The Pragmatic Engineer

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.
—
Timestamps
00:00 Intro
03:21 The Crossover Project
10:26 What software engineering does better
14:19 What traditional engineering does better
17:06 Formal methods
28:21 TLA+: what it is and demo
35:47 TLA+ at Amazon
36:59 Ways distributed systems break
39:52 Formal methods and systems thinking
45:09 The value of learning math
49:12 What TLA+ is good for and isn’t
51:39 Alloy: a declarative language for software modeling
57:42 Other formal methods tools
1:00:13 Property-based testing
1:04:20 AI and the need for formal verification
1:11:18 Logic for programmers
1:13:24 Hillel’s 2025 prediction on AI’s impact
1:20:19 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

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.
—
Timestamps
00:00 Intro
03:35 Dex’s path into tech
05:36 Early work in platform engineering
07:30 Replicated
13:26 Metalytics
14:38 12-factor agents
20:29 Context engineering
25:40 Harness engineering
28:13 Context overload
32:47 Loop engineering
46:36 Software factories before and after AI
52:35 Automation limits
57:20 Three options for automating
1:01:02 RPI framework
1:06:18 Intentional compaction
1:13:50 Token harder vs. token smarter
1:18:46 AI slop
1:21:17 HumanLayer
1:31:11 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

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!
—
Timestamps
00:00 Intro
01:56 From Uber to writing
09:22 AI-native SDLC
14:00 AI and hiring
19:06 Engineers currently thriving
22:18 Junior roles
24:44 Meta’s war mode
27:54 AI at Big Tech vs. startups
36:46 Tech debt
41:36 Types of engineering managers
44:40 Measuring AI productivity
48:30 The value of CS degrees
50:53 AI at Pragmatic Engineer
56:09 Future-proofing your career
1:01:36 The EU job market
1:03:55 Making money as a creator
1:08:20 What’s next for The Pragmatic Engineer
1:09:27 Bunq and Pollen
1:13:38 Spotting trends
1:14:33 Book updates
1:15:20 Favorite books & tech products
1:17:13 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

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.
—
Timestamps
00:00 Intro
03:47 Human engineers aren’t going away
08:00 Kent's path into tech
13:50 Undergraduate and graduate studies
17:21 Kent’s first programming job
18:54 The rise and fall of Smalltalk
27:04 Working with Ward Cunningham
37:36 Design patterns
44:05 Working at Apple
51:08 CRC Cards
59:29 Testing tools in the language
1:04:22 The C3 project with Martin Fowler
1:09:54 Extreme Programming
1:16:25 Developing TDD
1:25:07 Writing the Agile Manifesto
1:30:00 Agile’s impact
1:32:40 Agile’s downside
1:37:32 The Dotcom Bust
1:44:30 Lessons from working at Facebook
1:59:44 Kent’s ‘Good to Great’ program at Facebook
2:06:07 Soft skills engineers need to learn
2:09:30 AI and the challenges of acceleration
2:15:53 Explore, expand, extract
2:22:33 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

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