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Warren is joined by Olga Kundzich, Co-founder and CTO of Moderne, to discuss the reality of technical debt in modern software engineering. Olga reveals a shocking statistic: without maintenance, cloud-native applications often cease to function within just six months. And from our experience, that's actually optimistic. The rapid decay isn't always due to bad code choices, but rather the shifting sands of third-party dependencies, which make up 80 to 90% of cloud-native environments.
We review the limitations of traditional Abstract Syntax Trees (ASTs) and the introduction of OpenRewrite's Lossless Semantic Trees (LSTs). Unlike standard tools, LSTs preserve formatting and style, allowing for automated, horizontal scaling of code maintenance across millions of lines of code. This fits perfectly in to the toolchain that is the LLMs and open source ecosystem. Olga explains how this technology enables enterprises to migrate frameworks—like moving from Spring Boot 1 to 2 — without dedicating entire years to manual updates.
Finally, they explore the intersection of AI and code maintenance, noting that while LLMs are great at generating code, they often struggle with refactoring and optimizing existing codebases. We highlight that agents are not yet fully autonomous and will always require "right-sized" data to function effectively. Will is absent for this episode, leaving Warren to navigate the complexities of mass-scale code remediation solo.
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In a special solo flight, Warren welcomes Meagan Cojocar, General Manager at Pulumi and a self-proclaimed graduate of “PM school” at AWS. They dive into what it's like to own an entire product line and why giving up that startup hustle for the big leagues sometimes means you miss the direct signal from your users. The conversation goes deep on the paradox of open-source where direct feedback is gold, but dealing with license-shifting competitors can make you wary. From the notorious HashiCorp kerfuffle to the rise of OpenTofu, they explore how Pulumi maintains its commitment to the community amidst a wave of customer distrust.
Meagan highlights the invaluable feedback loop provided by the community, allowing for direct interaction between users and the engineering team. This contrasts with the "telephone game" that can happen in proprietary product development. The conversation also addresses the recent industry shift and then immediate back-peddling from open-source licenses, discussing the subsequent customer distrust and how Pulumi maintains its commitment to the open-source model.
And finally, the duo tackles the elephant in the cloud: LLMs, and extends on the earlier MCP episode. They debate the great code quality vs. speed trade-off, the risk of a "botched" infrastructure deployment, and whether these models can solve anything more than a glorified statistical guessing game. It's a candid look at the future of DevOps, where the real chaos isn't the code, but the tools that write it. The conversation concludes with a philosophical debate on the fundamental capabilities of LLMs, questioning whether they can truly solve "hard problems" or are merely powerful statistical next-word predictors.
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