The Pragmatic Engineer

Gergely Orosz

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

  1. Tech interviews with NeetCode

    ৫ দিন আগে

    Tech interviews with NeetCode

    Brought to You By: • Antithesis – verify your system’s correctness without human review or traditional integration tests – and avoid bugs or outages. • Sentry – application monitoring software considered “not bad” by millions of developers • Google Cloud Run – run your code and host LLMs directly on top of Google’s scalable infrastructure, without having to worry about managing infra. — Navdeep Singh – oftentimes better known as NeetCode – is the creator of NeetCode.io, one of the most popular coding interview preparation platforms and YouTube channels for software engineers. Before building NeetCode full-time, he worked as a software engineer at Amazon and Google. In this episode of The Pragmatic Engineer, I sit down with Neet to discuss his path from Amazon and Google to building his own startup, why he left Amazon after just two months, what he learned at Google, and the decision to leave a stable engineering career to bet on himself. We also discuss what coding interview preparation teaches beyond passing interviews, the value of going deep on difficult problems, and why systems thinking and domain expertise remain essential engineering skills in the age of AI. Throughout the conversation, NeetCode makes the case that learning hard things is one of the single best investments an engineer can make, helping build the judgment and expertise that remain valuable no matter how the tools change. — Timestamps 00:00 Intro 02:57 Neet’s take on coding interviews 06:41 Getting into tech 08:56 Why Neet isn't a fan of the CAP theorem 13:12 Quitting Amazon after two months 18:22 Google vs Amazon 22:26 The origins of NeetCode 25:27 Leaving Google to go all in on NeetCode 32:02 Why Neet doesn't fix every bug 39:26 The value of coding interview prep 42:57 Systems thinking and domain expertise 47:28 Hiring at Big Tech 52:15 Tech stack at Neetcode 57:57 The NeetCode  redesign contest 1:01:46 The future of software engineers 1:09:04 Hot takes: AGI, AI skill erosion, personality traits 1:22:49 “Maybe some people should just give up” 1:24:39 How to be a standout engineer 1:27:55 Book recommendation — The Pragmatic Engineer deepdives relevant for this episode: • Learnings from conducting ~1,000 interviews at Amazon • How experienced engineers get unstuck in coding interviews • The Reality of Tech Interviews in 2025 • Tech hiring: is this an inflection point? • AI fakers exposed in tech dev recruitment: postmortem — Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email podcast@pragmaticengineer.com. Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe

    ১ঘঃ ২৯মিঃ
  2. CI/CD with Robert Erez

    ১৭ জুন

    CI/CD with Robert Erez

    Brought to You By: • Antithesis – verify your system’s correctness without human review or traditional integration tests – and avoid bugs or outages. • 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. — Robert Erez is a principal engineer at Octopus Deploy, and a longtime expert in CI/CD, deployment systems, and software delivery. Rob and I were also once colleagues on the Skype web team, working on large-scale deployments and release processes. In this episode of The Pragmatic Engineer, I sit down with Rob to discuss how teams deploy software safely and efficiently at scale. We cover Kubernetes, GitOps, platform engineering, progressive delivery, feature flags, cloud development environments, and the growing role of AI in CI/CD workflows. We also get into the tradeoffs in different deployment approaches, why self-hosted software still matters for some organizations, and the recent evolution of software delivery practices. — Timestamps 00:00 Intro 02:09 Canary deployments at Skype 05:01 Joining at Octopus Deploy 06:15 Continuous deployment 10:26 Why Kubernetes won 15:51 Kubernetes on-prem 18:50 How GitOps works 25:00 The uses and limitations of GitOps 31:04 The rise of platform teams 35:51 How AI is changing CI/CD 39:49 Progressive delivery explained 47:31 Rollbacks and roll-forwards 50:14 Feature flags 54:32 How development environments are evolving 57:40 Cloud development environments (CDEs) 1:03:45 Self-hosting CI/CD 1:09:25 Getting started with progressive delivery 1:11:15 Book recommendations — The Pragmatic Engineer deepdives relevant for this episode: • Kubernetes and retiring at the top with Kelsey Hightower • The past and future of modern backend practices • Microsoft is dogfooding AI dev tools’ future • How Kubernetes is built with Kat Cosgrove • How Linux is built with Greg KH — Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email podcast@pragmaticengineer.com. Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe

    ১ঘঃ ১৫মিঃ
  3. Kubernetes and retiring at the top with Kelsey Hightower

    ৩ জুন

    Kubernetes and retiring at the top with Kelsey Hightower

    Brought to You By: • Antithesis – verify your system’s correctness without human review or traditional integration tests – and avoid bugs or outages. • Buildkite – CI software built to absorb whatever your coding agents throw at the build queue • Sentry – application monitoring software considered “not bad” by millions of developers — Kelsey Hightower went from a self-taught technician installing DSL modems to becoming one of Google’s elite Distinguished Engineers, whom the CEO of Microsoft personally tried to recruit. Hightower’s career achievements are rooted in hard work and self-directed learning, and today he’s one of the most influential voices in modern infrastructure, through his talks, open source work, and writing. In this episode of The Pragmatic Engineer podcast, Kelsey and I cover his unconventional path into tech and the lessons he’s learned during three decades in the industry. We discuss his entrepreneurial years, building a reputation through open source, the rise of containers and Kubernetes, and his time at Google during one of the most consequential periods in cloud computing.  He recounts how a job offer from a big tech giant led to the biggest raise of his career, what prompted him to slow down after years of career acceleration, and we also discuss his perspective on AI. Throughout, Kelsey keeps a simple idea front of mind: that technology is ultimately about people. Whether it’s infrastructure, leadership, careers, or AI, he argues that the goal is not to build technology for its own sake; it’s to solve meaningful human problems. — Timestamps 00:00 Intro 03:34 Kelsey’s first job at McDonald’s 05:04 His non-traditional path into tech 11:45 Landing his first tech job with an A+ certification 15:33 His entrepreneurial years 19:45 Joining Google as a data center technician 27:48 Learning automation at a Rackspace spinoff 33:26 Moving into financial services 50:00 Building a reputation through open source 53:55 From configuration management to containers 1:08:20 The rise of Kubernetes 1:25:05 Why he almost joined NASA instead of Google 1:29:20 Defining DevRel at Google 1:38:20 Demonstrating impact at Google 1:41:20 Microsoft's offer 1:55:20 Learning how to slow down 2:06:39 Advising and investing 2:15:03 A people-first view of GenAI 2:24:27 Using AI with guardrails 2:28:26 Matching AI to the task 2:36:06 Staying relevant in the AI era — The Pragmatic Engineer deepdives relevant for this episode: • Career paths for software engineers at large tech companies • The past and future of modern backend practices • How Kubernetes is built • How Linux is built • The Staff Engineer’s Path: You’re a role model now (sorry!) — Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email podcast@pragmaticengineer.com. Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe

    ২ ঘঃ ৫১ মিঃ
  4. Building OpenCode with Dax Raad

    ২৭ মে

    Building OpenCode with Dax Raad

    Brought to You By: • Antithesis – verify your system’s correctness without human review or traditional integration tests – and avoid bugs or outages. • 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. — OpenCode is one of the fastest-growing AI developer tools around, surging in just a few months from roughly 650,000 monthly active users to nearly 8 million, and almost 1M daily active users. In this episode of The Pragmatic Engineer Podcast, we meet Dax Raad, co-founder of OpenCode, for a discussion about the gaps in developer tooling that led him to build OpenCode, the advantages of open source, and why taste and engineering judgment matter even more as AI becomes a core part of software development. We also cover how OpenCode turned Anthropic’s blocking of integration with Claude Code into a massive growth lever by partnering with OpenAI and other model providers, why GPU demand is becoming a bottleneck everywhere, how come AI coding tools don’t automatically mean engineering teams move faster, and also why Dax is personally skeptical about predictions for the future of engineering and work, in general. I found this conversation especially interesting because Dax displays a healthy skepticism toward the benefits of AI, even while building one of the most popular AI coding harnesses. — Timestamps 00:00 Intro 07:03 Dax’s path into tech 09:04 Early startup experience 13:16 Getting involved with open source 16:13 OpenCode 23:17 Anthropic banning OpenCode 30:34 From terminal to GUI 32:34 OpenCode’s business model 36:33 Why inference is profitable 39:11 GPU bottlenecks 40:54 AI hype 45:50 AI spending 48:47 Dax’s memo 55:41 Dax’s skepticism of predictions 58:58 Engineering culture at OpenCode 1:02:38 How building works at OpenCode 1:05:36 Taste and quality 1:11:32 Dax’s work setup 1:12:35 The role of engineers and EMs 1:15:50 Advice for engineers 1:18:12 Book recommendation — The Pragmatic Engineer deepdives relevant for this episode: • How Claude Code is built • How Codex is built • Real-world engineering challenges: building Cursor • The AI Engineering stack • How Uber uses AI for development: inside look — Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email podcast@pragmaticengineer.com. Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe

    ১ঘঃ ২০মিঃ
  5. Why Rust is different, with Alice Ryhl

    ২০ মে

    Why Rust is different, with Alice Ryhl

    Brought to You By: • Antithesis – verify your system’s correctness without human review or traditional integration tests – and avoid bugs or outages. • Sentry⁠ – application monitoring software considered “not bad” by millions of developers • ⁠Craft Conference⁠: join Gergely, Kent Beck, Hillel Wayne and others at the conference dedicated to the art and science of software delivery craft. — Rust is one of the most admired programming languages around – and also one of the hardest to learn. What makes developers stick with it? In this episode of The Pragmatic Engineer Podcast, I sit down with Alice Ryhl, a software engineer on Google’s Android Rust team, and a core maintainer of Tokio, which is the most widely-used async runtime in Rust. We discuss what makes Rust different from other languages like TypeScript, Go, and C++, and why so many developers say that “once it compiles, it works.” We go deep into memory safety, ownership, borrowing, unsafe Rust, and Cargo. We also cover how Rust is governed by RFCs, feature flags, its six-week release cycle, how engineers get paid to work on the language, and also look into how Rust’s use inside the Linux kernel is progressing. — Timestamps (00:00) Intro (04:09) Tokio: an overview (05:11) What Alice likes about Rust (12:48) Rust for TypeScript engineers (13:51) Moving from C++ to Rust (14:34) Memory safety (18:12) Garbage collection tradeoffs (21:46) Ownership, references, and borrowing (26:59) Unsafe in Rust (31:21) Crates and Cargo (35:55) Language design and RFCs (43:02) Building new features (46:30) Editions vs. versions (49:47) Getting paid to work on Rust (51:27) Contributing to Rust (53:03) Rust in the Linux kernel (55:45) AI use cases for Rust (1:01:35) Learning Rust (1:03:54) Book recommendation — The Pragmatic Engineer deepdives relevant for this episode: • The past and future of modern backend practices • How Kotlin was built with Andrey Breslav • How Swift was built with Chris Lattner • How Linux is built with Greg KH — Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email podcast@pragmaticengineer.com. Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe

    ১ঘঃ ৫মিঃ
  6. TypeScript, C# and Turbo Pascal with Anders Hejlsberg

    ১৩ মে

    TypeScript, C# and Turbo Pascal with Anders Hejlsberg

    Brought to You By: • Antithesis – verify your system’s correctness without human review or traditional integration tests – and avoid bugs or outages. • 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 podcast@pragmaticengineer.com. Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe

    ১ঘঃ ১৫মিঃ
  7. Building Pi, and what makes self-modifying software so fascinating

    ২৯ এপ্রি

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

    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 podcast@pragmaticengineer.com. Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe

    ১ঘঃ ৩৩মিঃ
  8. Designing Data-intensive Applications with Martin Kleppmann

    ২২ এপ্রি

    Designing Data-intensive Applications with Martin Kleppmann

    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 podcast@pragmaticengineer.com. Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe

    ১ঘঃ ২৫মিঃ
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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

তথ্য

  • ক্রিয়েটর
    Gergely Orosz
  • অ্যাকটিভ বছর
    ২০২৪ - ২০২৬
  • পর্ব
    ৬৬
  • রেটিং
    যৌনতাপূর্ণ
  • কপিরাইট
    © Gergely Orosz
  • ওয়েবসাইট দেখান
    The Pragmatic Engineer

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