This episode reveals Monad's audacious bid to fuse Ethereum's robust compatibility with Solana's raw performance, creating a high-throughput, fully EVM-compatible Layer 1 blockchain.
Monad's Genesis: HFT Roots & EVM Performance Gap
- Keone, Monad Labs CEO, details his decade in high-frequency trading (HFT) at Jump, where systems processed millions of packets daily in microseconds. This experience exposed him to the critical need for ultra-low latency and high-scale operations, a stark contrast to existing decentralized finance (DeFi) infrastructure.
- Keone observed a significant performance gap in Ethereum Virtual Machine (EVM) execution, noting that scaling efforts largely focused on Layer 2 (L2) solutions and data availability, neglecting core execution efficiency.
- Jump's crypto team, particularly active in Solana DeFi, highlighted the demand for fractional-cent transaction fees to support high-volume trading, like on-chain order books.
- Current DeFi experiences 1-2% slippage on trades as small as $10,000-$50,000, a direct result of market makers' inability to update quotes frequently due to high transaction costs.
- Monad aims to bridge this execution quality and cost gap, initially for crypto-native applications, eventually targeting traditional assets (Real-World Assets or RWAs) for more efficient, transparent, composable, and self-custodial settlement.
- Keone states, "The experience when trading in DeFi right now is to pay a huge amount just in order to make in terms of price impact in order to make a trade."
Monad Architecture: Parallel Execution & Deferred Consensus
- Monad rebuilds Ethereum's stack from scratch across storage, execution, and consensus layers, introducing fundamental optimizations to achieve 10,000+ transactions per second (TPS) with 1-second block times and single-slot finality.
- Optimistic Parallel Execution: Unlike Ethereum's serial transaction processing, Monad executes multiple transactions concurrently. It tracks inputs and outputs for each, then commits results in the original order. If an input changes due to a prior transaction, the conflicting transaction re-executes, ensuring determinism while maximizing throughput.
- Deferred Execution: Monad decouples consensus from execution. Nodes first agree on transaction ordering (consensus) and then execute those transactions in parallel with the next block's consensus. This dramatically increases the execution budget, allowing full block time utilization.
- Ethereum's interleaved consensus and execution limit its execution budget to about 100 milliseconds per 12-second block, roughly 1% of total block time, due to network overhead.
- Keone attributes Ethereum's initial serial design to simplicity and deterministic outcome assurance, noting that parallelization is a more complex, later-stage optimization.
- Keone explains, "In Monad, execution is moved out of the hot path of consensus into a separate swim lane."
Monad DB & Monad BFT: State Access & Scalable Consensus
- Monad DB (Custom State Database): The biggest bottleneck for execution is state access, not computation. Existing Ethereum clients store the Merkle tree (a data structure used for efficient data verification) within another database (e.g., LevelDB), leading to "read amplification" where each Merkle tree node traversal triggers multiple disk lookups.
- Monad DB stores the Merkle tree directly on Solid State Drives (SSDs), drastically reducing lookups and efficiently utilizing SSD bandwidth. This ensures that even re-executed transactions (due to optimistic parallel execution conflicts) are fast because dependencies are often already cached in memory.
- Monad BFT (High-Performance Consensus Mechanism): Monad BFT is a derivative of the HotStuff consensus algorithm, designed for hundreds of globally distributed nodes. HotStuff features linear communication complexity, meaning the leader communicates directly with validators, and validators send votes to the next leader.
- This linear communication scales efficiently with the number of nodes, unlike quadratic complexity algorithms (like Tendermint), which limit network size (e.g., Tendermint's ~100-node limit). Monad BFT also incorporates pipelining for further latency reduction.
- Keone asserts, "The single biggest bottleneck for execution is actually state access... The thing that's slow is looking up any state variables from SSD."
Community as Product: Monad's Strategic Approach
- Monad views community as crypto's "superpower," essential for expanding reach and adoption beyond current users. The team adopted a product-driven mindset for community building.
- Monad prioritizes creating an enjoyable, engaging experience for community members, contrasting with "questing platforms" that often generate low-value, spammy content.
- During the 2022 bear market, Monad focused on providing a "home" for crypto enthusiasts, fostering genuine connections and creativity while actively filtering out bots and spammers.
- This strategy resulted in a highly engaged, creative community that has grown into a movement even before the mainnet launch.
- Access to inner community circles is gated to ensure genuine human interaction, requiring new members to engage in public chats before gaining full access.
- Keone emphasizes, "Community is in the early days the community is the product. So we should have a very product driven mindset with respect to delivering a really like enjoyable experience for members of the community."
The Future of L1s, L2s, and Fundraising
- L1s vs. L2s: Significant room exists for new Layer 1s that offer meaningful technological improvements, particularly in execution performance and consensus mechanisms. The industry is far from the "efficient frontier."
- The proliferation of Layer 2s, especially with tools like Conduit or Caldera, aligns with Ethereum's scaling roadmap. L2s are designed to be purpose-built and easily deployable, often with smaller economic footprints, relying on robust bridges to L1s for security.
- Fundraising Advice:
- First Raise: Founders must develop a highly detailed strategy document for building the business, then distill it into a concise pitch. The strength of the pitch reflects the depth of the underlying plan.
- Subsequent Raises: Focus on building mindshare and demonstrating traction. This can include product usage, but also a strong brand and significant community engagement. Monad's brand combines its technology with its community strength.
- Keone states, "I think there's always going to be room for new L1s that meaningfully improve the overall technology surface area that we have."
Investor & Researcher Alpha
- Execution Efficiency is the New Frontier: While L2s and data availability have dominated scaling narratives, Monad's approach highlights a critical, often overlooked bottleneck: core EVM execution performance. Investors should scrutinize L1s and L2s for fundamental architectural innovations that address this.
- Community as a Pre-Product Moat: Monad's success demonstrates that a product-driven approach to community building can create significant brand equity and mindshare before a mainnet launch. This shifts the focus from purely technical milestones to integrated community and product development.
- HFT Principles for DeFi: The application of high-frequency trading principles (microsecond latency, massive scale, first-principles system design) to blockchain architecture signals a maturation of the industry, demanding institutional-grade performance for broader financial adoption.
Strategic Conclusion
Monad's blend of EVM compatibility and Solana-level performance, driven by HFT-inspired engineering, directly addresses DeFi's execution and cost limitations. The industry's next step involves fundamentally re-architecting core blockchain components to unlock truly scalable, low-latency decentralized finance.
