The Pragmatic Engineer – Podcastlijstje

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

Afleveringen

The revised rules of engineering management with Will Larson

21 oktober 2026 · 1 uur 56 min
Afspelen

Brought to You By: Lees meer

• turbopuffer – a vector and full-text search engine built on object storage. It’s fast, cheap, and extremely scalable.

• Entire – Git hosting, rebuilt for the agentic era. Every agent session, prompt and tool calls: stored in your repo.

• Antithesis – verify your system’s correctness without human review or traditional integration tests – and avoid bugs or outages.

—

What’s changed in “the unwritten rules” of engineering management since the 2010s, what drove the shift to today, and what has it done to the engineer-to-CTO career path? Today’s guest is one of the best people I know who can tackle these questions.

Will Larson is CTO of Imprint, was an engineering executive for 10+ years, and is the author of several popular books on engineering leadership, including ‘The Engineering Executive's Primer,’ ‘Staff Engineer, An Elegant Puzzle,’ and ‘Crafting Engineering Strategy.’ Previously, he was also CTO at Carta and Calm, and an engineering leader at Stripe and Uber.

In this episode, we explore how engineering leadership has evolved from management practices shaped in the long post-financial-crisis ZIRP era to the altered expectations of engineers and managers today.

Is middle management an increasingly precarious career path, and might managers need to reskill and return to hands-on technical work – or even consider retirement? Will makes the case, and we hear why the traditional path to engineering executive roles is changing, as well as why taking one step backward might sometimes be the best way forward.

We discuss Will's early career, and get his first-hand account of Digg's disastrous relaunch, his own path to CTO, and he tells us why career ladders still matter. We also explore how AI is changing engineering roles and bringing technical decision-making back to leadership.

Timestamps

00:00 Intro

08:20 Stories from Yahoo!

12:47 Digg’s v4 rewrite: the insider story

26:02 Will’s path to eng leadership

30:03 Uber, Stripe, Carta, a…
Uber’s AI infra, from the inside

14 oktober 2026 · 1 uur 33 min
Afspelen

Brought to You By: Lees meer

• turbopuffer – a vector and full-text search engine built on object storage. It’s fast, cheap, and extremely scalable

• Linear – the product development system for teams and agents

• WorkOS – everything you need to make your app enterprise-ready.

—

What do developer tools look like inside of Uber, today? They are very different from what you would see at most places. For example, can you guess what service a system called DevPods, Code Inbox, Slate or Wisdom would be providing to engineers?

Today’s episode is a deepdive into the day-to-day tools of devs at Uber, our tour guide being on of Uber’s longest-tenured engineers: Uday Kiran Medisetty. Uday is one of the few Distinguished Engineers at the company, and leads much of the work on agentic AI, today.

With Uday, we talk through how Uber’s developer infrastructure prepared it for AI agents. We look at the systems Uber built before generative AI and the new tools that connect agents to its code, internal services, and engineering knowledge. Uday explains how engineers use background agents, why tools like Slate make development (and bugfixing!) more efficient, and how code review is changing. We also cover Uber’s approach to token costs and how it measures productivity as the engineer’s role changes.

Timestamps

00:00 Intro

02:48 Uday’s early days at Uber

05:40 Uber’s move to microservices

07:55 Uber’s engineering team, then and now

09:05 Developer tooling before AI

16:03 DevPods

19:28 Building for AI agents

29:27 MCP gateway

34:37 Agent Skills repo

38:46 The context graph and Cortana

47:54 PRD and ERD tool

50:45 Minion

54:46 Testing and code review with Bazel, Slate, and Capri

1:12:26 Edge Gateway, Shepherd, and Wisdom

1:21:33 The changing role of engineer and measuring productivity

1:30:40 Uday’s favorite new products

—

The Pragmatic Engineer deepdives relevant for this episode:

• How Uber uses AI for development: inside look

• Scaling Uber with Thuan Pham (Uber's fi…
Building resilient systems with Sam Newman

7 oktober 2026 · 1 uur 58 min
Afspelen

Brought to You By: Lees meer

• turbopuffer – a vector and full-text search engine built on object storage. It’s fast, cheap, and extremely scalable.

• Entire – Git hosting, rebuilt for the agentic era. Every agent session, prompt and tool calls: stored in your repo.

• Antithesis – verify your system’s correctness without human review or traditional integration tests – and avoid bugs or outages.

—

Sam Newman wrote one of the most-read books about microservices (“Building Microservices”), but he calls them an architecture of “last resort.”

In this episode of the Pragmatic Engineer podcast, Sam explains his thinking on this, and he’s certainly well placed to do so; he was in the room when the term “microservices” was coined. We discuss what teams get wrong when adopting microservices, why independent deployment matters, and how microservices can help teams work more autonomously.

We also delve into his new book, ‘Building Resilient Distributed Systems’, and Sam explains his three rules for distributed systems, why observability is essential, and also why it’s vital to take business context into account when deciding whether to fail open or fail closed on errors.

We also explore how AI is changing software development, from specs versus code as a source of truth to cognitive debt and cognitive surrender. Sam shares how modular architecture can help teams experiment with AI while maintaining understanding of the systems being built.

Timestamps

00:00 Intro

03:16 Sam’s path into tech

09:32 Thoughtworks

20:55 The rise of microservices

33:37 Are specs becoming more important than code?

45:22 Building Resilient Distributed Systems (Sam’s new book)

52:35 Three rules of distributed systems

56:16 Observability

1:02:20 Resilience tradeoffs

1:07:54 Idempotency

1:15:58 Thundering herds

1:21:03 Business context and resilience decisions

1:25:51 Resilience engineering: four concepts

1:32:42 AI and resilience

1:36:26 AI’s limitations and where to use it

1:40:06 Cognitiv…
Distributed databases with Peter Mattis

30 september 2026 · 1 uur 42 min
Afspelen

Brought to You By: Lees meer

• turbopuffer – a vector and full-text search engine built on object storage. It’s fast, cheap, and extremely scalable

• Linear – the product development system for teams and agents

• WorkOS – everything you need to make your app enterprise ready.

—

How is it that a software veteran who regularly shipped ~100K of database-grade code to production each year, pre-AI, feels like he’s even more productive today, with no drop in quality? Peter Mattis is co-founder and CTO of Cockroach Labs, and an original creator of GIMP. He also worked on Gmail and distributed storage at Google.

In this episode, Peter reflects on his journey from open source to Google to founding a database company, and we explore how to keep systems fast, reliable, and correct at scale, from Gmail’s early storage challenges to the tradeoffs in building distributed databases.

Peter tells us how AI has brought him back to writing code after his work shifted toward management, and why he believes AI can improve quality and multiply the impact of domain experts. We also consider the future of code review, and Peter has some advice about how to level up our engineering skills.

Timestamps

00:00 Intro

02:42 Peter’s path into tech

04:00 Building GIMP

09:30 Working on Gmail at Google

14:51 Google’s infra: google3, build files, Bazel, and Colossus

21:30 Distributed storage bottlenecks

23:59 Latency, throughput, and availability

30:04 Contributing to libraries

41:52 Google Spanner

46:10 CockroachDB

52:00 Manual vs. automatic sharding

55:28 Consistency models and strong consistency

1:00:03 Raft consensus

1:06:15 How AI brought Peter back to coding

1:19:12 Peter’s tools and agentic workflows

1:23:08 How AI can improve quality

1:26:39 Code reviews: are they done?

1:29:17 100x engineers

1:35:33 Peter’s advice for leveling up your engineering skills

—

The Pragmatic Engineer deepdives relevant for this episode:

• Inside Google’s Engineering Culture

• Resiliency in dis…
Design Engineering with Maggie Appleton

23 september 2026 · 1 uur 27 min
Afspelen

Brought to You By: Lees meer

• turbopuffer – a vector and full-text search engine built on object storage. It’s fast, cheap, and extremely scalable.

• O'Reilly Early Release: Scaling AI Adoption in Engineering – a free book on how to adopt and scale AI in a pragmatic way inside of engineering orgs. Complimentary, thanks to Antithesis.

• Entire – every agent prompt, tool call, stored in your repo, and mirrored.

—

What can everyone else learn from designers and design engineers? As it turns out, there’s plenty, as I discovered when one of the best design engineers in the industry, Maggie Appleton, came onto the Pragmatic Engineer Podcast. She’s a staff research engineer at GitHub Next, where she builds prototypes to explore how software engineers might collaborate with AI in new ways. Maggie is at the intersection of design, anthropology, and web development, and was the first designer hired by AI startup Elicit, and Lead Design engineer at AI startup, Normally.

Today’s episode is more visual than usual because Maggie brought her notebook along, so there are peeks inside its pages of prototypes and more:

We got into designers’ work and how their design processes are adapting to and changing with AI. We explore why Maggie starts projects with pens and notebooks, what distinguishes design engineers from other designers, and why understanding engineering constraints leads to better collaboration with engineers.

We also discuss how Maggie uses jigs to gain more control over AI agents, why human judgment and style still matter when models can generate designs, and how inconsistent AI capabilities can mislead us.

Timestamps

00:00 Intro

03:24 From anthropology to tech

10:18 What does a designer do?

18:23 How Maggie works

24:55 The case for planning with physical tools

31:53 Why Maggie is learning woodworking

33:13 Design engineers and engineering constraints

38:49 How Maggie uses Figma

40:30 Design at GitHub Next

45:12 How has AI changed design

50:37 When models d…
AI Skills with Matt Pocock

17 september 2026 · 1 uur 36 min
Afspelen

Brought to You By: Lees meer

• turbopuffer – a vector and full-text search engine built on object storage. It’s fast, cheap, and extremely scalable

• Linear – the product development system for teams and agents

• WorkOS – everything you need to make your app enterprise ready.

—

Why is the “grill-me” skill so popular, and why does its creator swear by the importance of software fundamentals? Matt Pocock created this widely-used skill – and many others – alongside being an educator, content creator, and engineer. His latest course is AI Hero, and he previously created the Total TypeScript course that generated more than $2.5 million in sales.

In this episode, Matt and I discuss his unconventional path from working as a voice teacher to becoming a developer and going all-in on technical education. He reveals how communication skills helped him break into tech, why he took an unusual three-days-a-week contract at Vercel, and how he built Total TypeScript through workshops, courses, and a lot of free content.

We also explore “strategic coding,” and how he uses skills like “grill me” and “wayfinder” to plan, delegate, and course-correct with AI agents. Matt explains his “day shift” and “night shift” approach, why splitting context up can keep agents in their “smart zone,” and how concepts from classic software engineering books can guide agents to do better. In this episode, there’s also local versus cloud workflows, whether agents need TDD, how AI is changing the ways that engineers learn the fundamentals, and why humans are still essential in teaching.

Timestamps

00:00 Intro

05:48 How Matt got into tech

10:14 How Matt got into open source

12:58 Joining Vercel

18:39 Total TypeScript

23:21 AI’s impact on technical education

30:32 Building reusable skills for AI coding agents

40:46 The “smart zone” vs the “dumb zone”

45:02 The wayfinder skill

47:52 Why agents excel at software engineering

50:54 “Leading words”

1:01:10 Learning the fundamentals

1:09:17 Local vs.…
Building Codex with Tibo Sottiaux

9 september 2026 · 1 uur 13 min
Afspelen

Brought to You By: Lees meer

• turbopuffer – a vector and full-text search engine built on object storage. It’s fast, cheap, and extremely scalable

• Antithesis – verify your system’s correctness without human review or traditional integration tests – and avoid bugs or outages.

• Entire – Git hosting, rebuilt for the agentic era. Every agent session, prompt and tool calls: stored in your repo.

—

Tibo Sottiaux is one of the engineers who created Codex, and today, he heads up the Core Products & Platform org at OpenAI which also includes Codex. He’s also one of the most public faces of Codex due to his frequent – and generous – usage reset announcements, like this one yesterday.

In this episode of the Pragmatic Engineer Podcast, Tibo and I discuss how Codex was built and continues to be iterated upon. We explore why the Codex CLI is written in Rust and was released as open source, how the harness and models have evolved, and why Codex supports models from multiple providers.

Tibo also shares details about how the OpenAI team uses Codex throughout the software development lifecycle, including code reviews, maintenance, and system rearchitecture. We look into how AI is lowering the cost of changing code – and some interesting side effects of this – the merger of ChatGPT and Codex, and also how Tibo uses the tools in his own work.

—

Timestamps

00:00 Intro

07:21 Working at Google

12:41 What drew Tibo to OpenAI

15:19 The early days of Codex

18:20 Why Codex was built in Rust

21:15 Why Codex is open source

25:50 Codex plays nice with other models: why?

32:09 How the harness works

36:44 Harness and model improvements

41:19 The SDLC behind Codex

46:39 Code reviews at Codex

52:09 Maintenance and architecture

56:43 How AI tools expand what engineers can do

1:02:30 The Merge: ChatGPT + Codex

1:07:16 How Tibo uses Codex and ChatGPT

1:10:44 Advice for engineers who want to work in AI

—

The Pragmatic Engineer deepdives relevant for this episode:

• How Codex is bui…
Why performant code matters (but gets widely ignored), with Casey Muratori

26 augustus 2026 · 1 uur 53 min
Afspelen

Brought to You By: Lees meer

• 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.

• turbopuffer – a vector and full-text search engine built on object storage. It’s fast, cheap, and extremely scalable.

—

There can be few people around who care about software performance more than today’s pod guest, Casey Muratori. He’s a programmer and videogame developer, founder of Molly Rocket, and creator of Handmade Hero – a long-running series about building a game from scratch. He also evangelizes about performance on his Substack, Computer, Enhance.

We got to know each other about three years ago, first via messages, including this one from Casey:

“Why does the industry zeitgeist place so little emphasis on software performance when there seems to be overwhelming evidence that performance is critical to their bottom line?

Like you, I run a Substack for professional programmers, but I focus exclusively on software performance. Although we are quite large by Substack standards, so a certain subset of programmers must believe performance is important, I nonetheless hear lots of dismissive excuses when I post on social media. This happens so frequently, I devoted an entire article to cataloging the extensive pro-performance evidence we already have from the world's leading software companies: Performance Excuses Debunked.

Strangely, nobody has a rebuttal to why performance is important. When I point people to this, they actually tend to agree. But the prevailing attitude nonetheless stays the same.”

I’m delighted we finally have Casey on the podcast because it’s overdue! In this episode, we discuss why software performance matters, why it’s overlooked, and how developers can get better at writing performant code. We explore why performance should be considered during design, the value of learning to read assembl…
From Chrome DevTools to AI Engineering, with Addy Osmani

19 augustus 2026 · 1 uur 32 min
Afspelen

Brought to You By: Lees meer

• Antithesis – verify your system’s correctness without human review or traditional integration tests – and avoid bugs or outages.

• Google Cloud Run – run your code and host LLMs directly on top of Google’s scalable infrastructure, without having to worry about managing infra.

• Sentry – application monitoring software considered “not bad” by millions of developers

—

Addy Osmani spent more than 14 years at Google, working on Chrome, DevTools, Core Web Vitals, and most recently, AI developer experience.

If you've ever opened Chrome DevTools, or optimized a page for Core Web Vitals, you’ve used software built by Addy Osmani. In this episode, I sit down with Addy and we talk about his path from building a web browser aged just 16 to becoming a director at Google. We discuss what he learned from building tools for millions of developers, Google’s engineering culture, and why he continued doing hands-on coding work as a manager. We also get into how he works with AI agents today, the risks of ‘cognitive surrender,’ his approach to ‘loop engineering,’ and why it’s good to develop skills in product management, go-to-market, and other areas.

—

Timestamps

00:00 Intro

02:50 Addy’s current workflow

05:11 Addy’s path into tech

15:04 Addy’s work on jQuery

16:44 TodoMVC

21:44 Getting hired at Google and working on Chrome

27:17 Building dev tools

40:15 Core Web Vitals

45:42 Google’s engineering culture

51:03 Addy’s career trajectory at Google

57:55 The director role at Google

1:01:40 Cognitive debt and cognitive surrender

1:03:03 Working with agents

1:05:52 Loop engineering

1:12:55 The changing role of the software engineer

1:18:15 How Addy uses AI in writing

1:27:40 What’s next for Addy

1:28:47 Career advice

—

The Pragmatic Engineer deepdives relevant for this episode:

• What is loop engineering?

• Inside Google’s engineering culture

• How AI-assisted coding will change software engineering: hard truths

• Are AI agents actually…
Stop being skeptical about AI for development with Charity Majors

12 augustus 2026 · 1 uur 26 min
Afspelen

Brought to You By: Lees meer

• 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.

• Buildkite – CI software built to absorb whatever your coding agents throw at the build queue

—

In 2025, it was rational to be skeptical about AI, but in 2026 it’s clear that AI is changing all of the industry, and there’s less and less place for skepticism. This take is from one of my favorite voices in software reliability and observability: Charity Majors, CTO and cofounder of Honeycomb, co-author of Observability Engineering. (Note: the second edition of Observability Engineering is out, and it’s pretty much a full rewrite of the book, I recommend grabbing it if you’re building reliable systems)

In this episode, I sat down with Charity to discuss how her thinking on AI has evolved, why she believes it is becoming a foundational part of software engineering, and what that means for how teams build, review, and ship software.

We explore how AI is changing the economics of code generation, why reliability and verification are increasingly the bottlenecks, and why the rise of non-deterministic systems requires more engineering discipline. Charity shares her views on code reviews, observability, DevOps, leadership, and why both AI skeptics and enthusiasts are getting important things right.

—

Timestamps

00:00 Intro

02:56 How Parse led to Honeycomb

06:00 The limits of individual productivity metrics

09:08 How Charity’s perspective on AI has evolved

13:50 Rewriting code vs. editing code

19:20 Production as a stage of development

22:14 Code reviews

26:56 Non-deterministic systems

31:11 Sensible uses of AI

37:41 The two AI camps

44:40 Why AI works so well for building software

49:42 DevOps

55:13 Modern observability

1:00:40 Handling context overload

1:01:56 What’s new in Observability Engineering’s 2nd edition

1:07:45 What effective…

Alle 80 afleveringen →

Vergelijkbare podcasts

De Technoloog | BNR BNR Nieuwsradio Laatste aflevering 5 november 2026
De Grote Tech Show | BNR BNR Nieuwsradio Laatste aflevering 5 november 2026
Machine Gods NPR Laatste aflevering 4 november 2026
De Groene Nerds Aljo Hartgers & Danny Oosterveer // De Podcasters Laatste aflevering 5 november 2026
Bright Podcast Bright B.V. Laatste aflevering 4 november 2026
Understood: The Big Bet CBC Laatste aflevering 26 oktober 2026