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    <title>Dissei Data Research</title>
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    <description>Field notes on building verifiable reinforcement-learning environments for institutional finance.</description>
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      <title>The anchor travels: one deal's chatter prices the next deal</title>
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      <pubDate>Thu, 11 Jun 2026 00:00:00 GMT</pubDate>
      <description>Plant one sentence of unverified market chatter in the first deal an AI analyst reads, and its price for an unrelated second deal in the same session moves half a turn of EBITDA. Telling the model to evaluate the second deal independently removes less than a third of the effect. Nothing in the output says it happened.</description>
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      <title>Prompt Risk Is Investment Risk</title>
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      <pubDate>Mon, 08 Jun 2026 00:00:00 GMT</pubDate>
      <description>We quadrupled a company's biggest risk and the AI's price didn't move. We added one line of market chatter and it moved $45 million. What that means for any committee putting AI near a capital decision.</description>
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      <title>You can scaffold away the flip. You can't scaffold away the frame.</title>
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      <pubDate>Sun, 07 Jun 2026 00:00:00 GMT</pubDate>
      <description>564 isolated runs across one synthetic deal and its controlled variants. The recommendation never moved. The price, the leverage, and what the memo noticed moved with the packaging of the question.</description>
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      <title>How a prompt's framing quietly answers its own question</title>
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      <pubDate>Fri, 05 Jun 2026 00:00:00 GMT</pubDate>
      <description>Why the grammar of an eval stem can hand a model the shape of its answer, the five trigger families that do the leaking, and the one-word test that catches all of them.</description>
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