Ethereum’s long-term protocol roadmap could evolve faster than expected as AI tools improve, according to Vitalik Buterin, who highlighted a recent experiment using agent coding to assemble an ambitious reference client covering much of Ethereum’s planned 2030 architecture.
The comment came after developer Jiayao Qi, posting under the name YQ via The project weighs 702,000 GB lines, covers 65 roadmap items across eight phases, passes 36,126 official Ethereum state tests, and can sync with the mainnet through integration with go-ethereum v1.17.0. Qi said the client was built in about six days using Claude Code, at a cost of about $5,750 and 2.77 billion tokens.
AI Could Accelerate Ethereum Roadmap
Buterin called the effort “a pretty impressive experiment,” while noting that a prototype built at this speed has obvious limitations. “Such a thing built in two weeks without even having the EIPs has huge caveats,” he wrote. “There are almost certainly a lot of critical bugs, and probably in some cases ‘stub’ versions of something where the AI hasn’t even tried to create the full version. But six months ago, even that was far from the realm of possibility, and what matters is where the trend is going.”
That distinction meant more to Buterin than the raw demo itself. According to him, AI does not just reduce development time. This could change the way Ethereum engineers approach insurance. “Probably the right way to use it is to take half the AI gains in speed and half the gains in safety,” he said. “Generate more test cases, verify everything formally, do more multiple implementations.”
He directly linked this to the formal verification work underway around Ethereum. Referring to the Lean Ethereum effort, Buterin said a collaborator had already used AI to produce a machine-verifiable proof of a complex theorem that underlies STARK security. “One of the core principles of @leanethereum is to formally verify everything, and AI dramatically accelerates our ability to do this,” he wrote. “In addition to formal verification, it is also important to be able to generate a much larger set of test cases. »
ETH2030 itself was presented less as a client candidate and more as a stress test for the roadmap. Qi repeatedly presented it as a draft, not production software, and argued that its value lies in shedding light on difficult engineering questions now rather than years from now.
The roadmap, as implemented in the project, aims for a version of Ethereum with over 10,000 TPS on L1, finality in seconds instead of 15 minutes, solo staking for 1 ETH, stateless nodes running on a $7 Raspberry Pi, and over 1 million TPS on L1 and L2. But the experience also highlighted deep coupling between upgrades, from blocklists and gas repricing to PeerDAS, native rollups, and rapid finality.
Qi was frank about the shortcomings. Pure-Go crypto implementations lag production code by about 10-100 times, consensus logic has not been tested on a smart tag chain, and going from about 5 million gas per second today to a target of 1 billion gas per second remains highly speculative under real-world MEV and contract dependency models.
Buterin did not claim that AI would make these problems disappear. In fact, he warned against expecting a secure protocol from a single prompt. “There will be a lot of fighting against bugs and inconsistencies between implementations,” he wrote. “But even this struggle can be fought 5 times faster and 10 times more thoroughly.”
This, more than the big numbers, is the point that now arises for researchers and Ethereum client teams. If AI can accelerate both implementation and verification, the roadmap may not be just a distant architectural sketch. As Buterin said, people should at least be open to the “possibility” that the Ethereum roadmap could be completed “much faster than expected, with a much higher level of security than people expect.”
At press time, ETH was trading at $1,956.
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