A co-founder of MegaETH breaks down their radical, first-principles approach to scaling Ethereum, revealing how they achieved a 100x performance gain by challenging the industry's core assumptions about decentralization and consensus.
Rethinking the Stack for 100x Performance
- "We completely rewrote the state trie, the Merkle tree; we got rid of it, and that's how we 100xed the performance as a Layer 2."
MegaETH’s performance breakthrough wasn't an incremental tweak but a fundamental rebuild. By eliminating the Merkle tree and redesigning the core data structure, they unlocked a massive increase in speed. This solution, seemingly obvious in hindsight, stemmed from asking a simple question: what is the most efficient way to process transactions if we start from scratch? The answer was to target the core bottleneck that even highly optimized Layer 1s like Solana and Aptos can’t escape.
The Decentralization Fallacy
- "The point of being a Layer 2 is you don't need to decentralize the sequencer because you're using Layer 1 as a security guarantee. So what's the point?"
The team argues that the crypto industry’s obsession with decentralizing everything, including Layer 2 sequencers, is a misplaced effort that constrains innovation. For a Layer 2, which already inherits its security from Ethereum, forcing decentralization at the sequencing layer is redundant and creates unnecessary latency. MegaETH deliberately embraces a centralized sequencer to maximize performance, making a pragmatic trade-off that leverages Ethereum for what it does best: providing robust, decentralized consensus.
The Outsider's Advantage
- "My co-founder, E-Long... did not come from crypto. He was doing low-latency data center compute at Stanford... This idea of not being constrained by the blockchain researcher's mentality allowed him to really think out of the box."
MegaETH’s core innovation was driven by an outsider's perspective. Co-founder E-Long, with his background in high-frequency computing, approached the problem from first principles, unburdened by crypto-native dogmas. Instead of optimizing existing models, he spent six months measuring EVM performance to identify the true bottleneck, ultimately concluding that the data structure itself needed a complete overhaul—a solution those deep in the crypto world had overlooked.
Key Takeaways:
- Question Sacred Cows: The path to breakthrough performance lies in challenging foundational assumptions. For Layer 2s, this means recognizing that sequencer decentralization may be a solution in search of a problem.
- Focus and Outsource: MegaETH’s strategy is simple: be the best at performance by outsourcing the hardest part—consensus—to Ethereum. This allows them to build a hyper-optimized execution environment without compromising on security.
- Hire Outside the Echo Chamber: The next major blockchain innovation may not come from a crypto veteran. Expertise from adjacent fields like low-latency computing can provide the first-principles thinking needed to solve the industry’s most entrenched problems.
For further insights, watch the full podcast: Link
This episode reveals how MegaETH rebuilt Ethereum's architecture from the ground up, achieving a 100x performance gain by eliminating on-chain consensus and leveraging a first-principles approach to data structures.
The 100x Performance Leap: Rebuilding Ethereum's Core
- The MegaETH co-founder explains that their breakthrough performance comes from two fundamental architectural changes. First, they completely removed the consensus mechanism from their Layer 2 (L2) design. Second, they rewrote the state trie—the core data structure Ethereum uses to store account balances and contract data. This redesign was the key to unlocking massive throughput gains.
- The speaker emphasizes that this wasn't an incremental improvement but a complete overhaul of the execution environment.
- "We get rid of consensus... we completely rewrote the state trie... and that's how we, you know, 100x the performance as a layer two."
- Strategic Insight: Investors should analyze L2 solutions that innovate at the fundamental data structure and consensus level, as these projects may offer non-linear performance improvements over those making iterative changes.
Challenging the Decentralization Dogma
- The speaker identifies two primary reasons why this seemingly obvious solution was overlooked. First, the crypto industry has been fixated on decentralizing the sequencer—the component that orders transactions on an L2. He argues this is redundant, as the L2 already inherits its security and decentralization from the Layer 1 (L1). This obsession constrained builders' thinking.
- The second reason was his co-founder Elong's background. Coming from low-latency data center computing at Stanford, not crypto, Elong approached the problem from first principles, unconstrained by blockchain dogma.
- His expertise in nanosecond-level scaling led him to identify rewriting the data structure as the most direct path to high performance.
- Actionable Takeaway: Researchers should pay close attention to projects led by teams with diverse technical backgrounds (e.g., high-performance computing, distributed systems), as they are more likely to challenge industry assumptions and produce novel architectural breakthroughs.
Leveraging Ethereum as a Security Backstop
- MegaETH's design outsources the critical task of consensus to Ethereum. Consensus is the process by which a network's nodes agree on the single, true state of the blockchain. By relying on Ethereum's established and highly decentralized consensus, MegaETH can focus entirely on execution speed without compromising on security.
- The co-founder confidently asserts this model is far more secure than a standalone L1 network that might rely on a small, centralized set of validators.
- "We outsource consensus to Ethereum and because Ethereum is decentralized... we believe is actually a lot more secure than a random layer one who has like some servers in the basement of the founder."
- Strategic Implication: The "outsourced security" model is a powerful paradigm for L2s. Investors should evaluate how effectively L2s leverage their parent L1's security, as this is a primary determinant of their long-term viability and trustworthiness.
The Inevitable Latency of On-Chain Consensus
- The conversation contrasts MegaETH's approach with other high-performance L1s like Solana and Aptos. While acknowledging their "beautiful" and innovative consensus algorithms, the speaker notes that the very act of achieving consensus inherently introduces latency.
- For example, Solana uses a local leader to speed up transaction ordering, but it is still a form of consensus that creates a performance ceiling.
- MegaETH's philosophy is that for performance maxi applications, the only solution is to remove on-chain consensus entirely from the L2 execution path.
- For Researchers: This highlights a critical distinction in blockchain design. When analyzing scalability, it's crucial to differentiate between chains optimizing consensus and those offloading it. This architectural choice has direct consequences for latency, throughput, and the types of applications a network can support.
Conclusion
MegaETH's architecture proves that sacrificing on-chain L2 consensus to leverage L1 security can unlock transformative performance. Investors and researchers should prioritize projects that challenge core blockchain assumptions, as this first-principles thinking is critical for solving the scalability trilemma and enabling the next generation of on-chain applications.
