Summarize Most enterprise AI failures stem not from weak models but from poor system design, where breakdowns in data pipelines, orchestration, evaluation, and governance lead to unreliable production outcomes. An overemphasis on model accuracy overlooks the need for robust, end-to-end architecture that ensures consistency, security, and cost efficiency. As modern AI systems, especially agentic workflows, introduce greater autonomy and complexity, the importance of structured system design and...
