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    <title>AI :: FAU Cybersecurity Club</title>
    <link>https://fau-cyber-wiki-test.necoconeco.net/learn/ai/index.html</link>
    <description>What language models and agents actually are, how agent systems are built, and why they are both a tool and a target.</description>
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      <title>Fundamentals for the AI Era</title>
      <link>https://fau-cyber-wiki-test.necoconeco.net/learn/ai/fundamentals/index.html</link>
      <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
      <guid>https://fau-cyber-wiki-test.necoconeco.net/learn/ai/fundamentals/index.html</guid>
      <description>What to actually learn now that models write code: the framings worth knowing, the case for small local models, and why the rest of the roadmap matters more.</description>
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      <title>Agentic Graphs</title>
      <link>https://fau-cyber-wiki-test.necoconeco.net/learn/ai/agentic-graphs/index.html</link>
      <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
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      <description>Nodes, edges, state and cycles: the vocabulary for describing systems built from many model calls, the named patterns, and the failure modes.</description>
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      <title>Harnesses &amp; the Agent Loop</title>
      <link>https://fau-cyber-wiki-test.necoconeco.net/learn/ai/harnesses-and-loops/index.html</link>
      <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
      <guid>https://fau-cyber-wiki-test.necoconeco.net/learn/ai/harnesses-and-loops/index.html</guid>
      <description>What actually turns a language model into an agent: the loop, the harness around it, and the tools people really use.</description>
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    <item>
      <title>Knowledge Bases as Agent Context</title>
      <link>https://fau-cyber-wiki-test.necoconeco.net/learn/ai/knowledge-bases/index.html</link>
      <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
      <guid>https://fau-cyber-wiki-test.necoconeco.net/learn/ai/knowledge-bases/index.html</guid>
      <description>Knowledge graphs against vector retrieval in plain terms, and what document structure actually helps an agent — with this wiki as the worked example.</description>
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    <item>
      <title>AI on Both Sides</title>
      <link>https://fau-cyber-wiki-test.necoconeco.net/learn/ai/blue-and-red/index.html</link>
      <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
      <guid>https://fau-cyber-wiki-test.necoconeco.net/learn/ai/blue-and-red/index.html</guid>
      <description>Defensive and offensive application of AI, and the part a cyber club uniquely needs: how agent systems themselves get attacked and defended.</description>
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      <title>Choosing an AI Model</title>
      <link>https://fau-cyber-wiki-test.necoconeco.net/learn/ai/choosing-a-model/index.html</link>
      <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
      <guid>https://fau-cyber-wiki-test.necoconeco.net/learn/ai/choosing-a-model/index.html</guid>
      <description>Selection criteria for picking an AI model for security work — not a product comparison.</description>
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    <item>
      <title>AI Workflows &amp; Agents</title>
      <link>https://fau-cyber-wiki-test.necoconeco.net/learn/ai/workflows/index.html</link>
      <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
      <guid>https://fau-cyber-wiki-test.necoconeco.net/learn/ai/workflows/index.html</guid>
      <description>The agent loop, common agent patterns, and vendor-neutral workflows for using AI in security work.</description>
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    <item>
      <title>Automating Security Work</title>
      <link>https://fau-cyber-wiki-test.necoconeco.net/learn/ai/automation/index.html</link>
      <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
      <guid>https://fau-cyber-wiki-test.necoconeco.net/learn/ai/automation/index.html</guid>
      <description>How to wire a model into a repeatable pipeline for triage, summarizing, and first-pass review — and what never goes in the prompt.</description>
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