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    <title>Christopher Cook | Insights</title>
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    <description>Writing on production AI, AI leadership, and secure language-model deployment.</description>
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      <title>Inside CogniCore: Memory Ranking, Skill-Gated Trust, and Overnight Distillation</title>
      <link>https://christopherclaudecook.com/insights/inside-cognicore-memory-trust-distillation</link>
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      <pubDate>Thu, 08 Oct 2026 12:00:00 GMT</pubDate>
      <description>The mechanics under a local AI companion: how three incompatible signals become one memory ranking, how a 27-billion-parameter model teaches a 0.6-billion-parameter one each night, and the skill score that decides how much the small model is allowed to steer.</description>
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      <title>Finding People in a House With Routers, $5 Radios, and an $8 Radar</title>
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      <pubDate>Mon, 05 Oct 2026 12:00:00 GMT</pubDate>
      <description>Two home projects that tried to locate people from radio signals: router signal strength first, then a mesh of ESP32 boards using radio tomography, then a small mmWave radar in each room. How each sensor works, what the simulations say, and what none of them can do.</description>
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      <title>SkyReady 107: A Study App for the Drone Pilot Exam, and the Physics It Teaches</title>
      <link>https://christopherclaudecook.com/insights/skyready-107-part-107-study-app</link>
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      <pubDate>Sat, 03 Oct 2026 12:00:00 GMT</pubDate>
      <description>An offline study app for the FAA Part 107 Remote Pilot knowledge test, with a cited source on every answer and a mock exam that mirrors the real one. Plus an interactive look at load factor, the piece of flight physics the exam cares most about.</description>
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      <title>A Local AI That Keeps Its Own Memory, and a Voice to Talk to It</title>
      <link>https://christopherclaudecook.com/insights/local-ai-with-its-own-memory</link>
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      <pubDate>Thu, 01 Oct 2026 12:00:00 GMT</pubDate>
      <description>CogniCore runs on one 24 GB graphics card, keeps a long-term memory, and retrains a small model every night. The rule that decides when those predictions are trusted, and the voice pipeline that lets you interrupt it mid-sentence.</description>
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      <title>Ethos: Connecting a Self-Hosted Knowledge Base to ChatGPT and Claude Over MCP</title>
      <link>https://christopherclaudecook.com/insights/ethos-knowledge-base-mcp</link>
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      <pubDate>Thu, 27 Aug 2026 12:00:00 GMT</pubDate>
      <description>A language model starts every session with an empty context window, and vendor memory features solve that inside one product while fragmenting it across the rest. How a self-hosted vault attached to both ChatGPT and Claude handles retrieval, artifacts, and a semantic memory the user can watch grow.</description>
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      <title>From a Team of One to a Defense AI Program: Building ORBIS's AI Department</title>
      <link>https://christopherclaudecook.com/insights/scaling-ai-team-1-to-10</link>
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      <pubDate>Sun, 23 Aug 2026 12:00:00 GMT</pubDate>
      <description>I founded ORBIS's AI department as its only engineer. Five years later it was a core team of ten inside programs of 30+ people spanning company departments, contract experts, the U.S. Navy, shipyards, a university, and industry partners. The hurdles, the results, and the servant-leadership model that held it together.</description>
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      <title>Writing a Lidar Driver From the Serial Protocol Up</title>
      <link>https://christopherclaudecook.com/insights/lidar-driver-from-the-serial-protocol-up</link>
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      <pubDate>Mon, 10 Aug 2026 12:00:00 GMT</pubDate>
      <description>A pure Node.js driver for the RPLIDAR A1M8 with no vendor SDK: decoding standard, express, and delta-compressed boost scans, testing against a byte-level mock device, and a simple scan-matching mapper. Includes an interactive version of the mock room.</description>
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      <title>What Shipping AI Into Submarine Construction Taught Me About Production ML</title>
      <link>https://christopherclaudecook.com/insights/production-ml-lessons-from-defense</link>
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      <pubDate>Sat, 01 Aug 2026 12:00:00 GMT</pubDate>
      <description>Most ML projects fail in the distance between a validated notebook and a system running inside someone else's workflow. What years of building AI for Department of Defense inspection pipelines taught me about that distance.</description>
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      <title>Agent Towns: Early Notes on Language-Model Agents Sharing a World</title>
      <link>https://christopherclaudecook.com/insights/agent-towns-workhorse-and-busyworld</link>
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      <pubDate>Thu, 18 Jun 2026 12:00:00 GMT</pubDate>
      <description>Early design notes from an experiment still in progress: several AI agents in one shared simulated world, connected like multiplayer clients, with the world server holding the only copy of positions and time.</description>
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      <title>Running LLMs Where the Data Can't Leave the Building</title>
      <link>https://christopherclaudecook.com/insights/local-llms-secure-environments</link>
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      <pubDate>Wed, 20 May 2026 12:00:00 GMT</pubDate>
      <description>For defense, healthcare, legal, and finance workloads, sending data to a commercial API is often prohibited outright. What actually works when the models have to run inside the boundary.</description>
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