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Article: Virtual Panel: How to Become a Principal Engineer

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As a software engineer or individual contributor, the next step in your career can be to become a principal engineer. The path to becoming a principal engineer at companies can feel unclear, which can inhibit individual engineering careers. By Ben Linders, Joy Ebertz, Pablo Fredrikson, Charlotte de Jong Schouwenburg

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Article: Tips on How Staff Engineers Can Impact Incidents

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Staff engineers can influence behaviors during and after incidents by modeling transparency and questioning assumptions to strengthen engineering culture. In retrospectives, staff engineers can improved model root cause analysis to improve underlying cultural issues. By Erin Doyle

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Article: The Top Three Priorities for Engineering Leaders in 2022 and Beyond

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For engineering leaders, the Great Resignation has made it clear that maintaining employee satisfaction should be a top priority in the coming year. By Lilac Mohr.

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Article: Moving towards a Future of Testing in the Metaverse

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In this article, Tariq King describes the metaverse concept, discusses its key engineering challenges and quality concerns, and then walks through recent technological advances in AI and software testing that are helping to mitigate these challenges.

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Article: Scaling and Growing Developer Experience at Netflix

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This article discusses why and when changes to developer needs will occur, how to get ahead of them, and how to adapt when these changes are necessary. An optimal Developer Experience will depend a lot on the company the developer is working for.

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Article: Using Machine Learning for Fast Test Feedback to Developers and Test Suite Optimization

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The article explores optimizing test execution, saving machine resources, and reducing feedback time to developers. Test suites may be computationally expensive, compete with each other for available hardware, or simply be so large as to cause considerable delay until their results are available. By Gregor Endler, Marco Achtziger.

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Article: Agile Development Applied to Machine Learning Projects

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Machine learning is a powerful new tool, but how does it fit in your agile development? Developing ML with agile has a few challenges that new teams coming up in the space need to be prepared for - from new roles like Data Scientists to concerns in reproducibility and dependency management. By Jay Palat.