The BugBash Podcast

The BugBash podcast is a lively look at all aspects of software reliability, by enthusiasts, for everyone.Each episode brings leading engineers and researchers together for deep dives on everything from formal methods to testing to observability to human factors. There’s concrete advice on best practices, and nuanced discussion of how these strategies combine to deliver software that works.And if you’re enjoying these conversations, check out the talks from BugBash 2025 on YouTube, and join us at BugBash 2026 on April 23-24, 2026, in Washington DC!

The BugBash Podcast is a technology podcast hosted by Antithesis, with 21 episodes on record and a Required Pod Score of 80. PitchCentric scores this show on Booking Probability, Listen Score, and live audience signals refreshed every 24 hours.

Antithesis hosts The BugBash Podcast, a technology show with 21 episodes published.

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  Episode #1

  A Wild Hypothesis: The Python Library that Kills PhDs

  Aug 12, 20261h 2mS3

  What happens when your open source library changes millions of lives? In this episode, we sit down with David MacIver, Zac Hatfield-Dodds, and Liam DeVoe — three generations of maintainers of Hypothesis, the property-based testing library used by roughly 5% of all Python developers. It’s by orders of magnitude the most-widely used property-based testing tool in the world. Hypothesis has introduced millions of developers to property-based testing, and made instant converts out of many others. All three maintainers quit their PhDs to work on Hypothesis, and today they talk about just why they did that, how pull requests lead to lifelong friendships, and about the factors that led to Hypothesis’ success.

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  The BugBash Podcast

  Dev in the Street

  Aug 5, 202635 min

  In this episode of the Bug Bash podcast, host David Wynn shares a collection of conversations recorded at Bug Bash 2026. 11 developers share their war stories about the most interesting bugs they've encountered and resolved. They talk about JDK issues on ARM architecture, kernel hangs related to NFS and half-duplex Ethernet, memory fences in Spark workloads, and complex logic bugs in iMessage. Together these conversations become a picture of what reliability-focused developers are thinking about today: the importance of formal verification, the rise of property-based testing, and how the only thing that makes systems work is our effort and care.

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  Episode #8

  Why simple workloads find the hardest bugs

  Apr 8, 202658 minS2

  You hit 100% test coverage, deploy to production, and the system still falls over. An old story, maybe aside from the 100% coverage percent part. In this episode, David sits down with Marco Primi and Sean Allen from the Antithesis Red Team to talk about a likely missing piece in your testing strategy: workloads. They break down exactly what workloads are, why they are so helpful for testing distributed systems, and the biggest pitfalls engineers hit when trying them out. They talk about why you have to let go of deterministic, "happy path" testing, and how even a workload as "dumb" as a basic `while true` loop can expose silent data loss that your unit tests would never catch.

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  Episode #7

  Programming as an Act of Building Vocabulary

  Apr 2, 202649 minS2

  Why do LLMs struggle to build complex architecture? According to Unmesh Joshi, Distinguished Engineer at ThoughtWorks, it often comes down to a lack of shared abstractions, of a shared vocabulary. Today he joins Will Wilson and David Wynn to unpack how we learn about, build, and test distributed systems. We cover the value of building miniature versions of systems like Kafka to grasp the basics, why Deterministic Simulation Testing (DST) is a highly effective tool for teaching as well as finding bugs , and why Guy Steele's 1998 keynote holds the secret to successfully collaborating with modern AI tools.

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  Episode #6

  The Dollar Bet that Fuzzed Figma: Exploding Laptops and UI Reliability with Jonathan Chan

  Mar 25, 202651 minS2

  Can you stress-test a React UI completely hands-free? In this episode, Oskar Wickström and I are joined by Jonathan Chan to discuss the origins of Fuzzmap. From a janitor’s closet in Figma—where end-to-end tests once lived on a "spicy pillow" MacBook—Jonathan shares how he applied coverage-guided fuzzing (inspired by AFL) to the world of web front-ends. We dive into the gnarly hacks required to instrument React, the challenges of visualizing complex state machines, and the future of "full-stack" fuzzing in the age of LLMs and team agents.

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