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The Pragmatic Engineer published a podcast conversation with Titus Winters about large-scale software engineering at Google and changes to computer science education. The episode covers Google’s C++ refactoring and testing practices, Winters’ work on curriculum guidelines, and his views on AI’s effects on productivity and reliability.
The Pragmatic Engineer has published a podcast interview with Titus Winters, a former Google engineer and lead author of Software Engineering at Google, discussing the company’s engineering practices and how computer science education should change. The conversation also examines a major refactoring effort across Google’s C++ codebase and the uncertain effects of AI on software productivity and reliability.
Winters spent more than a decade at Google, where he led the company’s readability program and helped build Abseil, a set of open-source foundational C++ libraries. He is now a senior principal scientist at Adobe, focused on developer experience and productivity, according to The Pragmatic Engineer. The podcast’s host presents the interview as a discussion of both engineering practice and Winters’ work updating undergraduate computer science curriculum guidelines with the ACM and IEEE.
One central example is a Google project from 2010, shortly after Winters joined the company. The report says a team of about a dozen engineers worked on changing old C++ patterns across a codebase then estimated at nearly 250 million lines and edited by about 10,000 engineers. The team used language parsing and automated code generation to identify and update patterns, then divided the changes into batches while allowing old and new APIs to coexist. The report says the work also prompted creation of the clang-format toolkit.
The interview recounts other organizational changes. The report says Google required tests to accompany every code change after Search had fallen from a monthly release cadence to quarterly releases around 2007. It also describes a review system involving both a project or file owner and a language-specific readability reviewer. At the time Winters left Google, the report says more than 10,000 engineers were enrolled in the readability program. These figures and recollections are presented in the source’s account of the interview.
Engineering Practices at Google
The discussion links code review, testing and automated refactoring to the challenge of changing large, interconnected systems safely. Google’s reported experience offers a case study in how engineering process can affect release pace: the source says testing requirements were introduced when Search could no longer ship monthly, and that its cadence later improved. It does not provide independent measurements or establish that testing alone caused the change.
For readers following AI-assisted software development, Winters’ comments highlight a tension between producing more code and delivering reliable products. The source reports that he has heard from engineers at other companies that code output has risen while outages have also increased, with feature output static. That is an attributed observation, not a published industry-wide dataset. It matters because code volume by itself may not show whether AI tools are improving outcomes for users or engineering teams.
The education discussion extends the issue to new engineers entering the field. If tools and workplace expectations are changing, curriculum guidance may need to adapt. The source identifies Winters’ involvement in ACM/IEEE undergraduate curriculum work, but does not detail specific proposed changes or present an approved new curriculum.
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From Google’s Codebase to Curriculum
Winters’ experience spans both technical infrastructure and engineering education. At Google, he worked on C++ libraries, code readability and large-scale refactoring; the report frames those efforts as examples of managing code maintained by thousands of engineers. Its description of the 2010 refactor emphasizes that the team relied on parsing, abstract syntax trees and generated edits rather than modern large language models, which were not available for the project.
The podcast also revisits Google’s review and testing practices as organizational responses to the difficulty of making changes safely. Those practices are relevant to the broader education question: the interview connects engineering work to what students should learn, though the source does not provide a full transcript of Winters’ curriculum recommendations. The article’s headline frames an apparent contradiction between helping shape engineering education and criticizing much of the existing curriculum; the supplied material does not include enough of the conversation to specify exactly which parts Winters wants replaced.
“We were replacing the foundation of the Empire State Building. We were not allowed to close the building or block traffic. Oh, and we discovered nuclear waste in the basement.”
— Titus Winters, recalling Google’s large C++ refactoring project
AI Claims and Curriculum Details
The supplied report does not identify a publication date for the episode, provide a full transcript, or specify the exact curriculum recommendations Winters made. Its headline says he argues that almost all of the existing curriculum should be burned down, but the excerpt does not include the discussion needed to assess the scope or wording of that argument.
The reported AI-related figures also lack key details: the source gives an estimate of outages rising by about 30% among companies Winters says he speaks with, but provides no measurement period, sample size, comparison method or underlying dataset. It also says feature output was static without defining the measure. These comments should be treated as Winters’ reported observations, not confirmed sector-wide statistics.
The account of Google’s historical projects is likewise drawn from the interview and the report; the supplied material does not include company records or independent verification. The current status of the ACM/IEEE curriculum update is not stated.
Where the Discussion Leads
The immediate next step for readers is the full podcast episode and transcript, which The Pragmatic Engineer says are available through its YouTube, Apple and Spotify channels. Those materials may clarify Winters’ curriculum proposals and provide fuller context for his comments about AI, outages and software output.
No specific publication date for revised ACM/IEEE curriculum guidelines, implementation plan or follow-up research on the AI observations is included in the supplied report. Until such details are available, the curriculum work and the reported industry trends remain topics raised in the interview rather than confirmed upcoming changes.
Key Questions
What is the news?
The Pragmatic Engineer published a podcast interview with Titus Winters about software engineering at Google, computer science education and AI’s possible effects on engineering work.
What did Winters do at Google?
According to the report, Winters spent more than a decade at Google, led its readability program and helped build Abseil, an open-source set of foundational C++ libraries.
What was the large C++ refactoring project?
The report says that in 2010 a team of about a dozen engineers used parsing and automated code edits to update patterns across a codebase estimated at nearly 250 million lines.
Did the interview prove AI is increasing outages?
No. The report attributes an estimate of roughly 30% more outages to Winters’ conversations with engineers, but gives no sample, time window or measurement method. It is not presented as a verified industry-wide finding.
What changes to computer science education does Winters propose?
The supplied report says Winters worked on ACM/IEEE undergraduate curriculum guidelines and frames him as calling for major changes, but it does not specify the recommendations. The full interview or transcript would be needed for those details.
Source: newsletter.pragmaticengineer.com
