TestGuild Automation Podcast

Nandini Srinivasan has spent 25 years in the quality industry and leads a global QA organization of over 150 engineers across the US, Canada, India, and Pakistan.
In this episode, she breaks down exactly how she built a QA AI acceleration charter, ran a train-the-trainer model, and used a phased proof-of-concept approach to separate real AI from what she calls "powerful automation dressed up as AI. 
We get into:
How she frames quality metrics for executives
Using language around revenue protection
Risk mitigation
Feature velocity instead of test coverage percentages.
She talks about the four pillars she uses to present her team's value: quality, scalability, performance, and availability.
Nandini also shares her take on the future of QA hiring, why the judgment layer will always require a human, and what skills testers need to stay relevant as AI agents take over the more mechanical parts of automation.
She is also writing a five-part LinkedIn series called "The Voice of QA in the AI Era" if you want to follow along.

Matt Wynne, co-creator of Cucumber and BDD practitioner, joins Joe for the first time in over a decade to talk about what two years inside a Silicon Valley AI startup taught him about the future of software testing.
Matt spent time at Mechanical Orchard working alongside experienced XP practitioners to modernize legacy COBOL mainframes using LLMs, and then spent a week with the team that coined the term "software factory," where the rule was simple: humans never write the code, never read the code.
In this episode, Matt breaks down what harness engineering actually means, why shared understanding is still the real bottleneck even in an agentic world, and how testers can use multiple LLMs to review AI-generated pull requests without reading every line.
He also gets honest about the grief that comes with realizing you can encode years of hard-won expertise into a Markdown file, and why that does not mean your skills are worthless.
If you are working in a brownfield codebase, wondering how to handle the flood of agentic PRs, or trying to figure out where testers fit in a world where agents write the code, this conversation is worth your time.
Find Matt at:
mattwynne.net
leansoftware.ai
Also check out his course:
Build a Software Factory: Hands-off agentic coding for experienced engineers
https://testgld.link/mattcourse

Amit Rawat is an agentic engineer who spent two decades in QA before shifting fully into building AI agents. He's the creator of PromptWright, a desktop tool that turns natural language prompts into automated Playwright browser tests, complete with screen recording, Gherkin scenario generation, and self-healing locators.
In this episode, Amit and Joe get into what it actually takes to work with AI agents at a high level, starting with why the planning phase matters more than the prompt itself. Amit breaks down his own workflow, brainstorming with AI, building a detailed plan in HTML before ever executing, and why curiosity and technical depth still matter even as AI gets more capable.
They also cover why Amit believes QA professionals, more than developers or DevOps engineers, are best positioned to thrive in the agentic era, how he tracks the ROI on his $200-a-month Claude subscription, the "Chief of Staff," "Chief Health Officer," and "Chief Financial Officer" AI agents he's built to help manage different aspects of his personal life, and how he uses a memory layer so those agents understand his preferences and become more useful over time.
If you're a tester, automation engineer, or QA leader trying to figure out where AI agents fit into your workflow and your career, this conversation is a practical look at what's already working today.

Most API testing stops at the happy path. The problem is that the bugs that actually hurt you in production are sitting in everything many testers skip, like the boundary values, the oversized payloads, the missing tokens, the security headers, the inputs that make no sense at all.
In this episode, Joe sits down with Liudas Jankauskas, who has spent almost twenty years breaking software and testing APIs since 2008.
Liudas demonstrates Rentgen, his free and open-source API testing tool, live on screen. You'll watch him take a single request from a real app, map it in seconds, and generate dozens of tests covering security, boundaries, performance, and load—all from one click.
You'll learn:
How to discover APIs hiding under the hood of any application, even when there is zero documentation
Why happy path testing leaves you exposed
How to run a fast hygiene check before your real automation ever starts
Liudas also explains why Rentgen runs completely locally with no server and no data leaving your machine, making it safe for banking, healthcare, and other regulated environments.
Plus, he demonstrates the killer Copy Bug Report feature that drops a standards-based ticket straight into Jira or Trello.
In This Episode You'll Discover
How to find and test undocumented internal APIs using the browser DevTools Network tab
Why happy path-only testing misses the bugs that matter most
How Rentgen turns one request into security, boundary, performance, and load tests automatically
Where Rentgen fits in your workflow as a pre-automation hygiene layer—not a Postman replacement
How to use it for regression by comparing results across environments
The one piece of advice Liudas gives every tester to level up their API testing
Try Rentgen, free and open source, at Rentgen.io.
Connect with Liudas Jankauskas on LinkedIn:
https://www.linkedin.com/in/liudas-jankauskas/

Your AI code review tools read the diff. They stare at your code. But they never actually run it. So the bugs that only show up at runtime, the broken user flows, the bad query plan, the duplicate submission, sail right past review and land in front of your customers.
In this episode, Joe Colantonio sits down with Evan Marshall, founder of Ito and a fifteen year engineer who spent five years in applied cryptography securing hundreds of millions of dollars for millions of people. Evan is taking that ship fast without breaking things discipline and pointing it straight at testing.
Ito is an agentic QA platform that builds and runs your actual app on every pull request, navigates it like a real user, exercises the frontend and backend as one system, and brings back real runtime evidence: video replays, logs, the exact lines responsible, and steps to reproduce, posted right in your PR.
You will learn:
Why static code review misses the bugs that cause real production incidents
How Ito spins up ephemeral environments and tests across UI, API, and database
Why QA is not disappearing, it is leveling up into a manager and quality strategist role
How to keep your test layer separate from your code generation so your signal stays honest
The skills testers and engineers need as AI writes more of the code
If you are shipping AI generated code at high velocity and your QA cannot keep up, this one is for you.
Try Ito on your own code. Your first ten pull requests are reviewed free, no credit card required. Check it out at https://testgld.link/itoai now.
And as Joe always says, seeing is believing.