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Hexagonal Architecture Slowed AI Coding Agent by 38%, Engineer's Experiment Finds

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A principal engineer tested whether hexagonal architecture would help an AI coding agent work more efficiently, expecting the structured approach to prove its worth. The experiment used a Java billing service called ChargeLedger, built for an EV charging network, with two versions: one following hexagonal architecture principles and one using a flatter, architecture-neutral design. Across nine features, the hexagonal version took 38% longer to reach acceptance compared to the flat implementation. The engineer concluded that architectural indirection added by habit — such as interfaces with single implementations and pass-through methods — carries a real cost for both humans and AI agents. While not abandoning clean code principles, the engineer now argues that every layer of abstraction requires concrete justification rather than being applied as a default practice.

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