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    <title>Jason Belnick — Writing</title>
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    <description>Practical notes on AI adoption and local models.</description>
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    <lastBuildDate>Wed, 01 Jul 2026 00:00:00 +0000</lastBuildDate>
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      <title>The missing 90 percent of AI adoption</title>
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      <pubDate>Wed, 01 Jul 2026 00:00:00 +0000</pubDate>
      <description>73% of surveyed enterprises use AI but only 10% run on it. The gap is not model quality. It is ownership, sign-off paths, and measured workflows</description>
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      <title>The open-weight frontier arrived in June</title>
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      <pubDate>Wed, 01 Jul 2026 00:00:00 +0000</pubDate>
      <description>In one June window, open weights reached the coding frontier. What I&#x27;d build on, what I&#x27;d admire from a distance, and which numbers to trust</description>
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      <title>Local LLMs on a 64GB Mac Studio</title>
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      <pubDate>Wed, 01 Jul 2026 00:00:00 +0000</pubDate>
      <description>The awkward middle tier of local AI in mid-2026, the capacity and bandwidth math that governs it, and the honest 75 percent verdict</description>
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      <title>The week the cloud blinked</title>
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      <pubDate>Wed, 01 Jul 2026 00:00:00 +0000</pubDate>
      <description>Fable 5 vanished for 18 days under an export-control order. Frontier model access is now a dependency risk you have to engineer against</description>
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      <title>Routing work between local and cloud</title>
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      <pubDate>Wed, 01 Jul 2026 00:00:00 +0000</pubDate>
      <description>Model rankings churn monthly; a routing policy survives. Classify work by risk, privacy, latency, and volume, and keep the decision log.</description>
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      <title>Self-refinement that knows when to stop</title>
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      <pubDate>Wed, 01 Jul 2026 00:00:00 +0000</pubDate>
      <description>Nous Research&#x27;s Autoreason finds naive self-refinement makes output worse, and fixes it with a blind tournament where doing nothing can win</description>
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