The Pragmatic Engineer

• How AI is changing software engineering at Shopify with Farhan Thawar

  Supported by Our Partners•⁠ WorkOS — The modern identity platform for B2B SaaS.•⁠ Statsig ⁠ — ⁠ The unified platform for flags, analytics, experiments, and more.• Sonar —  Code quality and code security for ALL code. —What happens when a company goes all in on AI?At Shopify, engineers are expected to utilize AI tools, and they’ve been doing so for longer than most. Thanks to early access to models from GitHub Copilot, OpenAI, and Anthropic, the company has had a head start in figuring out what works.In this live episode from LDX3 in London, I spoke with Farhan Thawar, VP of Engineering, about how Shopify is building with AI across the entire stack. We cover the company’s internal LLM proxy, its policy of unlimited token usage, and how interns help push the boundaries of what’s possible.In this episode, we cover:• How Shopify works closely with AI labs• The story behind Shopify’s recent Code Red• How non-engineering teams are using Cursor for vibecoding• Tobi Lütke’s viral memo and Shopify’s expectations around AI• A look inside Shopify’s LLM proxy—used for privacy, token tracking, and more• Why Shopify places no limit on AI token spending • Why AI-first isn’t about reducing headcount—and why Shopify is hiring 1,000 interns• How Shopify’s engineering department operates and what’s changed since adopting AI tooling• Farhan’s advice for integrating AI into your workflow• And much more!—Timestamps(00:00) Intro(02:07) Shopify’s philosophy: “hire smart people and pair with them on problems”(06:22) How Shopify works with top AI labs (08:50) The recent Code Red at Shopify(10:47) How Shopify became early users of GitHub Copilot and their pivot to trying multiple tools(12:49) The surprising ways non-engineering teams at Shopify are using Cursor(14:53) Why you have to understand code to submit a PR at Shopify(16:42) AI tools' impact on SaaS (19:50) Tobi Lütke’s AI memo(21:46) Shopify’s LLM proxy and how they protect their privacy(23:00) How Shopify utilizes MCPs(26:59) Why AI tools aren’t the place to pinch pennies(30:02) Farhan’s projects and favorite AI tools(32:50) Why AI-first isn’t about freezing headcount and the value of hiring interns(36:20) How Shopify’s engineering department operates, including internal tools(40:31) Why Shopify added coding interviews for director-level and above hires(43:40) What has changed since Spotify added AI tooling (44:40) Farhan’s advice for implementing AI tools—The Pragmatic Engineer deepdives relevant for this episode:• How Shopify built its Live Globe for Black Friday• Inside Shopify's leveling split• Real-world engineering challenges: building Cursor• How Anthropic built Artifacts—See the transcript and other references from the episode at ⁠⁠https://newsletter.pragmaticengineer.com/podcast⁠⁠—Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email [email protected]. Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe

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• The present, past and future of GitHub

  Supported by Our Partners•⁠ Statsig ⁠ — ⁠ The unified platform for flags, analytics, experiments, and more.• Graphite — The AI developer productivity platform. • Augment Code — AI coding assistant that pro engineering teams love—GitHub recently turned 17 years old—but how did it start, how has it evolved, and what does the future look like as AI reshapes developer workflows?In this episode of The Pragmatic Engineer, I’m joined by Thomas Dohmke, CEO of GitHub. Thomas has been a GitHub user for 16 years and an employee for 7. We talk about GitHub’s early architecture, its remote-first operating model, and how the company is navigating AI—from Copilot to agents. We also discuss why GitHub hires junior engineers, how the company handled product-market fit early on, and why being a beloved tool can make shipping harder at times.Other topics we discuss include:• How GitHub’s architecture evolved beyond its original Rails monolith• How GitHub runs as a remote-first company—and why they rarely use email • GitHub’s rigorous approach to security• Why GitHub hires junior engineers• GitHub’s acquisition by Microsoft• The launch of Copilot and how it’s reshaping software development• Why GitHub sees AI agents as tools, not a replacement for engineers• And much more!—Timestamps(00:00) Intro(02:25) GitHub’s modern tech stack(08:11) From cloud-first to hybrid: How GitHub handles infrastructure(13:08) How GitHub’s remote-first culture shapes its operations(18:00) Former and current internal tools including Haystack(21:12) GitHub’s approach to security (24:30) The current size of GitHub, including security and engineering teams(25:03) GitHub’s intern program, and why they are hiring junior engineers(28:27) Why AI isn’t a replacement for junior engineers (34:40) A mini-history of GitHub (39:10) Why GitHub hit product market fit so quickly (43:44) The invention of pull requests(44:50) How GitHub enables offline work(46:21) How monetization has changed at GitHub since the acquisition (48:00) 2014 desktop application releases (52:10) The Microsoft acquisition (1:01:57) Behind the scenes of GitHub’s quiet period (1:06:42) The release of Copilot and its impact(1:14:14) Why GitHub decided to open-source Copilot extensions(1:20:01) AI agents and the myth of disappearing engineering jobs(1:26:36) Closing—The Pragmatic Engineer deepdives relevant for this episode:• AI Engineering in the real world• The AI Engineering stack•  How Linux is built with Greg Kroah-Hartman•  Stacked Diffs (and why you should know about them)•  50 Years of Microsoft and developer tools—See the transcript and other references from the episode at ⁠⁠https://newsletter.pragmaticengineer.com/podcast⁠⁠—Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email [email protected]. Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe

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• TDD, AI agents and coding with Kent Beck

  Supported by Our Partners• Sonar —  Code quality and code security for ALL code. •⁠ Statsig ⁠ — ⁠ The unified platform for flags, analytics, experiments, and more.• Augment Code — AI coding assistant that pro engineering teams love.—Kent Beck is one of the most influential figures in modern software development. Creator of Extreme Programming (XP), co-author of The Agile Manifesto, and a pioneer of Test-Driven Development (TDD), he’s shaped how teams write, test, and think about code.Now, with over five decades of programming experience, Kent is still pushing boundaries—this time with AI coding tools. In this episode of Pragmatic Engineer, I sit down with him to talk about what’s changed, what hasn’t, and why he’s more excited than ever to code.In our conversation, we cover:• Why Kent calls AI tools an “unpredictable genie”—and how he’s using them• Why Kent no longer has an emotional attachment to any specific programming language• The backstory of The Agile Manifesto—and why Kent resisted the word “agile”• An overview of XP (Extreme Programming) and how Grady Booch played a role in the name • Tape-to-tape experiments in Kent’s childhood that laid the groundwork for TDD• Kent’s time at Facebook and how he adapted to its culture and use of feature flags• And much more!—Timestamps(00:00) Intro(02:27) What Kent has been up to since writing Tidy First(06:05) Why AI tools are making coding more fun for Kent and why he compares it to a genie(13:41) Why Kent says languages don’t matter anymore(16:56) Kent’s current project building a small talk server(17:51) How Kent got involved with The Agile Manifesto(23:46) Gergely’s time at JP Morgan, and why Kent didn’t like the word ‘agile’(26:25) An overview of “extreme programming” (XP) (35:41) Kent’s childhood tape-to-tape experiments that inspired TDD(42:11) Kent’s response to Ousterhout’s criticism of TDD(50:05) Why Kent still uses TDD with his AI stack (54:26) How Facebook operated in 2011(1:04:10) Facebook in 2011 vs. 2017(1:12:24) Rapid fire round—The Pragmatic Engineer deepdives relevant for this episode:• —See the transcript and other references from the episode at ⁠⁠https://newsletter.pragmaticengineer.com/podcast⁠⁠—Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email [email protected]. Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe

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• 50 Years of Microsoft and Developer Tools with Scott Guthrie

  Supported by Our Partners•⁠ Statsig ⁠ — ⁠ The unified platform for flags, analytics, experiments, and more.•⁠ Sinch⁠ — Connect with customers at every step of their journey.•⁠ Modal⁠ — The cloud platform for building AI applications.—How has Microsoft changed since its founding in 1975, especially in how it builds tools for developers?In this episode of The Pragmatic Engineer, I sit down with Scott Guthrie, Executive Vice President of Cloud and AI at Microsoft. Scott has been with the company for 28 years. He built the first prototype of ASP.NET, led the Windows Phone team, led up Azure, and helped shape many of Microsoft’s most important developer platforms.We talk about Microsoft’s journey from building early dev tools to becoming a top cloud provider—and how it actively worked to win back and grow its developer base.In this episode, we cover:• Microsoft’s early years building developer tools • Why Visual Basic faced resistance from devs back in the day: even though it simplified development at the time• How .NET helped bring a new generation of server-side developers into Microsoft’s ecosystem• Why Windows Phone didn’t succeed • The 90s Microsoft dev stack: docs, debuggers, and more• How Microsoft Azure went from being the #7 cloud provider to the #2 spot today• Why Microsoft created VS Code• How VS Code and open source led to the acquisition of GitHub• What Scott’s excited about in the future of developer tools and AI• And much more!—Timestamps(00:00) Intro(02:25) Microsoft’s early years building developer tools(06:15) How Microsoft’s developer tools helped Windows succeed(08:00) Microsoft’s first tools were built to allow less technically savvy people to build things(11:00) A case for embracing the technology that’s coming(14:11) Why Microsoft built Visual Studio and .NET(19:54) Steve Ballmer’s speech about .NET(22:04) The origins of C# and Anders Hejlsberg’s impact on Microsoft (25:29) The 90’s Microsoft stack, including documentation, debuggers, and more(30:17) How productivity has changed over the past 10 years (32:50) Why Gergely was a fan of Windows Phone—and Scott’s thoughts on why it didn’t last(36:43) Lessons from working on (and fixing)  Azure under Satya Nadella (42:50) Codeplex and the acquisition of GitHub(48:52) 2014: Three bold projects to win the hearts of developers(55:40) What Scott’s excited about in new developer tools and cloud computing (59:50) Why Scott thinks AI will enhance productivity but create more engineering jobs—The Pragmatic Engineer deepdives relevant for this episode:• Microsoft is dogfooding AI dev tools’ future• Microsoft’s developer tools roots• Why are Cloud Development Environments spiking in popularity, now?• Engineering career paths at Big Tech and scaleups• How Linux is built with Greg Kroah-Hartman—See the transcript and other references from the episode at ⁠⁠https://newsletter.pragmaticengineer.com/podcast⁠⁠—Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email [email protected]. Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe

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• From Software Engineer to AI Engineer – with Janvi Kalra

  Supported by Our Partners•⁠ Statsig ⁠ — ⁠ The unified platform for flags, analytics, experiments, and more.•⁠ Sinch⁠ — Connect with customers at every step of their journey.•⁠ Cortex⁠ — Your Portal to Engineering Excellence.—What does it take to land a job as an AI Engineer—and thrive in the role?In this episode of Pragmatic Engineer, I’m joined by Janvi Kalra, currently an AI Engineer at OpenAI. Janvi shares how she broke into tech with internships at top companies, landed a full-time software engineering role at Coda, and later taught herself the skills to move into AI Engineering: by things like building projects in her free time, joining hackathons, and ultimately proving herself and earning a spot on Coda’s first AI Engineering team.In our conversation, we dive into the world of AI Engineering and discuss three types of AI companies, how to assess them based on profitability and growth, and practical advice for landing your dream job in the field.We also discuss the following: • How Janvi landed internships at Google and Microsoft, and her tips for interview prepping• A framework for evaluating AI startups• An overview of what an AI Engineer does• A mini curriculum for self-learning AI: practical tools that worked for Janvi• The Coda project that impressed CEO Shishir Mehrotra and sparked Coda Brain• Janvi’s role at OpenAI and how the safety team shapes responsible AI• How OpenAI blends startup speed with big tech scale• Why AI Engineers must be ready to scrap their work and start over• Why today’s engineers need to be product-minded, design-aware, full-stack, and focused on driving business outcomes• And much more!—Timestamps(00:00) Intro(02:31) How Janvi got her internships at Google and Microsoft(03:35) How Janvi prepared for her coding interviews (07:11) Janvi’s experience interning at Google(08:59) What Janvi worked on at Microsoft (11:35) Why Janvi chose to work for a startup after college(15:00) How Janvi picked Coda (16:58) Janvi’s criteria for picking a startup now (18:20) How Janvi evaluates ‘customer obsession’ (19:12) Fast—an example of the downside of not doing due diligence(21:38) How Janvi made the jump to Coda’s AI team(25:48) What an AI Engineer does (27:30) How Janvi developed her AI Engineering skills through hackathons(30:34) Janvi’s favorite AI project at Coda: Workspace Q&A (37:40) Learnings from interviewing at 46 companies(40:44) Why Janvi decided to get experience working for a model company (43:17) Questions Janvi asks to determine growth and profitability(45:28) How Janvi got an offer at OpenAI, and an overview of the interview process(49:08) What Janvi does at OpenAI (51:01) What makes OpenAI unique (52:30) The shipping process at OpenAI(55:41) Surprising learnings from AI Engineering (57:50) How AI might impact new graduates (1:02:19) The impact of AI tools on coding—what is changing, and what remains the same(1:07:51) Rapid fire round—The Pragmatic Engineer deepdives relevant for this episode:•⁠ AI Engineering in the real world•⁠ The AI Engineering stack•⁠ Building, launching, and scaling ChatGPT Images—See the transcript and other references from the episode at ⁠⁠https://newsletter.pragmaticengineer.com/podcast⁠⁠—Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email [email protected]. Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe

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