As AI Takes Over Code Writing, Developers Must Reclaim Business Logic Ownership

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AI coding tools such as GitHub Copilot, Cursor, Claude, and ChatGPT have become near-universal in software development, operating across levels from simple autocomplete to fully autonomous agent-based project execution. While AI can generate syntactically correct, convention-compliant unit tests, it lacks awareness of the underlying business rules that give those tests meaning. Complex workflows — such as reserving stock for 15 minutes after an order and notifying a seller if payment lapses — require human understanding to define and validate correctly. Token costs for AI-assisted refactoring can reach $1,000–$1,500 per month for a 50-person team, raising questions about return on investment when business logic coverage is missing. The article argues that developers retain irreplaceable value not in writing code line by line, but in knowing why features exist, setting boundaries, and ensuring AI-generated work aligns with real-world intent.

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