Vitalik's Lost Bet: One Person Uses AI to Run Through Ethereum's Future 5 Years in 6 Days

Article by Bibi News

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Two weeks ago, Vitalik made a bet with a developer named Yaq: can one person use AI programming tools to write the entire Ethereum 2030+ roadmap into code?

No one expected results so soon. But now, Yaq has completed it. 700,000 lines of Go code, 2,000 files. It took 6 days, cost $5,750, and passed 36,126 official tests—all successfully. The code compiles, runs, syncs 9,000 blocks per second from the testnet, and connects to the Ethereum mainnet.

This project, called ETH2030, may be the largest technical roadmap validation in blockchain history.

6 days, 700,000 lines

Imagine this scenario: a developer, using Claude Code (Anthropic’s AI coding assistant), writes 700,000 lines of code in six days.

What does 700,000 lines mean? The Linux kernel has 30 million lines. Chrome browser has 170 million lines. A full production-grade database has about one million lines.

Within Yaq’s 700,000 lines is the complete technical blueprint for Ethereum’s next five years: full-stack implementation of consensus layer, data layer, execution layer; cryptography, zero-knowledge proofs, RISC-V CPU, Verkle trees—all among the most complex parts of Ethereum’s plan.

If you tell a software engineer this story, their first reaction is usually: how is this possible?

Because traditionally, what’s the approach? Find a team of 10 to 20 people, spend two to three years, to produce a reference implementation.

But AI has changed everything. Six days, one person, one prompt, one code review process—boom, 700,000 lines of code that can compile, test, and sync to the mainnet.

A one-person super-team

This signifies two key changes.

First, costs have decreased by an order of magnitude. Projects that previously required millions of dollars now cost only $5,750. Second, the detection of issues has moved earlier.

Before Yaq’s code release, these potential problems were hidden in specifications; no one had really tried to integrate them all. Now, anyone can download the code, see the actual implementation, and raise real issues.

Using AI, one person effectively has a super-team. Yaq validated whether a multi-billion ecosystem’s technical roadmap is self-consistent. He exposed problems hidden deep within specifications. He gave the entire community a chance to review Ethereum’s future four years in advance.

But this also reveals AI’s fundamental limitation: no matter what AI can do, it can never make true strategic decisions. Should Ethereum complete this upgrade before 2030? How should the roadmap be prioritized? Which risks are acceptable? Only humans can answer these questions. Only the Ethereum community can.

Yaq’s work provides a clear framework for this decision-making process—a framework with code, tests, and specific issues.

The bottleneck of the blueprint

When Yaq integrated all 65 future upgrades into a single codebase, the perfect blueprint on paper began to show challenges at the code level.

First, cryptography. Yaq wrote all cryptographic parts (including BLS signatures, KZG commitments) entirely in pure Go.

The result? It’s 10 to 100 times slower than optimized specialized versions. This isn’t due to coding errors but because he deliberately chose a fast verification route. Switching to C or Rust for acceleration would at least double development time.

Now, everyone can clearly see a key issue: in a real network, will this speed gap slow down the entire system to a crawl?

Next, parallel execution. Ethereum aims to process multiple transactions simultaneously, which could be a game-changer. But in reality, transactions often conflict or compete for resources.

Even more critically, some malicious actors might intentionally create conflicts to sabotage parallel performance. These adversarial risks will only surface once the code is running.

Finally, the timeline. The 65 upgrades are like a chain—if one link is late, the rest must wait. This systemic vulnerability, previously hidden in documents, now becomes something everyone can discuss and proactively address.

Yaq’s goal isn’t to say the roadmap is flawed. He wants to bring these real risks forward today, so the community can see clearly at the code level and make smarter decisions early.

Four-year challenge

There are four years until 2030.

Ethereum needs to complete a major upgrade within this period: increase processing capacity from 5 million gas/sec to 1 billion gas/sec; reduce transaction confirmation time from 15 minutes to seconds; enable ordinary users to verify the network with just 1 ETH; and even run full nodes on Raspberry Pi.

Simultaneously, it must migrate to post-quantum cryptography—upgrading nearly 200 million old accounts, coordinated across 8 phases, with any delay causing chain reactions.

Meanwhile, competitors like Solana and Monad are already delivering high-throughput solutions in the real world. This is no longer just a technical challenge but a race against time and confidence.

Yaq used 6 days to simulate Ethereum’s five-year future, bringing the problems from 2030 into today.

The code is open source, and tests are passing. Now it’s up to community engineers, researchers, and cryptographers to scrutinize, identify bottlenecks, and decide what needs optimization or redesign.

This process might adjust the timeline, but it’s much better than discovering fundamental incompatibilities in 2028.

The future validated early

Did Vitalik’s bet lose? Yaq completed what seemed impossible in just six days.

But on a broader level, the Ethereum community has won. We are no longer just imagining the future on paper; we can download the code, run it, and see what Ethereum in 2030 will look like.

We can ask the toughest questions early: Why is this design chosen? How will it hold up under real pressure? Can this assumption last four years?

These 700,000 lines of code may become a guide for Ethereum development over the next four years, or they may be heavily rewritten during community iterations. But at least, the direction is clear, and the issues are explicit.

In the AI era, the boundaries of what one person can do are constantly being broken. What seemed impossible six days ago has now happened. AI enables us to verify the future at an astonishing speed, providing precise questions rather than abstract discussions.

Yaq has proven: one person + AI can simulate Ethereum five years into the future, bringing the problems from 2030 into today.

We now have a tool to rapidly simulate the future—an opportunity and a pressure. The opportunity to discover real issues earlier; the pressure to make faster decisions—because every hesitation means a competitor moves ahead.

The future is being simulated by us, ahead of time.