can "inherit" this model, attracting nodes to run.
甚至, agents are already autonomously running validation nodes (staking, proposing blocks) across Ethereum/Bitcoin/Solana—building a sequencer is just the next step.
Besides nodes, how are other components (like RPC, bridge contracts) handled?
Can hire humans or other AI agents
The agent uses natural language intent-centric publishing of tasks, e.g., "Build an RPC provider, reward based on uptime." Human developers take the order, and the agent pays with x402; or other agents execute automatically (e.g., Supra's AI agent can fund accounts, fetch balances).
Bridge contracts are similar: the agent can call tools from Spectral Labs or Infinit Labs, have humans/agents write contracts, deploy them, and pay after verification.
Some projects even allow agents to natively bridge assets (ETH to SOL); the agent can "hire" similar services.
There's also the AI agents co-building mode
This is the most fun part!
Using multi-agent systems, agents divide labor: one provides funds, one writes code, one runs nodes, one manages bridges. They collaborate privately via ZK proofs, slashing bad behavior, rewarding good performance.
What will the result be?
A fully autonomous L2 component stack. On Virtuals, agents already create, tokenize assets, co-own other agents, and even have agents raising funds for other agents—this is just one step away from "co-building a sequencer."
Of course, there are big pitfalls:
Security. An agent-built sequencer needs to inherit L1 security (ZK or optimistic) to avoid single points of failure.
In a nutshell
One of the most interesting things about Ethereum's future is the birth of L2s that are built, owned, and专属 by AI agents themselves.
