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The Pragmatic Engineer

Gergely Orosz
The Pragmatic Engineer
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61 épisodes

  • The Pragmatic Engineer

    TypeScript, C# and Turbo Pascal with Anders Hejlsberg

    13/05/2026 | 1 h 15 min
    Brought to You By:
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    • WorkOS – Everything you need to make your app enterprise ready.
    • turbopuffer – a vector and full-text search engine built on object storage. It’s fast, cheap, and extremely scalable.

    Anders Hejlsberg is a living legend and one of the most influential programming language designers of all time. He created Turbo Pascal, Delphi, C#, and also TypeScript. As well as that, he spent nearly a decade at the pioneering dev tools company, Borland, and is now in his 30th year of working at Microsoft, where he’s a Technical Fellow.
    In this episode, we discuss what it takes to build programming languages that developers love to use, and trace his career from writing his first compiler to creating Turbo Pascal and Delphi, and helping to pioneer modern software development through C# and TypeScript.
    Anders details how C# was designed by a small group of experienced language designers who met a few hours each week, and he explains why tooling was just as important as the language for TypeScript’s success, and what he has learned from building languages which stay relevant for decades.
    We also look into how Anders uses AI today, which language features suit AI-assisted development, and what he thinks is changing in the craft of software engineering as developers move further away from writing code line by line.

    Timestamps
    (00:00) Intro
    (02:48) How Anders got into programming 
    (05:40) Building his first compiler 
    (07:44) Turbo Pascal
    (12:25) Delphi 
    (14:53) Joining Microsoft
    (19:41) Building C# 
    (29:11) Async/await
    (34:01) The rise of JavaScript
    (37:52) Building TypeScript
    (42:58) How the TypeScript compiler works 
    (48:30) JavaScript’s strengths and weaknesses
    (52:18) How Anders uses AI 
    (56:03) What language features work well with AI 
    (1:02:49) How software craftsmanship is changing
    (1:07:49) Performance and efficiency 
    (1:09:29) Anders’ tool stack 
    (1:11:30) A 30-year career at Microsoft
    (1:13:40) Book recommendation

    The Pragmatic Engineer deepdives relevant for this episode:
    • Microsoft’s developer tools roots
    • 50 Years of Microsoft and developer tools with Scott Guthrie
    • How Linux is built with Greg Kroah-Hartman
    • How will AI change operating systems? Part 1: Ubuntu and Linux
    • How Uber uses AI for development: inside look

    Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email [email protected].


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  • The Pragmatic Engineer

    Building Pi, and what makes self-modifying software so fascinating

    29/04/2026 | 1 h 33 min
    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.

    Mario Zechner is the creator of Pi, a minimalist, self-modifying AI coding agent, that is the foundation upon which OpenClaw (created by Peter Steinberger) is built. Meanwhile, Armin Ronacher is the creator of Flask, and a longtime user of Pi. The pair are also friends.
    I sat down with Mario and Armin for the latest episode of the Pragmatic Engineer Podcast for an interesting conversation about AI and their reservations about it – even though both are heavily invested in building AI-powered tools.
    Mario explains why he built Pi, and gives his take on why it has become so popular. Armin walks us through how he uses AI tools, including building a game with Pi, and why he always puts human judgment firmly at the heart of his approach.
    We cover the risks of over-automation, the limits of agentic workflows, and why strong engineers with informed judgment still matter. We also get into the challenges of working with code written by non-engineers, and whether open source can withstand a tidal wave of agent-generated code.

    Timestamps
    (00:00) Intro
    (07:30) How Mario, Armin, and Peter Steinberger met(15:15) How 30 dev teams use AI agents: learnings
    (21:50) The importance of judgment
    (24:26) Challenges when non-engineers write code
    (28:30) Downsides of over-automation
    (32:18) Pi
    (48:09) OpenClaw + Pi
    (50:54) “Clankers”
    (57:32) Open source and AI
    (1:00:22) Complexity as the enemy
    (1:02:50) Building an AI-native startup
    (1:11:52) “Slow the F down”
    (1:16:40) MCPs vs. CLI
    (1:25:03) Predictions and staying up to date

    The Pragmatic Engineer deepdives relevant for this episode:
    • The impact of AI on software engineers in 2026: key trends
    • Cycles of disruption in the tech industry
    • The AI engineering stack
    • The creator of OpenClaw: "I ship code that I don't read"
    • What is inference engineering? Deepdive

    Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email [email protected].


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  • The Pragmatic Engineer

    Designing Data-intensive Applications with Martin Kleppmann

    22/04/2026 | 1 h 25 min
    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.

    Martin Kleppmann is a researcher and the author of Designing Data-Intensive Applications, one of the most influential books on modern distributed systems. As of this month, the second, heavily updated edition of the book is out.
    In this episode of Pragmatic Engineer, we discuss Martin’s career in tech building startups, how he ended up writing this iconic book, and what he’s focused on now after moving into academia.
    We talk about the tradeoffs behind modern infrastructure, how the cloud has changed what it means to scale, and the thinking behind Designing Data-Intensive Applications, including what’s changing in the second edition.
    Martin reflects on lessons from building startups like Rapportive, which he sold to LinkedIn, and shares how his experience in both academia and industry shaped his perspective.
    We also explore what’s ahead: why formal verification may become more important in an AI-assisted world, the challenges of building local-first software, and his recent research into using cryptography to improve transparency in supply chains without exposing sensitive data.

    Timestamps
    (00:00) Early career
    (05:46) Building Rapportive
    (10:47) Working at LinkedIn
    (14:09) Writing Designing Data-Intensive Applications
    (23:00) Reliability, scalability, and repeatability 
    (26:24) DDIA: the second edition
    (30:50) Tradeoffs of using cloud services 
    (39:02) How the cloud changed scaling 
    (42:53) The trouble with distributed systems
    (49:02) Ethics for software engineers 
    (52:45) Formal verification
    (1:00:12) Academia vs. industry 
    (1:03:50) Local-first software 
    (1:09:50) Computer science education
    (1:18:32) Martin’s current research and advice

    The Pragmatic Engineer deepdives relevant for this episode:
    • Building Bluesky: a distributed social network
    • Inside Uber’s move to the cloud
    • The history of servers, the cloud, and what’s next
    • The past and future of modern backend practices
    • How Kubernetes is built

    Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email [email protected].


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  • The Pragmatic Engineer

    DHH’s new way of writing code

    08/04/2026 | 1 h 46 min
    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.

    David Heinemeier Hansson (DHH) is the creator of Ruby on Rails and Omarchy, co-founder and CTO of 37signals (maker of Basecamp and HEY), and the author of several books including the best-seller, Remote: Office Not Required, co-written with Jason Fried.
    Six months ago, in an episode of the Lex Fridman podcast, David shared how he doesn’t use AI tools to write code: he types out all his code. But things have changed a lot since then. 
    In this episode, we discuss his approach to building software, how it’s changed in the last six months, and why he now takes an agent-first approach, and how he barely writes any code by hand. We go into how he uses AI agents: which alter how he builds and explores ideas, but also how his standards of quality and craft remain the same.
    We also discuss how 37signals thinks about product development, from the role of designers to the importance of aesthetics and taste. David gets into how he sees beauty and functionality as closely linked, and why strong opinions about design lead to better software.
    Finally, we look into the uneven impact of AI which amplifies senior engineers while creating challenges for junior developers, and what this may mean for the role of the software engineer.

    Timestamps
    (00:00) Intro
    (02:11) Omarchy and Ruby on Rails
    (08:25) 37signals overview
    (10:12) Launching HEY
    (18:38) Building HEY
    (22:47) Designers at 37signals
    (28:08) The craft of design
    (31:52) Why DHH now embraces AI workflows
    (39:45) The AI inflection point
    (44:23) DHH’s agent-first workflow
    (55:09) AI’s impact on junior developers
    (1:03:08) Developer experience with AI
    (1:16:43) What does AI mean for developers?
    (1:23:33) 37signals teams and hiring
    (1:38:20) Work-life balance with AI
    (1:41:41) Why DHH keeps building
    (1:45:24) Closing

    The Pragmatic Engineer deepdives relevant for this episode:
    • Are AI agents actually slowing us down?
    • How Claude Code is built
    • The future of software engineering with AI: six predictions
    • The AI Engineering Stack
    • Mitchell Hashimoto’s new way of writing code
    • How Linux is built with Greg Kroah-Hartman

    Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email [email protected].


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  • The Pragmatic Engineer

    Scaling Uber with Thuan Pham (Uber’s first CTO)

    01/04/2026 | 1 h 38 min
    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.

    Thuan Pham was Uber's first and longest-serving CTO, and today he’s the CTO of Faire, a B2B wholesale platform. Back when Thuan joined Uber, it had around 40 engineers and 30,000 rides per day, and the system crashed multiple times a week. Over seven years, he helped rebuild the system, move it from a monolith to microservices, and scaled the engineering organization behind it. I had the privilege of working with Thuan for four of those seven years. Later, the very first issue of The Pragmatic Engineer newsletter was a deepdive into Uber’s Program and Platform split. This episode of the podcast contains a nice “full circle” moment, where Thuan shares even more details about why Uber chose to embrace that structure.
    We discuss what it takes to operate and build in that kind of environment. Thuan explains how he divided his time at Uber into three “tours of duty,” from stabilizing a fragile system, to re-architecting it, and scaling the org.
    We go deep into the platform-and-program split, the Helix app rewrite, and what it took to launch Uber in China in just five months (the original estimate was 18 months). We also cover Uber’s in-house tools and explain why they were necessary to support rapid growth.
    Finally, we discuss his role today as CTO of Faire, how the company is using AI, and how he sees AI changing software engineering.

    Timestamps
    (00:00) Intro
    (05:32) Getting into tech
    (16:09) The dot-com bust
    (20:42) VMware
    (26:29) Getting hired by Travis at Uber
    (33:22) Early days at Uber and scaling challenges
    (40:57) Uber’s China launch
    (47:12) The platform and program split
    (50:26) From monolith to microservices 
    (53:38) Internal tools at Uber 
    (57:05) Helix: Uber’s mobile app rewrite
    (59:55) Thuan’s email about naming
    (1:02:03) Org structure changes under
    (1:06:34) Thuan’s work philosophy 
    (1:12:23) The “three tours of duty” at Uber
    (1:15:37) Why Thuan left Uber 
    (1:17:34) Coupang and Nubank
    (1:21:59) Faire
    (1:25:31) How Faire uses AI
    (1:28:24) AI’s impact on software engineering 
    (1:31:09) The role of the CTO 
    (1:35:13) Career advice

    The Pragmatic Engineer deepdives relevant for this episode:
    • How Uber uses AI for development: inside look
    • The Platform and Program split at Uber
    • How Uber is measuring engineering productivity
    • Inside Uber’s move to the cloud
    • Uber's crazy YOLO app rewrite, from the front seat
    • How Uber built its observability platform
    • Developer experience at Uber with Gautam Korlam
    • Uber’s engineering level changes

    Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email [email protected].


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À propos de The Pragmatic Engineer
Software engineering at Big Tech and startups, from the inside. Deepdives with experienced engineers and tech professionals who share their hard-earned lessons, interesting stories and advice they have on building software. Especially relevant for software engineers and engineering leaders: useful for those working in tech. newsletter.pragmaticengineer.com
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