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by 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.
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- Today1h 23m
Formal methods with Hillel Wayne
Brought to You By:• Antithesis – verify your system’s correctness without human review or traditional integration tests – and avoid bugs or outages.• turbopuffer – a vector and full-text search engine built on object storage. It’s fast, cheap, and extremely scalable.• WorkOS – everything you need to make your app enterprise ready.—There’s a popular theory that AI will finally make formal verification mainstream because mathematical proof of correctness will be needed when machines write most or all of the code. But will this happen? Today, I’m talking with one of the best people to tackle the prediction. Hillel Wayne is a formal methods consultant, educator, and author, who’s deeply interested in software history. In this episode of Pragmatic Engineer podcast, I sit down with Hillel to compare software engineering with traditional engineering, discuss where formal methods fit into modern software development, and we explore why they are essential for some of the world's most complex systems. We cover the formal specification language, TLA+, walk through several formal verification tools, examine why distributed systems are so difficult to reason about, and look into whether AI will make formal methods accessible to more engineering teams.—Timestamps00:00 Intro03:21 The Crossover Project10:26 What software engineering does better14:19 What traditional engineering does better17:06 Formal methods28:21 TLA+: what it is and demo35:47 TLA+ at Amazon36:59 Ways distributed systems break39:52 Formal methods and systems thinking45:09 The value of learning math49:12 What TLA+ is good for and isn’t51:39 Alloy: a declarative language for software modeling57:42 Other formal methods tools1:00:13 Property-based testing1:04:20 AI and the need for formal verification1:11:18 Logic for programmers1:13:24 Hillel’s 2025 prediction on AI’s impact1:20:19 Book recommendation—The Pragmatic Engineer deepdives relevant for this episode:• How to debug large, distributed systems: Antithesis• How AWS S3 is built• Paying down tech debt• How Big Tech does quality assurance (QA)• Bug management that works• Resiliency in distributed systems—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
- 2 weeks ago1h 32m
Context engineering with Dex Horthy
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.—Knowing how LLM contexts work and how to work around context limitations – aka “context engineering” – is becoming more important for software engineers working with LLMs. Let’s look into what works and what doesn’t, today.In this episode of The Pragmatic Engineer podcast, I sit down with the CEO and cofounder of HumanLayer, Dex Horthy, who coined the term “context engineering”. We discuss the ideas behind this context engineering, harness engineering, loop engineering, software factories, why his approach to AI-assisted software development has evolved, and how HumanLayer is helping engineering teams automate more of the software development lifecycle without sacrificing code quality.—Timestamps00:00 Intro 01:33 Dex’s path into tech03:34 Early work in platform engineering05:28 Replicated11:24 Metalytics12:36 12-factor agents18:27 Context engineering23:38 Harness engineering26:11 Context overload30:45 Loop engineering44:34 Software factories before and after AI50:33 Automation limits55:18 Three options for automating59:00 RPI framework1:04:16 Intentional compaction1:11:48 Token harder vs. token smarter1:16:44 AI slop1:19:15 HumanLayer1:29:09 Book recommendation—The Pragmatic Engineer deepdives relevant for this episode:• How Uber uses AI for development: inside look• Are AI agents actually slowing us down?• AI Tooling for Software Engineers in 2026• Vibe Coding as a software engineer• How Claude Code is built• AI Engineering in the real world• The AI Engineering Stack• How AI-assisted coding will change software engineering: hard truths• The creator of OpenClaw: "I ship code I don't read"—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
- 3 weeks ago1h 18m
The Pragmatic Engineer AMA
Brought to You By:• Antithesis – verify your system’s correctness without human review or traditional integration tests – and avoid bugs or outages.—In this special “ask me anything” episode of Pragmatic Engineer podcast, I am in the hot seat facing questions sent in by subscribers that are read out by guest Volodymyr Giginiak, CTO and cofounder of Wordsmith AI, a legal tech startup (note: I’m an investor).I tackle your questions on the software industry, AI, hiring, engineering organizations, career growth, the business model of the Pragmatic Engineer, and more. We also discuss where software engineering is headed, and I offer advice on some specific situations. Thanks to everyone who sent questions!—Timestamps00:00 Intro01:56 From Uber to writing09:22 AI-native SDLC14:00 AI and hiring19:06 Engineers currently thriving22:18 Junior roles24:44 Meta’s war mode27:54 AI at Big Tech vs. startups36:46 Tech debt41:36 Types of engineering managers44:40 Measuring AI productivity48:30 The value of CS degrees50:53 AI at Pragmatic Engineer56:09 Future-proofing your career1:01:36 The EU job market1:03:55 Making money as a creator1:08:20 What’s next for The Pragmatic Engineer1:09:27 Bunq and Pollen1:13:38 Spotting trends1:14:33 Book updates1:15:20 Favorite books & tech products1:17:13 What won’t change in engineering—The Pragmatic Engineer deepdives relevant for this episode:• State of the software engineering job market in 2026• The impact of AI on software engineers in 2026: key trends. • How 10 tech companies choose the next generation of dev tools • The reality of tech interviews—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
- 4 weeks ago2h 27m
How Kent Beck shapes the software engineering industry
Brought to You By:• Antithesis – verify your system’s correctness without human review or traditional integration tests – and avoid bugs or outages.• turbopuffer – a vector and full-text search engine built on object storage. It’s fast, cheap, and extremely scalable.• WorkOS – everything you need to make your app enterprise ready.—Few have made as big an impact on software engineering as this week’s guest on the Pragmatic Engineer podcast, Kent Beck. He created Extreme Programming, pioneered test-driven development (TDD), co-created JUnit, and is one of the authors of the famous ‘Agile Manifesto’. But these days, he's re-examining many ideas for the age of AI, and says we’re failing to accumulate trust during this new era at the same high rate as new code is being accumulated.In this episode of the Pragmatic Engineer podcast, Kent and I dig into his journey from discovering Smalltalk in the early days of personal computing, to helping define modern software engineering practices. We explore the origins of TDD, design patterns, Extreme Programming, and Agile – along with some lessons learned at Apple and Facebook.Kent explains why he believes software engineering is about far more than writing code, why no one yet knows exactly how engineers should work alongside AI agents, and how his "explore, expand, extract" framework can help engineers navigate major technology shifts.—Timestamps00:00 Intro03:47 Human engineers aren’t going away08:00 Kent's path into tech13:50 Undergraduate and graduate studies17:21 Kent’s first programming job18:54 The rise and fall of Smalltalk27:04 Working with Ward Cunningham37:36 Design patterns44:05 Working at Apple51:08 CRC Cards59:29 Testing tools in the language1:04:22 The C3 project with Martin Fowler1:09:54 Extreme Programming1:16:25 Developing TDD1:25:07 Writing the Agile Manifesto1:30:00 Agile’s impact1:32:40 Agile’s downside1:37:32 The Dotcom Bust1:44:30 Lessons from working at Facebook1:59:44 Kent’s ‘Good to Great’ program at Facebook2:06:07 Soft skills engineers need to learn2:09:30 AI and the challenges of acceleration2:15:53 Explore, expand, extract2:22:33 What Kent is excited about—The Pragmatic Engineer deepdives relevant for this episode:• Measuring developer productivity? A response to McKinsey – co-written with Kent Beck• TDD, AI agents and coding with Kent Beck• Paying down tech debt• The past and future of modern backend practices—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
- Jun 24, 20261h 29m
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.—Timestamps00:00 Intro02:57 Neet’s take on coding interviews06:41 Getting into tech08:56 Why Neet isn't a fan of the CAP theorem13:12 Quitting Amazon after two months18:22 Google vs Amazon22:26 The origins of NeetCode25:27 Leaving Google to go all in on NeetCode32:02 Why Neet doesn't fix every bug39:26 The value of coding interview prep42:57 Systems thinking and domain expertise47:28 Hiring at Big Tech52:15 Tech stack at Neetcode57:57 The NeetCode redesign contest1:01:46 The future of software engineers1:09:04 Hot takes: AGI, AI skill erosion, personality traits1:22:49 “Maybe some people should just give up”1:24:39 How to be a standout engineer1:27:55 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
- Jun 17, 20261h 14m
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.—Timestamps00:00 Intro02:09 Canary deployments at Skype05:01 Joining at Octopus Deploy06:15 Continuous deployment10:26 Why Kubernetes won15:51 Kubernetes on-prem18:50 How GitOps works25:00 The uses and limitations of GitOps31:04 The rise of platform teams35:51 How AI is changing CI/CD39:49 Progressive delivery explained47:31 Rollbacks and roll-forwards50:14 Feature flags54:32 How development environments are evolving57:40 Cloud development environments (CDEs)1:03:45 Self-hosting CI/CD1:09:25 Getting started with progressive delivery1:11:15 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
- Jun 3, 20262h 51m
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.—Timestamps00:00 Intro03:34 Kelsey’s first job at McDonald’s05:04 His non-traditional path into tech11:45 Landing his first tech job with an A+ certification15:33 His entrepreneurial years19:45 Joining Google as a data center technician27:48 Learning automation at a Rackspace spinoff33:26 Moving into financial services50:00 Building a reputation through open source53:55 From configuration management to containers1:08:20 The rise of Kubernetes1:25:05 Why he almost joined NASA instead of Google1:29:20 Defining DevRel at Google1:38:20 Demonstrating impact at Google1:41:20 Microsoft's offer1:55:20 Learning how to slow down2:06:39 Advising and investing2:15:03 A people-first view of GenAI2:24:27 Using AI with guardrails2:28:26 Matching AI to the task2:36:06 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
- May 27, 20261h 20m
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.—Timestamps00:00 Intro07:03 Dax’s path into tech09:04 Early startup experience13:16 Getting involved with open source16:13 OpenCode23:17 Anthropic banning OpenCode30:34 From terminal to GUI32:34 OpenCode’s business model36:33 Why inference is profitable39:11 GPU bottlenecks40:54 AI hype45:50 AI spending48:47 Dax’s memo55:41 Dax’s skepticism of predictions58:58 Engineering culture at OpenCode1:02:38 How building works at OpenCode1:05:36 Taste and quality1:11:32 Dax’s work setup1:12:35 The role of engineers and EMs1:15:50 Advice for engineers1:18:12 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
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About 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.
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