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AI coding assistants are widely criticized as overhyped in 2026, but they're proving useful for unglamorous tasks like generating boilerplate, debugging edge cases, and automating release workflows. The author uses AI to automate their GitHub release pipeline (testing, tagging, deployment), saving significant time while acknowledging limitations like context loss and hallucinations. The key is treating AI as a helpful tool for grunt work rather than a replacement, and balancing it with focused coding sessions.