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Enterprise AI strategy is shifting as companies prioritize cost control and operational autonomy by increasingly adopting open-source models over proprietary frontier alternatives. While frontier models remain powerful, open-source solutions now handle over 90% of enterprise use cases, offering a path to avoid vendor lock-in and excessive token costs. Building a sustainable AI business requires moving beyond simple automation toward integrating AI into core workflows, despite the inherent challenges of measuring engineering productivity and the high cost of inferencing. As AI agents begin to perform complex tasks, the future of work will likely favor composite roles that blend engineering, design, and product management. Maintaining a competitive edge in this landscape demands a balance between aggressive market expansion and the disciplined, value-focused execution necessary to build long-term, defensible enterprise software.