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      <image:title>Enterprise procurement has found its questions. Most AI vendors are still rehearsing their answers.</image:title>
      <image:caption>The enterprise AI buying cycle changed materially in the first quarter of 2026 — longer timelines, real technical due diligence, and procurement questionnaires most vendors cannot honestly complete. The shift is being driven by boards who authorised AI programmes in 2023 and 2024 and have since seen what they produced. Here is what the smart buyers are now testing for, and why the firms that have only ever sold demos will not pass.</image:caption>
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      <image:title>What breaks in agentic systems at month seven, and the three structural gates we now require before any deployment.</image:title>
      <image:caption>Agentic AI systems fail in ways that demos do not reveal and evaluations rarely test. After eighteen months of production deployments, three failure modes have become reliably visible — none of them are about model capability, all of them are about architecture. Here is what we have learned to require before we approve a build.</image:caption>
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      <image:title>Why most enterprise AI pilots never reach production — and the four conditions that change that.</image:title>
      <image:caption>Eighteen months of pilot work across three sectors taught us that the gap between a working demo and a deployed system is not a technical gap. It is an organisational one. Here is what we have learned to look for before we agree to build.</image:caption>
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      <image:title>The case for retrieval-first architectures over fine-tuning, in seven failed projects.</image:title>
      <image:caption>Fine-tuning a frontier model looks like the obvious move when the demo data is yours. It almost never is. A note from the engineering bench on why we keep reaching for retrieval, what fine-tuning is actually good for, and the projects that taught us the difference.</image:caption>
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      <image:title>Boards have stopped asking what AI is. They are starting to ask better questions.</image:title>
      <image:caption>A shift in the conversations we have been having in board rooms this year. The interesting boards are no longer asking what artificial intelligence can do. They are asking what it should be allowed to do, and on whose authority.</image:caption>
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