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      <title>Article: AI Interventions to Reduce Cycle Time in Legacy Modernization</title>
      <link>https://www.infoq.com/articles/AI-legacy-modernization/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Requirements+Management-articles</link>
      <description>&lt;img src="https://res.infoq.com/articles/AI-legacy-modernization/en/headerimage/AI-legacy-modernization-header-1746528855677.jpg"/&gt;&lt;p&gt;In this article, we share our experiences and insights on how large language models (LLMs) helped us uncover and enhance the conceptual constructs behind software. We discuss how these approaches address the inherent complexity of software engineering and improve the likelihood of success in large, complex software modernization projects.&lt;/p&gt; &lt;i&gt;By Michael Wytock, Ken Judy, Aaron Foster Breilyn&lt;/i&gt;</description>
      <category>Artifacts &amp; Tools</category>
      <category>Requirements</category>
      <category>Legacy Code</category>
      <category>Requirements Management</category>
      <category>Architecture</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>article</category>
      <pubDate>Wed, 21 May 2025 09:00:00 GMT</pubDate>
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      <dc:creator>Michael Wytock, Ken Judy, Aaron Foster Breilyn</dc:creator>
      <dc:date>2025-05-21T09:00:00Z</dc:date>
      <dc:identifier>/articles/AI-legacy-modernization/en</dc:identifier>
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