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  <titleInfo>
    <title>AI for everyday IT</title>
    <subTitle>accelerate workplace productivity</subTitle>
  </titleInfo>
  <name type="personal">
    <namePart>LeMaire, Chrissy</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Abshire, Brandon</namePart>
  </name>
  <name type="personal">
    <namePart>Narasimhan, Nitya</namePart>
  </name>
  <typeOfResource>text</typeOfResource>
  <originInfo>
    <place>
      <placeTerm type="text">Shelter Island</placeTerm>
    </place>
    <publisher>Manning Publications</publisher>
    <dateIssued>2025</dateIssued>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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    <extent>xxv, 348 p.</extent>
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  <abstract>"What if you never had to write another after-incident report, piece of boilerplate code, or a performance review from scratch ever again? Use AI tools like ChatGPT, Claude, Gemini, and Copilot right, and you’ll take back hours of your time—and more! AI for Everyday IT reveals how you can automate dozens of your daily IT tasks with generative AI. In this hands-on guide, automation experts Chrissy LeMaire and Brandon Abshire show you how AI tools like ChatGPT have made their lives a million times easier, and how they can do the same for you. You’ll find proven strategies for using AI to improve help desk support, automate sysadmin and database tasks, aid with DevOps engineering, handle managing IT teams, and dozens more time-saving and quality-improving hacks."-- Provided by publisher</abstract>
  <note type="statement of responsibility">Chrissy LeMaire and Brandon Abshire ; foreword by Nitya Narasimhan</note>
  <note>Index present</note>
  <note>Eng</note>
  <subject>
    <topic>AI-data processing</topic>
  </subject>
  <subject>
    <topic>Information technology</topic>
  </subject>
  <classification authority="ddc">006.3 LEM-A</classification>
  <identifier type="isbn">9781633436428</identifier>
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    <recordCreationDate encoding="marc">260727</recordCreationDate>
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