AI test automation is evolving fast — but most tools still generate brittle code that breaks with every UI change.

See it for yourself now: https://links.testguild.com/Thunders

In this episode of the TestGuild Podcast, Joe Colantonio sits down with Karim Jouini, founder of Thunders, to explore a radically different approach to AI testing: executing test automation in plain English without generating Selenium or Playwright code.

Instead of "auto-healing selectors," Thunders interprets natural language directly — allowing teams to:

• Ship twice as fast
• Achieve 10x test coverage with the same resources
• Reduce regression cycles from weeks to days
• Eliminate massive automation maintenance overhead

Karim shares real-world case studies, including:

• A European bank that reduced a 3-year core banking upgrade testing effort to 4 months
• A SaaS company that transitioned from a traditional QA team to AI-assisted product-led testing

We also discuss:

• Whether AI test agents replace QA roles
• How QA managers must shift from individual contributors to AI managers
• The risks of adopting AI without a defined success metric
• The future of shift-left testing in the AI era

If you're a software tester, automation engineer, QA lead, or DevOps leader trying to understand what's hype versus real ROI in AI testing — this episode breaks it down.

Try it for yourself and see how AI testing fits into your pipeline.

Get personal demo: https://links.testguild.com/Thunders

Is traditional performance testing becoming obsolete?

In this episode, performance engineering expert Akash Thakur shares why AI is fundamentally transforming load testing, scripting, observability, and shift-left strategies.

With 17 years of real-world enterprise experience, Akash explains how AI-augmented tools are already reducing scripting time by 30%, improving analysis speed, and helping teams move from reactive performance testing to predictive intelligence.

You'll learn:

• How AI is accelerating performance scripting and analysis
• Why shift-left performance testing is finally becoming realistic
• The role of structured data in predictive QA models
• How to test AI applications (LLMs, GPUs, inference throughput) differently than traditional web apps
• What the future role of performance engineers looks like — architect, not script writer

If you're a performance tester, SRE, QA leader, or DevOps engineer wondering how AI will impact your role — this episode gives you practical, actionable insights you can apply immediately.

Most teams find defects after the damage is done — during regression, late-stage testing, or production incidents. That's expensive, stressful, and completely avoidable.

Try Spec2Test AI now: https://testguild.me/spec2testdemo

In this episode, Joe Colantonio sits down with Missy Trumpler, CEO of AgileAILabs, to explore how Spec2TestAI helps teams prevent defects before code ships by applying AI directly to requirements.

You'll learn:

• Why traditional test automation still misses critical risk
• How predictive, requirements-based AI testing works in practice
• What "shift-left" actually looks like beyond the buzzword
• How to reduce escaped defects without writing more tests
• Why secure, explainable AI matters for QA and enterprise teams

This conversation is especially valuable for software testers, automation engineers, and QA leaders who want earlier visibility into risk, faster feedback, and higher confidence releases.

Don't miss Automation Guild 2026 - Register Now: https://testguild.me/podag26