Just thought of an interesting topic. @OrderlyNetwork and @skate_chain are two projects that actually share the exact same narrative. They’ve chosen different technical approaches and market strategies. It’s a rare opportunity for a comparative experiment. Let me summarize and compare them: 1. **Narrative:** “Cross-chain + Modular Infrastructure” track players: Both use OP Stack as the foundation, hiding complex cross-chain or trading logic in the backend via SDK to build infrastructure for full-chain swaps. They’re taking the “surround the cities from the countryside” approach to challenge top-tier swaps. 2. **Completely different technical approaches:** **Cross-chain:** - Orderly: Omnichain (off-chain matching, on-chain settlement) - Skate: Chain abstraction **Core modules:** - Orderly: Thin clob (central limit order book) - Skate: AMM (automated market maker) as the core product **Liquidity mechanism:** - Orderly: Perpetuals + aggregated order book + omni liquidity - Skate: Shared spot liquidity pool **Developer-friendly:** - Skate: SDK integration in minutes, stateless app deployment, supports cross-chain VM app creation - Orderly: White-label SDK (build a DEX in 1-2 weeks), no-code Orderly One; API supports bots/arbitrage 3. **Market performance:** **TVL (Total Value Locked):** - Skate: $730K - Orderly: $39M **Twitter followers:** - Skate: 680K - Orderly: 390K 4. **Advantages and disadvantages:** **Skate:** - True cross-VM interoperability, reducing bridging; instant liquidity for emerging chains. - Relies on hub chain synchronization, which may cause finality delays; AMM slippage still exists for large orders. **Orderly:** - CEX-like experience + DeFi security; leading depth in derivatives. - Order book requires high liquidity maintenance; AMM is only auxiliary, not core. This comparison could go on forever. It’s impossible to say one is better than the other—they’re complementary technical approaches that achieve the same business scenario. If I’d known there was so much to cover, I would’ve just written an article. That’s it for the comparison. @KaitoAI @xeetdotai @River4fun