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    <title>Sovereign-Ai on Jeff Geiser</title>
    <link>https://jeffgeiser.dev/tags/sovereign-ai/</link>
    <description>Recent content in Sovereign-Ai on Jeff Geiser</description>
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    <lastBuildDate>Thu, 15 Oct 2026 00:00:00 +0000</lastBuildDate>
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      <title>account-intelligence-7b-v1: A Small Model That Writes Account Briefs</title>
      <link>https://jeffgeiser.dev/posts/account-intelligence-7b-v1/</link>
      <pubDate>Thu, 15 Oct 2026 00:00:00 +0000</pubDate>
      <guid>https://jeffgeiser.dev/posts/account-intelligence-7b-v1/</guid>
      <description>&lt;p&gt;&lt;strong&gt;I fine-tuned a 7B model to turn raw enterprise account data into structured briefs. It&amp;rsquo;s on Hugging Face now, with the numbers and the gaps.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;By Jeff Geiser — October 2026&lt;/em&gt;&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;The model&amp;rsquo;s up on Hugging Face now: &lt;a href=&#34;https://huggingface.co/jgeiser/account-intelligence-7b-v1&#34;&gt;jgeiser/account-intelligence-7b-v1&lt;/a&gt;.&lt;/p&gt;&#xA;&lt;p&gt;You hand it a bundle of account signals (support tickets, usage metrics, contract terms, stakeholder notes, etc..) and it gives you back a structured JSON brief across six surfaces: meeting prep, QBR pack, handoff, renewal alert, onboarding, and escalation context. Nobody is supposed to read the output like an essay.. it&amp;rsquo;s JSON, and downstream systems consume it directly.&lt;/p&gt;</description>
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      <title>Test the Stack, Not the Diagram</title>
      <link>https://jeffgeiser.dev/posts/test-the-stack-not-the-diagram/</link>
      <pubDate>Mon, 12 Oct 2026 00:00:00 +0000</pubDate>
      <guid>https://jeffgeiser.dev/posts/test-the-stack-not-the-diagram/</guid>
      <description>&lt;p&gt;&lt;strong&gt;Data in an AI stack doesn&amp;rsquo;t live in one place. It sprawls across caches, logs, vector stores, and traces. Residency is a surface, and you can&amp;rsquo;t prove a surface from a diagram.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;By Jeff Geiser — October 2026&lt;/em&gt;&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;If you&amp;rsquo;ve built an AI stack, you already know the uncomfortable version of this: your data does not live in one place.&lt;/p&gt;&#xA;&lt;p&gt;You designed a request path. Prompt comes in, hits the gateway, goes to a model, answer goes back. That path is what&amp;rsquo;s on the architecture diagram, and it&amp;rsquo;s real. It&amp;rsquo;s also a small fraction of where the data actually goes.&lt;/p&gt;</description>
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    <item>
      <title>The Hard Part of Sovereign AI Isn&#39;t the Models</title>
      <link>https://jeffgeiser.dev/posts/the-hard-part-of-sovereign-ai-isnt-the-models/</link>
      <pubDate>Tue, 06 Oct 2026 00:00:00 +0000</pubDate>
      <guid>https://jeffgeiser.dev/posts/the-hard-part-of-sovereign-ai-isnt-the-models/</guid>
      <description>&lt;p&gt;&lt;strong&gt;Everyone&amp;rsquo;s composing small specialized models now, and everyone&amp;rsquo;s moving them onto their own hardware. What happens when these two collide.&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;By Jeff Geiser — October 2026&lt;/em&gt;&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;p&gt;Two shifts are happening.&lt;/p&gt;&#xA;&lt;p&gt;First, we stopped shipping a single model. If you&amp;rsquo;re building anything serious now, you&amp;rsquo;re composing. A small classifier to triage the request, a retrieval step, a generator, a verifier to catch the generator, etc.. Three to five specialized models wired into a pipeline, each doing their job. The research crew named it compound AI. A composed pipeline of small models beats one big model on accuracy and cost.. as long as you keep the coordination overhead in check.&lt;/p&gt;</description>
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