How do you test for bugs that only appear when a user clicks frantically, or when asynchronous data loads in an unexpected order? Standard UI tests often miss the subtle stuff that happens all the time in the stateful, dynamic applications.
In this episode, Paul Ryan and I sit down with Oskar Wickström, creator of the QuickStrom framework, among other things, to explore how to apply generative testing to the complex world of user interfaces.
Oskar argues that you don't need to be a formal methods genius to get real value out of the approach. Even simple properties can uncover deep bugs, like ensuring a loading spinner eventually disappears or that the screen never goes blank.
If you've been intrigued by property-based testing but intimidated by the thought of writing complex formal models for UIs, stick around.
AI coding assistants promise incredible speed, but what happens when you run straight into a wall of buggy code and technical debt?
In this episode, Clare Sudbery, a software engineer with over 25 years of experience, discusses a crucial paradox for modern developers.
The secret to harnessing AI's power isn't to move faster, but to slow down. Clare explains why deliberate, rigorous practices like Test-Driven Development (TDD) are the essential "guardrails" needed to guide AI tools toward reliable, high-quality software. You'll learn why "more, smaller steps" is the key to tackling technical debt and how throwing your code away might be the most productive thing you do all week.
Some bugs are so rare, they can take years to track down and fix. What if you could find and fix five of them per day?
For Joran Dirk Greef, the creator of the TigerBeetle database, that's not a wild dream — it's how his team works every day. While most people think building a new database takes a decade, Joran's team built TigerBeetle in just three and a half years. The key is a unique philosophy for writing software called "Tiger Style".
Joran joins the show to share the secrets behind their speed and safety. You'll hear why he thinks picking C would have been a "fatal" mistake , how a strict rule about memory can force you to write better code , and why Zig was the perfect choice for TigerBeetle.
The key to it all is a powerful testing method that Joran calls "existential" for any important project. If you want to hear more about how his team turns squashing impossible bugs into their normal day-to-day, stay tuned.
When is a bug not really a bug? In this episode, host David Wynn talks with SRE veteran Dan Slimmon about a radical idea: chasing perfect code might not be the best way to make your service reliable.
Dan argues that once your code is "good enough," most outages aren't caused by code defects. They're caused by weird interactions between different parts of a system or by users doing things you would never expect. He shares wild stories from his career, including how a tiny database hiccup created a massive, repeating traffic jam and how a single user crashed servers by uploading a 3.2-gigabyte config file.
This conversation will make you rethink what you thought you knew about bugs, quality, and what "reliability" truly means.
Every map of a complex territory is inherently wrong, but without one, we're completely lost. So what happens when the territory is the vast, ever-changing landscape of distributed systems?
In this episode, David Wynn sits down with Kyle Kingsbury, the renowned researcher behind Jepsen, to discuss a monumental effort to chart this landscape: the new Distributed Systems Reliability Glossary.
Kyle explains why he and T.W. Lim from Antithesis felt the need to "put this all in one place," creating a practical roadmap for testers and engineers navigating the field. They explore the challenge of creating "directionally correct" definitions , the surprising "urban legends" that persist in system design (like yelling at hard drives to increase error rates ), and why even the most rigorous formal models can drift from the code they're meant to describe.
Tune in for a deep dive into the subtle bugs that defy simple explanations , the future of reliability in the age of AI-generated code, and the one problem Kyle is still determined to solve in his own work: reproducibility.
Is it just a fact of life that software is broken? Our industry often operates as if the answer is "yes." We write tests, we fix bugs, but we seem to accept a certain level of failure as the cost of doing business. Our guest today is tired of it.
Isaac Van Doren is a software engineer at Paytient, a healthcare payment solutions provider, and he’s "sick of software being broken all the time". Isaac makes the provocative case for a radical cultural shift in how we approach software reliability. He argues that we need to move beyond the narrow view that reliability simply equals testing and instead adopt practices that force us to be explicit about the rules of our systems.
Listen to explore a different philosophy of development—one where engineers are fully responsible for defining business logic , assertions are a tool for building a "theory of the system" , and failures in production are not just bugs, but immediate, unmissable signals that our understanding was wrong. This conversation will challenge your assumptions and give you a new vocabulary for building software that, as Isaac puts it, "actually works".
How do you prove the correctness of services that underpin a huge portion of the internet? At the scale of Amazon Web Services, traditional testing falls short.
In this episode, Antithesis’ own Will Wilson and Ben Collins talk with Marc Brooker, a Distinguished Engineer who has spent nearly 17 years building core AWS infrastructure like S3, Lambda, and Aurora Serverless. Marc gives us the inside story on AWS's decade-long journey with formal methods, from the early days of using complex tools like TLA+ to the current focus on "lightweight" approaches that any engineering team can adopt.
He shares the counterintuitive lesson learned at AWS: investing in correctness up front doesn't just improve reliability, it actually boosts development velocity and leads to faster delivery. We also explore the convergent evolution of deterministic simulation testing, the challenge of applying these techniques to user interfaces and control planes , and what role AI will play in the future of programming and verification.
The BugBash Podcast kicks off with a bit of pre-history -- the story of FoundationDB, one of the first companies to successfully use deterministic simulation testing to accelerate development, assure reliability, and build something legendary.
Today, FoundationDB is the hidden layer in Snowflake, DeepSeek, and many core systems at places like Apple and Goldman Sachs. But it started with some guys in a garage, building a system demo with plywood and lightbulbs...
