Webinar 9: The Journey to Becoming a Test Superhero (Eggplant.AI, Testers.ai)

The conversation frequently mentions various AI-driven testing solutions. several tools and approaches were discussed

• Checki / http://Testers.ai AI-based testing approach mentioned as an example.

• Eggplant AI (KeySight) Discussed as a visual automation tool with AI capabilities.

• Cursor, DevN, Codeium, Anthropic, OpenAI – Mentioned as broader AI and code-generation platforms relevant to testing.

Objective of the Webinar

This webinar aimed to explore how Generative AI and Agentic AI are reshaping the software testing landscape. The main focus was on:

• Transitioning from manual or traditional automation to AI-first approaches.

• Understanding the new roles and opportunities for testers in an AI-driven future.

• Highlighting the practical steps testers can take now to prepare for the shift.

Presenters

• Jonathan Discussed enterprise-grade AI solutions, large action models (LAM), and the shift toward agentic AI.

• Jason Shared experiences with AI-driven test automation (e.g., Checki / http://Testers.ai ), including how AI can autonomously generate tests.

• Joe (Host) Moderated the session, asked clarifying questions, and guided the conversation.

Brief Summary of the Webinar

Overview of Agentic AI The panel explained that AI is evolving from simple code generation to agentic systems capable of autonomously performing tasks like running tests, identifying bugs, and even adapting to new UIs.

• Implications for Testers

  • Many current testing practices (e.g., writing Selenium scripts) may become obsolete.

  • Skilled testers will shift to critical thinking, domain expertise, and oversight of AI agents.

• Real-World Examples:

  • Anthropic’s “Computer Use” feature demonstrates how AI can control the desktop environment.

  • Tools like Eggplant AI and Checki/Testers.ai highlight end-to-end testing with minimal human intervention in coding.

Features and Technical Aspects

• Agentic AI / Large Action Models (LAMs)

  • AI that not only generates code but also executes and adapts to tasks without explicit user prompts.

  • Potential to control desktop apps, web apps, and entire workflows.

• Self-Healing / Automatic Maintenance

  • AI can autonomously update tests when UIs or features change.

• Visual vs. DOM-based Testing

  • Tools like Eggplant AI use image recognition; other frameworks rely on DOM selectors.

  • AI can unify these approaches, reducing reliance on brittle locators.

• Data Privacy and Infrastructure

  • Enterprises may need on-prem or private cloud solutions for compliance (e.g., EU AI Act).

• Developer-Driven vs. Tester-Driven AI

  • Developers are increasingly using AI to generate and test code quickly.

  • Testers must leverage AI to avoid being outpaced by Dev-oriented solutions.

Future Job Specifications

• AI Test Wranglers / Overseers Manage AI-driven testing processes, interpret complex results, ensure compliance.

• Subject Matter Experts (SMEs) Provide domain insight and critical thinking to validate AI findings.

• Multi-Disciplinary Collaboration Testers will collaborate closely with Dev, Ops, and Security, all using AI tools.

How GoTestPro Can Compete

Given the emerging dominance of AI-first testing, GoTestPro can

• Offer AI-Driven Test Generation and Maintenance

  • Implement generative AI to reduce scripting and maintain tests autonomously.

• Provide Agentic Workflows

  • Develop or integrate with agentic AI frameworks, enabling end-to-end automation across platforms.

• Prioritize Enterprise-Grade Security

  • Offer on-prem or private cloud solutions to address compliance and data privacy.

• Integrate Domain Expertise

  • Focus on user-friendly dashboards, allowing SMEs to guide AI without heavy coding.