Automation, AI, and quality under pressure.
TestGuild Automation Podcast treats testing as a production problem, not a checkbox. Recent episodes move through AI-generated code, mobile automation, production logs, ML pipelines, observability, and the pressure quality teams face when delivery speeds up.
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TestGuild Automation Podcast is built around the practical work of making software releases safer while delivery keeps accelerating. It is technical, direct, and strongly focused on automation. The recent episode run is dominated by AI's effect on testing and quality engineering, but the show does not treat AI as a magic replacement for testers. It keeps asking what changes when code, tests, and product behavior move faster than a team can comfortably validate. That question shows up in discussions of AI coding assistants, rollbacks, late-night firefighting, and the pressure to create more code without losing production stability. The show has a recurring quality-first argument. Speed matters, but the excerpts repeatedly frame durable speed as something that comes from disciplined engineering, review, and better testing practice. Human judgment is central. Guests talk about human-in-the-loop testing, collaboration with AI agents, hallucination risk, customer context, and the limits of one-on-one AI interactions when broader product risk is involved. The show also spends time on mobile automation, where web testing gets more tool attention and mobile teams still wrestle with device coverage, Appium, Flutter, React Native, native Android, and autonomous crawling. Tooling is discussed concretely. QA Pilot, BrowserStack products, production-log mining, BDD-formatted crawler output, and AI-generated regression tests appear as part of the show's working vocabulary. The result is not abstract futurism. It is a stream of conversations about what testers, developers, and quality engineers can actually inspect, automate, review, and improve. Recent episodes also widen the frame beyond QA tooling. SRE, observability, ML pipeline testing, platform quality, global engineering teams, brownfield modernization, unit tests, legacy code, and non-deterministic AI systems all sit inside the show's quality lens. The pacing is energetic. Openings often pose a concrete testing problem before moving into a practitioner conversation. The style can be promotional around community and sponsors, but the core editorial center is clear: quality work is changing because software creation is changing. For PlayNext, the show reads as a specialist feed for people who want to hear how automation, AI, and testing practice are being argued through by people close to the work.
Made for: Suits a listener who works near software quality, test automation, DevOps, SRE, mobile testing, or AI-assisted delivery. It also fits technically curious engineering leaders who want practitioner-level conversations rather than broad software trends.
What sets it apart: The show stands out by treating AI in testing as a delivery-system problem: pipelines, production logs, non-deterministic outputs, human review, and release confidence all stay connected. Its emphasis is less on hype and more on what quality teams can actually do next.
TestGuild Automation Podcast (formally Test Talks) is a weekly podcast hosted by Joe Colantonio, which geeks out on all things software test automation. TestGuild Automation covers news found in the testing space, reviews books about automation, and speaks with some of the thought leaders in the test automation field. We'll aim to interview some of today's most successful and inspiring software engineers, and test automation thought leaders.
Green tests, broken product: Joe Colantonio wants you to ask what the checks missed.
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Short reviews from the PlayNext desk, based on the episodes we processed.
A grounded argument for matching AI-assisted coding speed with testing discipline before failures reach production.
Test Skill Test Talks Automation Podcast takes up a real pressure point for teams using AI coding assistants: faster output can still leave testing, pipelines, and production reliability exposed.
A grounded review of scaling quality, human judgment, and the shifting line between testing and development.
Scaling quality engineering lands here as a matter of judgment before it becomes a matter of tooling. Sunita McCoy, a global engineering leader focused on platform quality, SRE, and observability at Fortune 100 companies, frames large-scale quality transformation around people…
QA Pilot's mobile crawler pitch lands because it keeps editable BDD input and human control in the workflow.
Mobile automation is framed here as testing's overlooked corner, with QA Pilot's mobile-first crawler as the practical lens. Aditya Challa, QA Pilot's co-founder, walks through how it maps an app like a sitemap, handles pop-ups, generates test data, and works against Flutter…
A grounded conversation about keeping human judgment involved when AI makes software easier to produce than to question.
Green tests can still leave a product feeling wrong, and this episode treats solo QA as a matter of judgment, not just coverage. It focuses on the pressure around AI-generated code, where a result that looks convincing can move toward deployment before anyone has really…
A practical, measured look at using production logs for regression tests when system behavior is less predictable.
Production logs carry the episode's central idea: real behavior in production can become useful test material, especially when teams need to trace the sequences behind defects and turn them into regression coverage.
Power Platform news with practical static.
An interview with Nicola Lindgren and Vernon Richards about their new book 'The Software Tester's Journey' and career advancement in software testing.
Joe Colantonio introduces a session with Mike Lyles on how testers can stay relevant by focusing on leadership and expertise in the age of AI.
Eric Minick, co-author of O'Reilly Books' AI Native Software Delivery, says AI coding tools are creating a “velocity paradox” inside DevOps pipelines.
Sunita McCoy, a global engineering leader focused on platform quality, SRE, and observability at Fortune 100 companies, argues that AI and quality transformation only work when leaders create sponsorship, time, and psychological safety.
Aditya Challa says mobile automation is stuck with web-first tooling, real-device requirements, and Appium as the main option, which is why he and Chetanya built QA Pilot.
Christine Pinto, co-founder of Epic TestQuest and creator of Wizzo, talks with TestGuild Automation Podcast about solo tester pressure, AI-generated code, and why “solo QA syndrome” feels like isolation plus imposter syndrome.
Tanvi Mittal discusses using AI to mine production logs for generating smarter regression tests and addressing challenges in testing non-deterministic AI systems.
Adam Sandman of Inflectra tells host Joe Colantonio that AI-assisted coding raises both code volume and risk, since 2 experienced developers can now produce "6x" the functionality.
Selectors Hub founder Sanjay Kumar says testers helped shape the tools he launched after starting the project in June 2020.
On TestGuild Automation Podcast, host Joe asks Dunders founder Kareem Jouini how generative AI could change software testing.
An expert machine learning engineer discusses ML pipeline best practices and testing at scale.
Jim interviews Dalton about a new Swift driver for the Appium framework and UI testing, with a sponsor segment for BrowserStack App Live.
Srirang Srikantha discusses how AI-driven platforms like Tenjin address scalability, maintainability, and complexity challenges in enterprise test automation.