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Julia Ferraioli - Capturing Untold Open Source Stories

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Manage episode 431404360 series 2503882
Innehåll tillhandahållet av Robby Russell. Allt poddinnehåll inklusive avsnitt, grafik och podcastbeskrivningar laddas upp och tillhandahålls direkt av Robby Russell eller deras podcastplattformspartner. Om du tror att någon använder ditt upphovsrättsskyddade verk utan din tillåtelse kan du följa processen som beskrivs här https://sv.player.fm/legal.

Welcome to the Maintainable Software Podcast! In this episode, Robby speaks with Julia Ferraioli, an Open Source AI/ML Strategist at AWS and co-founder of Open Source Stories. Julia joins us from Seattle, Washington, and shares her insights into the world of open source, AI, and software maintainability.

Key Topics:

Well-Maintained Software: Julia shares her thoughts on the characteristics of well-maintained software, emphasizing the importance of avoiding "clever" code that is often unmaintainable.
Creative vs. Assembly Process: The discussion touches on the balance between software as a creative endeavor and an assembly process, highlighting the need for maintainability.
Ternary Operators and Readability: Julia provides her perspective on the use of ternary operators and how certain programming language features can impact code readability and maintainability.
Open Source Stories: Julia discusses the origins and goals of Open Source Stories, a narrative project that captures the untold stories of open-source contributors.
Challenges in Open Source: The episode delves into the challenges faced by open source contributors, including cultural context, erasure, and the lack of exit interviews.
Research and Software Maintenance: Julia's background in machine learning research offers a unique perspective on the intersection of research and software maintenance.
Technical Debt: A broader definition of technical debt is explored, encompassing work deferred and cultural issues within organizations.
Effective Strategies: Julia shares strategies for addressing technical debt and navigating conversations about prioritizing technical improvements.
Metrics and Developer Experience: The importance of context in metrics and the value of developer experience feedback are discussed.
AI/ML Tools: Julia provides her predictions on the impact of AI/ML tools on software maintenance in the coming years.

Resources Mentioned:

Open Source Stories
Feminism is for Everybody by Bell Hooks

Thanks to Our Sponsor!

Turn hours of debugging into just minutes! AppSignal is a performance monitoring and error tracking tool designed for Ruby, Elixir, Python, Node.js, Javascript, and soon, other frameworks.

It offers six powerful features with one simple interface, providing developers with real-time insights into the performance and health of web applications.

Keep your coding cool and error-free, one line at a time! Check them out!

Subscribe to Maintainable on:

Or search "Maintainable" wherever you stream your podcasts.

Keep up to date with the Maintainable Podcast by joining the newsletter.

  continue reading

188 episoder

Artwork
iconDela
 
Manage episode 431404360 series 2503882
Innehåll tillhandahållet av Robby Russell. Allt poddinnehåll inklusive avsnitt, grafik och podcastbeskrivningar laddas upp och tillhandahålls direkt av Robby Russell eller deras podcastplattformspartner. Om du tror att någon använder ditt upphovsrättsskyddade verk utan din tillåtelse kan du följa processen som beskrivs här https://sv.player.fm/legal.

Welcome to the Maintainable Software Podcast! In this episode, Robby speaks with Julia Ferraioli, an Open Source AI/ML Strategist at AWS and co-founder of Open Source Stories. Julia joins us from Seattle, Washington, and shares her insights into the world of open source, AI, and software maintainability.

Key Topics:

Well-Maintained Software: Julia shares her thoughts on the characteristics of well-maintained software, emphasizing the importance of avoiding "clever" code that is often unmaintainable.
Creative vs. Assembly Process: The discussion touches on the balance between software as a creative endeavor and an assembly process, highlighting the need for maintainability.
Ternary Operators and Readability: Julia provides her perspective on the use of ternary operators and how certain programming language features can impact code readability and maintainability.
Open Source Stories: Julia discusses the origins and goals of Open Source Stories, a narrative project that captures the untold stories of open-source contributors.
Challenges in Open Source: The episode delves into the challenges faced by open source contributors, including cultural context, erasure, and the lack of exit interviews.
Research and Software Maintenance: Julia's background in machine learning research offers a unique perspective on the intersection of research and software maintenance.
Technical Debt: A broader definition of technical debt is explored, encompassing work deferred and cultural issues within organizations.
Effective Strategies: Julia shares strategies for addressing technical debt and navigating conversations about prioritizing technical improvements.
Metrics and Developer Experience: The importance of context in metrics and the value of developer experience feedback are discussed.
AI/ML Tools: Julia provides her predictions on the impact of AI/ML tools on software maintenance in the coming years.

Resources Mentioned:

Open Source Stories
Feminism is for Everybody by Bell Hooks

Thanks to Our Sponsor!

Turn hours of debugging into just minutes! AppSignal is a performance monitoring and error tracking tool designed for Ruby, Elixir, Python, Node.js, Javascript, and soon, other frameworks.

It offers six powerful features with one simple interface, providing developers with real-time insights into the performance and health of web applications.

Keep your coding cool and error-free, one line at a time! Check them out!

Subscribe to Maintainable on:

Or search "Maintainable" wherever you stream your podcasts.

Keep up to date with the Maintainable Podcast by joining the newsletter.

  continue reading

188 episoder

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