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    <title>Ai on WhiteMatterTech</title>
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    <description>Recent content in Ai on WhiteMatterTech</description>
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      <title>Agentic Static-Site Hosting: Giving Claude a Place to Publish on Kubernetes</title>
      <link>https://whitematter.tech/posts/pages-mcp/</link>
      <pubDate>Sun, 09 Aug 2026 00:00:00 +0000</pubDate>
      <guid>https://whitematter.tech/posts/pages-mcp/</guid>
      <description>&lt;hr&gt;
&lt;h1 id=&#34;introduction&#34;&gt;Introduction&lt;/h1&gt;
&lt;p&gt;I use Claude Code for a lot of one-off analysis, and the output is very often a single self-contained HTML file. As of this writing, some examples are the following: a dashboard of my flight log, an interactive trainer built from an audiobook transcript &lt;em&gt;(I wrote about building those in &lt;a href=&#34;https://whitematter.tech/posts/interactive-audiobook-trainers/&#34;&gt;Building Interactive Trainers From My Audiobook Library&lt;/a&gt;)&lt;/em&gt;, a pedigree chart, and a client map. Every one of those started life as a Live Artifact, or as a file in &lt;code&gt;/tmp&lt;/code&gt; that I opened with &lt;code&gt;file://&lt;/code&gt;, looked at once, and then lost.&lt;/p&gt;</description>
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    <item>
      <title>Building Interactive Trainers From My Audiobook Library</title>
      <link>https://whitematter.tech/posts/interactive-audiobook-trainers/</link>
      <pubDate>Sat, 11 Jul 2026 00:00:00 +0000</pubDate>
      <guid>https://whitematter.tech/posts/interactive-audiobook-trainers/</guid>
      <description>&lt;h1 id=&#34;building-interactive-trainers-from-my-audiobook-library&#34;&gt;Building Interactive Trainers From My Audiobook Library&lt;/h1&gt;
&lt;p&gt;I listen to a lot of business and leadership audiobooks, and I retain almost none of them a month later. Listening is passive, the good frameworks blur together over time, and &amp;ldquo;I read that one&amp;rdquo; soon becomes &amp;ldquo;I think I read that one.&amp;rdquo; I wanted the retention without having to re-listen to seven hours just to find the one idea I actually needed.&lt;/p&gt;</description>
    </item>
    <item>
      <title>The Lever and the Enter Key: A Conceptualization of Agent-Mediated Software Development as a Functional Analog of Brain Stimulation Reward</title>
      <link>https://whitematter.tech/posts/the-lever-and-the-enter-key/</link>
      <pubDate>Tue, 26 May 2026 00:00:00 +0000</pubDate>
      <guid>https://whitematter.tech/posts/the-lever-and-the-enter-key/</guid>
      <description>&lt;p&gt;&lt;em&gt;This essay is also available as a preprint on PsyArXiv. To cite it, use the following reference (APA 6th edition):&lt;/em&gt;&lt;/p&gt;
&lt;blockquote&gt;
&lt;p&gt;White, R. D. (n.d.). The lever and the enter key: A conceptualization of agent-mediated software development as a functional analog of brain stimulation reward. Retrieved from &lt;a href=&#34;https://osf.io/preprints/psyarxiv/zxpwg_v1&#34;&gt;https://osf.io/preprints/psyarxiv/zxpwg_v1&lt;/a&gt;&lt;/p&gt;
&lt;/blockquote&gt;
&lt;h2 id=&#34;abstract&#34;&gt;Abstract&lt;/h2&gt;
&lt;p&gt;Olds and Milner (1954) reported that rats with electrodes implanted in the septal area would learn to lever-press for brief pulses of electrical stimulation delivered to the implant site, establishing what is now called brain stimulation reward (BSR) and its operant counterpart, intracranial self-stimulation (ICSS). Subsequent work demonstrated that rats stimulated in the lateral hypothalamus or medial forebrain bundle would respond at sustained high rates (Olds, 1958a) and would self-stimulate to physical exhaustion without satiation under extended testing (Olds, 1958b), would forgo food to the point of starvation when both food and stimulation were available concurrently (Routtenberg &amp;amp; Lindy, 1965), and would respond for brain stimulation in competition with shock avoidance (Valenstein &amp;amp; Beer, 1962). Researchers have since demonstrated the phenomenon in multiple species, including humans, with published case reports of compulsive self-stimulation that closely mirror the rodent literature (Bishop, Elder, &amp;amp; Heath, 1963; Moan &amp;amp; Heath, 1972; Portenoy et al., 1986). The purpose of this essay is to (a) review BSR and its proposed neural mechanism with appropriate hedging of the contested causal role of dopamine, (b) propose a structural analogy between BSR and the reinforcement profile generated by interaction with large language model (LLM) coding agents (e.g., Claude, Codex), and (c) clarify that the behaviors examined in this essay are conceptually distinct from the cluster of LLM-associated psychotic phenomena recently discussed in the clinical literature on so-called &amp;ldquo;AI psychosis&amp;rdquo; (Flathers et al., 2026; Morrin et al., 2026), which refer to delusion formation rather than compulsive use. I close with a personal observation, as the analogy did not become persuasive to me until I noticed it operating in myself.&lt;/p&gt;</description>
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    <item>
      <title>Politics Dashboard: A Self-Hosted, AI-Summarized News &amp; X Feed Reader</title>
      <link>https://whitematter.tech/posts/politics-dashboard/</link>
      <pubDate>Wed, 06 May 2026 00:00:00 +0000</pubDate>
      <guid>https://whitematter.tech/posts/politics-dashboard/</guid>
      <description>&lt;h1 id=&#34;politics-dashboard-a-self-hosted-ai-summarized-news--x-feed-reader&#34;&gt;Politics Dashboard: A Self-Hosted, AI-Summarized News &amp;amp; X Feed Reader&lt;/h1&gt;
&lt;p&gt;&lt;strong&gt;Bottom line up front.&lt;/strong&gt; I built and now open-sourced a self-hosted news dashboard that aggregates political news from RSS or FreshRSS, summarizes each article with a configurable LLM, generates a 24-hour thematic digest, and sits alongside live X/Twitter posts (with per-account AI summaries) via a self-hosted Nitter. Repository: &lt;a href=&#34;https://github.com/RobertDWhite/politics-dashboard&#34;&gt;github.com/RobertDWhite/politics-dashboard&lt;/a&gt;. License: MIT. Multi-arch images at &lt;code&gt;ghcr.io/robertdwhite/politics-{api,ui}&lt;/code&gt;. The image I run in production is the same image GitHub Actions builds from &lt;code&gt;main&lt;/code&gt;.&lt;/p&gt;</description>
    </item>
    <item>
      <title>Always-On SDR: Building a Multi-Band Radio Intelligence Platform on Kubernetes</title>
      <link>https://whitematter.tech/posts/sdr-research-stack/</link>
      <pubDate>Mon, 20 Apr 2026 00:00:00 +0000</pubDate>
      <guid>https://whitematter.tech/posts/sdr-research-stack/</guid>
      <description>&lt;blockquote&gt;
&lt;p&gt;&lt;em&gt;This post was originally published at &lt;a href=&#34;https://w3rdw.radio/posts/sdr-research-stack/&#34;&gt;w3rdw.radio&lt;/a&gt;, the ham radio blog of Robert White (W3RDW). It is cross-posted here for the WhiteMatter Tech audience.&lt;/em&gt;&lt;/p&gt;
&lt;/blockquote&gt;
&lt;h1 id=&#34;always-on-sdr-building-a-multi-band-radio-intelligence-platform-on-kubernetes&#34;&gt;Always-On SDR: Building a Multi-Band Radio Intelligence Platform on Kubernetes&lt;/h1&gt;
&lt;p&gt;I have been quietly building something i am pretty excited about. The idea started simple enough: i wanted a permanent, always-on radio monitor for 2m. It grew into something considerably larger. Today the stack covers 2m, 70cm, and the full HF spectrum from 3–28 MHz simultaneously: recording, decoding, transcribing, and tagging everything it hears, around the clock, with no manual intervention.&lt;/p&gt;</description>
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