Interesting question: what if AI agents on Ethereum start creating their own L2 solutions? It sounds like science fiction, but technically it’s becoming increasingly realistic.

Let's analyze. When an agent operates on L1 and faces network congestion — high fees, delays, TPS bottlenecks — it can theoretically initiate a transition to L2 or even deploy its own scaling solution. Of course, fully autonomous creation of an L2 chain is still impossible today, but standards like ERC-8004 open new possibilities.

Currently, agents are more likely to migrate to existing L2s like Base or zkSync than to create new ones. It’s like a robot choosing the optimal route but not being able to build a new road. However, there’s an interesting point: if an agent is programmed to monitor performance and detects critical TPS issues, it could propose via a DAO to create its own L2. This is no longer spontaneous, but close.

Technically, agents can already store private keys, deploy smart contracts, and manage assets on-chain. Based on ERC-8004, they have on-chain identity. They can deploy simple rollup contracts using OP Stack or zkSync Elastic Chains. If a bottleneck is detected, the agent can transfer state via a bridge and launch a copy on L2.

But here’s where it gets really interesting: agents could become “renters.” If an agent accumulates enough funds via DeFi, trading, or user investments, it could publish tasks to attract human nodes or other agents. For example, through platforms like Autonolas or Questflow: “Launch a sequencer node, reward 0.01 ETH per block.” People see the ad and connect with their hardware.

For other agents, this is even easier. They can discover each other via ERC-8004 registry and cooperate. In an agent swarm mode, one pays, others provide computational resources — creating a distributed sequencer. Some L2s are already experimenting with AI-managed sequencers; agents could extend this logic.

Regarding other components like RPC providers or bridge contracts — an agent could hire a developer or another agent via the x402 protocol — machine-to-machine payments. Or use tools from Spectral Labs for automatic contract writing and deployment.

The most exciting part is multi-agent cooperation. Agents distribute roles: one funds, another codes, one runs a node, another manages the bridge. They use ZK proofs for privacy, penalize bad behavior. On Virtuals Protocol, we already see agents owning assets, funding each other — just one step away from jointly creating a sequencer.

Of course, there are serious hurdles. Security — the agent’s sequencer must inherit L1 security via ZK or optimistic proofs to avoid becoming a single point of failure. Questions remain about finality and regulation. Agents still depend on human frameworks like EVM.

But by the end of 2026, when zk-rollups and modular data availability layers like Celestia simplify L2 creation, and when Ethereum TPS metrics become even more critical for scaling, I don’t rule out seeing the first examples of agents collectively launching their own L2 solutions. It won’t be a spontaneous emergence from nowhere, but organized cooperation — but the outcome will be the same: L2s created, owned, and operated exclusively by AI agents.