@cobradecipher

GM CT In Modular AI Chains, Dev Experience Is the Real Throughput 0G Labs is architecting a future of modular AI infrastructure: Galileo for Data Availability Newton for Storage Socrates for Inference Impressive on paper. But here’s what time in systems design has taught me: Let’s analyze: How many lines of code does it take to deploy an inference module across Socrates? Is there a unified SDK, or are devs left stitching APIs across components? Where are the playgrounds, the sandboxes, the open testbeds? Modular design increases surface area. Which means developer friction multiplies, not just adds. Ethereum succeeded not because of raw TPS—but because you could write 15 lines of Solidity and launch a dApp. If 0G requires devs to think like infra architects just to push a model—it’s not a chain, it’s a research paper. In Web3, throughput is measured not in transactions—but in experiments shipped by real devs, fast.

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