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      <title>Presentation: The Five Stages of AI Maturity in Engineering Organizations - Where and Why Teams Get Stuck</title>
      <link>https://www.infoq.com/presentations/ai-sdlc-maturity-framework-bottlenecks/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Software+Engineering</link>
      <description>&lt;img src="https://res.infoq.com/presentations/ai-sdlc-maturity-framework-bottlenecks/en/mediumimage/LizzieMatusov-medium-1785314207748.jpeg"/&gt;&lt;p&gt;Quotient CEO Lizzie Matusov explains why soaring AI spend often fails to improve software delivery. She presents a research-backed AI maturity framework designed to help engineering leaders move beyond vanity metrics like token usage, align organizational AI adoption, and address critical bottlenecks across the software development life cycle to deliver measurable business outcomes.&lt;/p&gt; &lt;i&gt;By Lizzie Matusov&lt;/i&gt;</description>
      <category>Software Development Lifecycle</category>
      <category>QCon AI Boston 2026</category>
      <category>Metrics</category>
      <category>Productivity</category>
      <category>Software Engineering</category>
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      <category>AI, ML &amp; Data Engineering</category>
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      <pubDate>Tue, 04 Aug 2026 16:00:00 GMT</pubDate>
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      <dc:creator>Lizzie Matusov</dc:creator>
      <dc:date>2026-08-04T16:00:00Z</dc:date>
      <dc:identifier>/presentations/ai-sdlc-maturity-framework-bottlenecks/en</dc:identifier>
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      <title>Presentation: The Future of Engineering: Mindsets That Matter When Code Isn’t Enough</title>
      <link>https://www.infoq.com/presentations/ai-future-engineering/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Software+Engineering</link>
      <description>&lt;img src="https://res.infoq.com/presentations/ai-future-engineering/en/mediumimage/ben-greene-mediumm-1784809015374.jpeg"/&gt;&lt;p&gt;Ben Greene discusses how software engineers can adapt and thrive in an era of rapid AI code automation. Drawing on his startup experience, he explains key mindsets like starting simple, maintaining code comprehension, attacking hard problems first, and focusing on customer impact. He shares why human empathy, agency, and practical problem-solving remain irreplaceable when code is automated.&lt;/p&gt; &lt;i&gt;By Ben Greene&lt;/i&gt;</description>
      <category>QCon San Francisco 2025</category>
      <category>Artificial Intelligence</category>
      <category>Software Engineering</category>
      <category>Transcripts</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
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      <pubDate>Tue, 28 Jul 2026 11:10:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/ai-future-engineering/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Software+Engineering</guid>
      <dc:creator>Ben Greene</dc:creator>
      <dc:date>2026-07-28T11:10:00Z</dc:date>
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