Maintainable Podcast Por Robby Russell arte de portada

Maintainable

Maintainable

De: Robby Russell
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Do you feel like you're hitting a wall with your existing software projects? Are you curious to hear how other people are navigating this? You're not alone. On the Maintainable Software Podcast, Robby speaks with seasoned practitioners who have overcome the technical and cultural problems often associated with software development. Our guests will share stories in each episode and outline tangible, real-world approaches to software challenges. In turn, you'll uncover new ways of thinking about how to improve your software project's maintainability.© 2019-2024 Maintainable Software Podcast Economía Exito Profesional
Episodios
  • Joel Oliveira: Predictability Is a Maintainability Feature

    Joel Oliveira: Predictability Is a Maintainability Feature
    Mar 17 2026
    Long-lived software systems rarely stay tidy. Over time they accumulate decisions, workarounds, and layers of history that can make even simple changes feel risky. For engineers responsible for maintaining those systems, the challenge often becomes less about writing new code and more about understanding what already exists. In this episode of Maintainable, Robby Russell speaks with Joel Oliveira, Engineering Manager at ezCater, about what helps software remain understandable and adaptable as it evolves. Joel starts with a principle that often gets overlooked: predictability. When patterns are consistent and code is organized in familiar ways, engineers can navigate a codebase with confidence. Frameworks like Ruby on Rails reinforce this by encouraging shared conventions, making it easier for developers to orient themselves when working in a new application. The conversation also explores how common metrics can be misleading. Test coverage is often treated as a proxy for quality, but Joel explains that it can create a false sense of confidence. Instead, he values testing most as a thinking tool. Practices like test-driven development can help engineers clarify interfaces and better understand the problem before committing to an implementation. Joel also shares a story from ezCater about replacing an aging image-cropping service that had become difficult to maintain and required frequent restarts due to a memory leak. Rather than patch the system again, the team introduced ImageProxy, an open source image processing tool created by Evil Martians. Because the image URLs flowed through a single object in their GraphQL layer, the team could introduce an adapter and gradually route traffic to the new service using feature flags. This allowed them to migrate safely and incrementally instead of relying on a risky “big bang” change. Robby and Joel also discuss how engineers’ perspectives shift over time. Early in a career it is easy to look at legacy code and label it as bad. Joel now sees older systems as layers of decisions shaped by real constraints. Approaching them with empathy makes it easier to improve them thoughtfully. The episode closes with advice for engineers maintaining complex systems: frame problems as opportunities. By documenting impact and proposing incremental improvements, teams can steadily move their software toward a healthier future. Maintainable software rarely comes from one heroic refactor. More often, it’s the result of many small improvements made by teams who understand their systems and care about how they evolve. Episode Highlights 00:02:18 – Predictability as a Maintainability Feature Joel explains why predictable patterns and conventions make large codebases easier to navigate. 00:07:41 – When Test Coverage Misleads Why high coverage can give a false sense of quality. 00:12:05 – Consulting vs. Product Engineering How switching environments shaped Joel’s approach to code. 00:16:32 – Replacing a Legacy Image Service ezCater’s migration away from a failing Node-based image service. 00:21:14 – Migrating with Adapters and Feature Flags How the team gradually moved traffic to ImageProxy. 00:26:03 – Developing Empathy for Legacy Code Why older systems deserve understanding, not blame. 00:30:47 – The Shift to Engineering Management Joel reflects on moving from IC work to leading teams. 00:34:52 – Advice for Improving Complex Systems Small, consistent improvements matter more than big rewrites. 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 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! Use the code maintainable to get a 10% discount for your first year. Check them out! Links / References Joel Oliveira — LinkedInJoel Oliveira — WebsiteJoel Oliveira — Mastodon (@jayroh)ezCaterImageProxy Subscribe to Maintainable on:Apple PodcastsSpotifyOr search "Maintainable" wherever you stream your podcasts.Keep up to date with the Maintainable Podcast by joining the newsletter.
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    1 h y 1 m
  • Lucas Roesler: The Fast Feedback Loop Advantage

    Lucas Roesler: The Fast Feedback Loop Advantage
    Feb 3 2026
    Maintaining software over time rarely fails because of one bad decision. It fails because teams stop getting clear signals… and start guessing.In this episode, Robby talks with Lucas Roesler, Managing Partner and CTO at Contiamo. Lucas joins from Berlin to unpack what maintainability looks like in practice when you are dealing with real constraints… limited context, missing documentation, and systems that resist understanding.A big through-line is feedback. Lucas argues that long-lived systems become easier to change when they provide fast, trustworthy signals about what they are doing. That can look like tests that validate assumptions, tooling that makes runtime behavior visible, and a habit of designing for observability instead of treating it as a bolt-on.The conversation also gets concrete. Lucas shares a modernization effort built on a decade-old tangle of database logic… views, triggers, stored procedures, and materializations… created by a single engineer who was no longer around. With little documentation to lean on, the team had to build their own approach to “reading” the system and mapping dependencies before they could safely change anything.If you maintain software that has outlived its original authors, this is a grounded look at what helps teams move from uncertainty to confidence… without heroics, and without rewriting for sport.Episode Highlights[00:00:46] What well-maintained software has in common: Robby asks Lucas what traits show up in systems that hold together over time.[00:03:25] Readability at runtime: Lucas connects maintainability to observability and understanding what a system actually did.[00:16:08] Writing the system down as code: Infrastructure, CI/CD, and processes as code to reduce guesswork and improve reproducibility.[00:17:42] How client engagements work in practice: How Lucas’ team collaborates with internal engineering teams and hands work off.[00:25:21] The “rat’s nest” modernization story: Untangling a legacy data system with years of database logic and missing context.[00:29:40] Making data work testable: Why testability matters even when the “code” is SQL and pipelines.[00:34:59] Pivot back to feedback loops: Robby steers into why logs, metrics, and tracing shape better decision-making.[00:35:20] Why teams avoid metrics and tracing: The organizational friction of adding “one more component.”[00:42:59] Local observability with Grafana: Using visual feedback to spot waterfalls, sequential work, and hidden coupling.[00:50:00] Non-technical book recommendations: What Lucas reads and recommends outside of software.Links & ReferencesGuest and CompanyLucas Roesler: https://lucasroesler.com/Contiamo: https://contiamo.com/SocialMastodon: https://floss.social/@theaxerBluesky: https://bsky.app/profile/theaxer.bsky.socialBooks MentionedThe Wheel of Time (Robert Jordan): https://en.wikipedia.org/wiki/The_Wheel_of_TimeAccelerando (Charles Stross): https://en.wikipedia.org/wiki/AccelerandoCharles Stross: https://en.wikipedia.org/wiki/Charles_StrossThanks 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 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! Use the code maintainable to get a 10% discount for your first year. Check them out! Subscribe to Maintainable on:Apple PodcastsSpotifyOr search "Maintainable" wherever you stream your podcasts.Keep up to date with the Maintainable Podcast by joining the newsletter.
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    54 m
  • Brittany Ellich: Using AI to Maintain Software, Not Rewrite It

    Brittany Ellich: Using AI to Maintain Software, Not Rewrite It
    Jan 21 2026
    Rewrites are seductive. Clean slates promise clarity, speed, and “doing it right this time.” In practice, they’re often late, over budget, and quietly demoralizing.In this episode of Maintainable, Robby sits down with Brittany Ellich, a Senior Software Engineer at GitHub, to talk about a different path. One rooted in stewardship, readability, and resisting the urge to start over.Brittany’s career began with a long string of rebuild projects. Over time, she noticed a pattern. The estimates were wrong. Feature development stalled. Teams burned energy reaching parity with systems they’d already had. That experience pushed her toward a strong belief: if software is in production and serving users, it’s usually worth maintaining.[00:00:57] What well-maintained software actually looks likeFor Brittany, readability is the first signal. If code can’t be understood, it can’t be changed safely. Maintenance begins with making systems approachable for the next person.[00:01:42] Rethinking technical debtShe explains how her understanding of technical debt has evolved. Rather than a fixed category of work, it’s often anything that doesn’t map directly to new features. Bugs, reliability issues, and long-term risks frequently get lumped together, making prioritization harder than it needs to be.[00:05:49] Why AI changes the maintenance equationBrittany describes how coding agents have made it easier to tackle small, previously ignored maintenance tasks. Instead of waiting for debt to accumulate into massive projects, teams can chip away incrementally. (Related: GitHub Copilot and the Copilot coding agent workflow she’s explored.)[00:07:16] Context from GitHub’s billing systemsWorking on metered billing at GitHub means correctness and reliability matter more than flash. Billing should be boring. When it’s not, customers notice quickly.[00:11:43] Navigating a multi-era codebaseGitHub’s original Rails codebase is still in active use. Brittany relies heavily on Git blame and old pull requests to understand why decisions were made, treating them as a form of living documentation.[00:25:27] Treating coding agents like teammatesRather than delegating massive changes, Brittany assigns agents small, well-scoped tasks. She approaches them the same way she would a new engineer: clear instructions, limited scope, and careful review.[00:36:00] Structuring the day to avoid cognitive overloadShe breaks agent interaction into focused windows, checking in a few times a day instead of constantly monitoring progress. This keeps deep work intact while still moving maintenance forward.[00:40:24] Low-risk ways to experimentImproving test coverage and generating repository instructions are safe entry points. These changes add value without risking production behavior.[00:54:10] Navigating team resistance and ethicsBrittany acknowledges skepticism around AI and encourages teams to start with existing backlog problems rather than selling AI as a feature factory.[00:57:57] Books, habits, and staying balancedOutside of software, Brittany recommends Atomic Habits by James Clear, sharing how small routines help her stay focused.The takeaway is clear. AI doesn’t replace engineering judgment. Used thoughtfully, it can support the unglamorous work that keeps software alive.Good software doesn’t need a rewrite.It needs caretakers.References MentionedGitHub – Brittany’s current role and the primary environment discussedGitHub Universe – Where Brittany presented her coding agent workflowAtomic Habits by James Clear – Brittany’s recommended book outside of techOvercommitted - Podcast Brittany co-hostsThe Balanced Engineer Newsletter – Brittany’s monthly newsletter on engineering, leadership, and balanceBrittany Ellich’s website – Central hub for her writing and linksGitHub Copilot – The AI tooling discussed throughout the episodeHow the GitHub billing team uses the coding agent in GitHub Copilot to continuously burn down technical debt – GitHub blog post referencedThanks 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 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! Use the code maintainable to get a 10% discount for your first year. Check them out! Subscribe to Maintainable on:Apple PodcastsSpotifyOr search "Maintainable" wherever you stream your podcasts.Keep up to date with the Maintainable Podcast by joining the newsletter.
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    1 h y 1 m
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