The Pragmatic Engineer

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How did a tiny team of 30 engineers build the world-famous messaging app more than a decade ago, and what can dev teams learn from that feat today? Jean Lee was engineer #19 at WhatsApp, joining when the company was still small, with almost no formal processes. She helped it scale to hundreds of millions of users, went through the $19B acquisition by Facebook, and later worked at Meta.
In this episode of Pragmatic Engineer, I talk with Jean about what it was like building WhatsApp. When Facebook bought WhatsApp in 2014, only around 30 engineers supported hundreds of millions of users across eight platforms.
We discuss how the founders kept things simple, saying “no” to most feature requests for years. Jean explains why WhatsApp chose Erlang for the backend, why the team avoided cross-platform abstractions, and how charging users $1 per year paid everyone’s salaries, while keeping growth intentionally slow.
Jean also shares what the Facebook acquisition was like on the inside, how she dealt with sudden personal wealth, and what it was like transitioning from an IC to a manager at Facebook – including the reality of calibration meetings and performance reviews.
We also discuss how AI enables smaller engineering teams, and why WhatsApp’s experience suggests ownership and trust might matter more than tools.
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Timestamps
(00:00) Intro
(01:39) Early years in tech
(06:18) Becoming engineer #19 at WhatsApp
(13:53) WhatsApp’s tech stack
(18:09) WhatsApp’s unique ways of working
(25:27) Countdown displays and outages
(27:07) Why WhatsApp won
(28:53) The Facebook acquisition
(33:13) Life after acquisition
(39:27) Working at Facebook in London
(44:07) Transitioning to management
(47:27) Performance reviews as a manager
(53:29) After Facebook
(58:53) AI’s impact on engineering
(1:02:34) Jean’s advice to new grads and startups
(1:06:45) Empowering employees
(1:08:17) Book recommendations
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The Pragmatic Engineer deepdives relevant for this episode:
• How Meta built Threads
• How Big Tech runs tech projects and the curious absence of Scrum
• Performance calibrations at tech companies
• Software engineers leading projects
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Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe

Brought to You By:
• Statsig — ⁠ The unified platform for flags, analytics, experiments, and more.
• Sonar – The makers of SonarQube, the industry standard for automated code review
• WorkOS – Everything you need to make your app enterprise ready.
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Steve Yegge has spent decades writing software and thinking about how the craft evolves. From his early years at Amazon and Google, to his influential blog posts, he has often been early at spotting shifts in how software gets built. 
In this episode of Pragmatic Engineer, I talk with Steve about how AI is changing engineering work, why he believes coding by hand may gradually disappear, and what developers should focus on, instead. We discuss his latest book, Vibe Coding, and the open-source AI agent orchestrator he built called Gas Town, which he said most devs should avoid using.
Steve shares his framework for levels of AI adoption by engineers, ranging from avoiding AI tools entirely, to running multiple agents in parallel. We discuss why he believes the knowledge that engineers need to know keeps changing, and why understanding how systems evolve may matter more than mastering any particular tool.
We also explore broader implications. Steve argues that AI’s role is not primarily to replace engineers, but to amplify them. At the same time, he warns that the pace of change will create new kinds of technical debt, new productivity pressures, and fresh challenges for how teams operate.
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Timestamps
(00:00) Intro
(01:43) Steve’s latest projects
(02:27) Important blog posts
(04:48) Shifts in what engineers need to know
(10:46) Steve’s current AI stance
(13:23) Steve’s book Vibe Coding
(18:25) Layoffs and disruption in tech
(31:13) Gas Town
(40:10) New ways of working
(51:08) The problem of too many people
(54:45) Why AI results lag in business
(59:57) Gamification and product stickiness
(1:04:54) The ‘Bitter Lesson’ explained
(1:07:14) The future of software development
(1:23:06) Where languages stand
(1:24:47) Adapting to change
(1:27:32) Steve’s predictions 
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The Pragmatic Engineer deepdives relevant for this episode:
• Vibe coding as a software engineer
• The full circle of developer productivity with Steve Yegge
• AI Tooling for Software Engineers in 2026
• The AI Engineering Stack
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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

Brought to You By:
• Statsig — ⁠ The unified platform for flags, analytics, experiments, and more.
• Sonar – The makers of SonarQube, the industry standard for automated code review
• WorkOS – Everything you need to make your app enterprise ready.
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Boris Cherny is the creator and Head of Claude Code at Anthropic. He previously spent five years at Meta as a Principal Engineer and is the author of the book Programming TypeScript.
In this episode of Pragmatic Engineer, we went through how Claude Code was built and what it means when engineers no longer write most of the code themselves.
We discuss how Claude Code evolved from a side project into a core internal tool at Anthropic and how Boris uses it day-to-day. We go deep into workflow details, including parallel agents, PR structure, deterministic review patterns, and how the system retrieves context from large codebases. We also get into how Claude Cowork was built.
As coding becomes more accessible, the role of engineers shifts rather than shrinks. We examine what that shift means in practice, which skills become more important, and why the lines between product, engineering, and design are blurring.
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Timestamps
(00:00) Intro
(11:15) Lessons from Meta
(19:46) Joining Anthropic
(23:08) The origins of Claude Code
(32:55) Boris's Claude Code workflow
(36:27) Parallel agents
(40:25) Code reviews
(47:18) Claude Code's architecture
(52:38) Permissions and sandboxing
(55:05) Engineering culture at Anthropic
(1:05:15) Claude Cowork
(1:12:48) Observability and privacy
(1:14:45) Agent swarms
(1:21:16) LLMs and the printing press analogy
(1:30:16) Standout engineer archetypes
(1:32:12) What skills still matter for engineers
(1:35:24) Book recommendations
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The Pragmatic Engineer deepdives relevant for this episode:
• How Claude Code is built
• How Anthropic built Artifacts
• How Codex is built
• Real-world engineering challenges: building Cursor
—
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

Brought to You By:
• Statsig — ⁠ The unified platform for flags, analytics, experiments, and more.
• Sonar – The makers of SonarQube, the industry standard for automated code review
• WorkOS – Everything you need to make your app enterprise ready.
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How has the day-to-day workflow of Mitchell Hashimoto changed, thanks to AI tools?
Mitchell Hashimoto is one of the most influential infrastructure engineers of our time, and is one of the most pragmatic builders I’ve met. He is the co-founder of HashiCorp and creator of Ghostty. In this episode, we talk about how he got into software engineering, the history of HashiCorp, and the challenges of turning widely used open-source tools into a durable business. We also go into what it’s really like to work with AWS, Azure and GCP as a startup.
Mitchell shares how he uses AI these days, and how agents have completely changed how he works. We touch on Ghostty, open source, and what’s changing for software engineers and founders in an AI-native era.
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Timestamps
(00:00) Intro
(02:03) Mitchell’s path into software engineering
(07:19) The origins of HashiCorp
(15:52) Early cloud computing
(18:22) The 2010s startup scene in SF
(23:11) Funding HashiCorp
(25:23) The Hashi stack
(32:33) Why HashiCorp’s business lagged behind its technology
(35:28) An early failure in commercialization
(38:28) The open-core pivot and path to enterprise profitability
(48:08) Taking HashiCorp public
(51:58) The near VMware acquisition
(59:10) Mitchell’s take on all the cloud providers
(1:06:02) AI’s impact on open source
(1:07:00) Why Mitchell built Ghostty
(1:09:11) Why Mitchell used Zig
(1:10:38) How terminals work and Ghostty’s approach
(1:17:31) AI’s impact on terminals and libghostty
(1:19:13) How Mitchell uses AI
(1:22:02) Ghostty’s evolving AI use policy
(1:28:36) Why open source must change
(1:31:46) The problem of Git in monorepos
(1:36:22) What needs to change to work effectively with AI
(1:39:57) Mitchell’s hiring practices
(1:47:52) Mitchell’s AI adoption journey
(1:50:41) Advice to would-be founders
(1:52:21) Mitchell’s advising work
(1:53:20) What’s changing for software engineers
(1:55:03) How Mitchell recharges
(1:55:50) Book recommendation
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The Pragmatic Engineer deepdives relevant for this episode:
• AI Engineering in the real world
• The AI Engineering stack
• Pressure on commercial open source to make more money – and HashiCorp changing its license
• How Linux is built with Greg Kroah-Hartman
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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

Brought to You By:
• Statsig — ⁠ The unified platform for flags, analytics, experiments, and more.
• Sonar – The makers of SonarQube, the industry standard for automated code review
• WorkOS – Everything you need to make your app enterprise ready.
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Andrey Breslav is the creator of Kotlin and the founder of CodeSpeak, a new programming language that aims to reduce boilerplate by replacing trivial code with concise, plain-English descriptions. He led Kotlin’s design at JetBrains through its early releases, shaping both the language and its compiler as Kotlin grew into a core part of the Android ecosystem.
In this episode, we talk about what it takes to design and evolve a programming language in production. We discuss the influences behind Kotlin, the tradeoffs that shaped it, and why interoperability with Java became so central to its success. 
Andrey also explains why he is building CodeSpeak as a response to growing code complexity in an era of LLM agents, and why he believes keeping humans in control of the software development lifecycle will matter even more as AI becomes more capable.
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Timestamps
(00:00) Intro
(01:02) Why Kotlin was created
(06:26) Dynamic vs. static languages
(09:27) Andrey joins the Kotlin project
(14:26) Designing a new language 
(19:40) Frontend vs. Backend in language design
(21:05) Why is it named Kotlin?
(24:37) Kotlin vs. Java tradeoffs
(28:32) Null safety 
(31:24) Kotlin’s influences 
(39:12) Smartcasts 
(40:42) Features Kotlin left out
(44:54) Bidirectional Java interoperability
(55:01) The Kotlin timeline 
(58:00) Kotlin’s development process
(1:07:20) From Java to Android developers
(1:12:12) How Android became Kotlin-first 
(1:18:20) CodeSpeak: a language for LLMs
(1:24:07) LLMs and new languages
(1:28:20) How software engineering is changing with AI
(1:36:12) Developer tools of the future 
(1:39:00) Andrey’s advice for junior engineers and students 
(1:42:32) Rapid fire round
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The Pragmatic Engineer deepdives relevant for this episode:
• Cross-platform mobile development
• How Swift was built – with Chris Lattner, the creator of the language
• Building Reddit’s iOS and Android app
• Notion: going native on iOS and Android
• Is there a drop in native iOS and Android hiring at startups?
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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