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A Pragmatic Engineer podcast interview with Titus Winters examines his work on Google’s engineering practices and his involvement in updating undergraduate computer science curriculum guidelines. Winters discusses a large C++ refactor, mandatory testing, code review and how AI complicates measures of developer productivity. The supplied report does not identify a publication date or provide the full interview transcript.
The Pragmatic Engineer has published an interview with Titus Winters, a former Google engineer and lead author of Software Engineering at Google, about large-scale code changes, testing, AI and computer science education. The discussion matters to software developers and educators because Winters draws on Google’s engineering practices while questioning whether current university curricula prepare students for the work now expected of engineers.
Winters spent more than a decade at Google, where he led the company’s readability program and helped build Abseil, an open-source collection of foundational C++ libraries. The report says he is now a Senior Principal Scientist at Adobe, focusing on developer experience and productivity. It presents the interview as a discussion of his experience rather than a newly announced Google policy or a formal curriculum decision.
Among the examples is a refactoring effort begun after Winters joined Google in 2010. The report says Google then had close to 250 million lines of code, maintained by about 10,000 engineers. A team of roughly a dozen used automated parsing and code generation to replace old C++ patterns across the codebase. The process included making old and new APIs coexist, distributing edits in batches and preventing the old pattern from being reintroduced.
The interview also looks at Google’s adoption of mandatory tests and a formal review system. According to the report, Google required changes to be accompanied by tests after Search struggled to maintain a monthly release cadence. The company’s review process paired project owners with language-specific readability reviewers; when Winters left, the report says more than 10,000 engineers were enrolled in the program. Winters also discusses his work on updating ACM/IEEE undergraduate computer science curriculum guidelines, although the supplied report does not spell out the proposed changes.
Engineering Practices Meet CS Education
The interview connects day-to-day engineering safeguards with the education of future developers. Testing, code review and maintainable code can make large systems safer to change, while curriculum decisions influence what new graduates have practiced before entering software jobs. Winters’ experience at Google gives the conversation a concrete case study, but it does not establish that every company should adopt the same processes.
The AI discussion adds a current workplace concern: producing code faster does not automatically mean delivering more useful software. The report says Winters relayed observations from engineers at other companies who described substantially higher code output alongside an approximately 30% rise in outages and no increase in features shipped. Those figures are reported as observations he discussed, not as a measured industry-wide study. If the pattern holds in particular organizations, it would suggest that productivity assessments should account for reliability and shipped outcomes, not just code volume.
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From Google’s Codebase to Curriculum
The source frames the conversation around a tension: Winters helped shape modern engineering education through a widely used book and curriculum work, yet argues that much of what is taught may need substantial revision. The supplied material does not include his full explanation of which subjects should be removed or what should replace them, so that broad characterization should not be mistaken for a detailed curriculum proposal.
Google’s examples show why the interview focuses on systems as well as individual programming skills. The C++ refactor relied on parsing and controlled, staged changes rather than manually editing hundreds of millions of lines. The readability program, meanwhile, treated review as a way to spread language expertise and mentorship across a large engineering organization. The source says the refactor’s needs also led Winters’ team to create the clang-format toolkit.
“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, describing Google’s large C++ refactor in the report
Curriculum Proposals and AI Data
The supplied report does not state the interview’s publication date, provide the full transcript or list specific revisions to the ACM/IEEE curriculum guidelines. It also does not establish whether any proposed changes have been adopted. Readers should treat the curriculum discussion as Winters’ work and perspective, not as a completed change to degree requirements.
The reported 30% increase in outages lacks a defined sample, measurement period and comparison baseline in the material provided. It is attributed to conversations Winters described, rather than a published dataset. The source also notes that AI may bring benefits traditional productivity measures miss, but the excerpt ends before detailing those benefits. The overall effect of AI on reliability, feature delivery and engineering productivity therefore remains unsettled in this account.
Watch for Curriculum and Reliability Details
The immediate next step for readers is to consult the full episode and transcript, available through the platforms named by The Pragmatic Engineer, for Winters’ fuller account of curriculum changes and AI’s less visible benefits. The supplied material does not announce a specific follow-up release, implementation date or decision by the ACM or IEEE.
For organizations evaluating AI-assisted development, the discussion points to questions they can track: whether reliability changes as code output rises, whether shipped features increase, and what safeguards catch regressions. Those are practical measures to investigate, not findings established by the interview excerpt. Any firm conclusion about the effects of AI or the future curriculum will require clearer data and details about the proposals.
Key Questions
Who is Titus Winters?
Titus Winters spent more than a decade at Google, where he led its readability program and worked on Abseil. The report identifies him as a Senior Principal Scientist at Adobe, focused on developer experience and productivity.
What is the interview about?
The Pragmatic Engineer interview covers Google’s large C++ refactor, testing and code review practices, AI’s effects on engineering work, and Winters’ involvement in updating undergraduate computer science curriculum guidelines.
Did Google refactor 250 million lines of code at once?
The report says Google had close to 250 million lines of code at the time and describes a team-led effort to change old C++ patterns across that codebase. It does not say every line was rewritten; the work targeted specific patterns using parsing and generated edits.
Does the report prove AI has increased software outages?
No. It relays Winters’ account of conversations in which engineers reported outages up about 30%, alongside greater code output and static feature counts. The supplied material gives no sample, time window or comparison baseline, so it is not evidence of an industry-wide measured effect.
What changes to computer science education are proposed?
The source says Winters worked on updating ACM/IEEE undergraduate curriculum guidelines and argues that current education needs change. It does not specify the proposed course changes or confirm that new guidelines have been approved.
Source: newsletter.pragmaticengineer.com
