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  1. Why Most AI POCs Stall and How to Build an AI Operating Model That Works

    Companies are generating more AI ideas, hackathons, and proof-of-concepts than ever before. Yet only a small fraction of those initiatives ever become secure, scalable, and widely adopted production solutions. The challenge isn't a lack of innovation or model capability. It's the absence of an AI operating model that connects governance, data readiness, measurement, accountability, and people enablement. In this article, I explore why most AI POCs stall and what organizations can do differently to consistently transform AI experiments into measurable business value.

    bhavingandhi.com/2026/08/26/wh

  2. 3 main reasons why technical programs fail:
    - You build the wrong thing and don't find out until it's too late to do anything about it;
    - #IntegrationHell
    - #TechDebt to the point that it grinds progress to a halt

    #TechnicalProgramManagement