Fireside Chat with Revathi Chanda Syren

Hello Testers,

A fireside chat is an opportunity for open and honest dialogue. Also, the unique format that allows for gaining insight into the experiences of industry experts, and finding inspiration, by posing candid questions.

We’ve brought "Fireside Chat with Revathi Chanda Syren" for all of you!

Date: 30th March 2026

Time: 8 PM - 9 PM IST

A special thank you and huge shoutout to BrowserStack, our exclusive sponsor for all community events and premier sponsor for conferences.

Session Title: Beyond Autocomplete: AI Agents as Teammates in Quality Engineering

Most teams today still use AI in testing as an advanced autocomplete tool—helping write test scripts, suggest locators, or generate basic test cases. But this is only scratching the surface. The real shift in quality engineering comes when AI moves from being a passive assistant to an active testing agent. Instead of just supporting individual tasks, AI agents can take ownership of end-to-end testing activities—analyzing requirements, identifying test coverage gaps, generating and maintaining test suites, executing tests across environments, and continuously learning from defects and production data.

In this Fireside Chat, we will explore how AI agents can act as true teammates in testing, working alongside QA engineers to improve speed, coverage, and reliability. We will discuss practical use cases such as self-healing automation, risk-based test generation, intelligent regression selection, and autonomous defect analysis. More importantly, we will challenge the traditional role of QA—shifting from script creators to quality strategists who guide, supervise, and collaborate with AI. The conversation will focus on what it really takes to adopt AI in testing beyond hype—covering mindset shifts, tooling, and real-world implementation challenges.

Key Takeaways:

1. AI agents can own testing workflows, not just tasks - They can autonomously analyze requirements, generate test scenarios, execute tests, and adapt based on results—reducing manual handoffs.
2. Continuous learning improves test quality over time - AI agents learn from defects, production issues, and past executions to refine test coverage and prioritize high-risk areas.
3. Dynamic and self-healing automation becomes the default - Agents can detect UI/API changes, update scripts, and maintain stability without constant human intervention.
4. Human + AI collaboration is critical for trust and control - QA engineers define strategy, validate outcomes, and guide agents—ensuring testing remains aligned with business risk and quality goals.

About Speaker: Revathi Chanda Syren

Revathi Chanda Syren is a Quality Leader with deep expertise in software quality engineering, test automation, and digital transformation. With over 20 years of experience in software engineering, she has built her career across multiple roles — starting as a programmer, then moving into business analysis, and ultimately leading global Quality Assurance and Quality Engineering teams. This diverse background gives her a unique end-to-end understanding of what it truly takes to deliver high-quality, reliable software in complex technology environments.

Throughout her career, Revathi has helped organizations build scalable quality practices, successfully implement test automation strategies, and transform traditional QA teams into modern quality engineering organizations. Her experience across development, business analysis, and quality leadership allows her to bridge the gap between technology, product thinking, and business outcomes.

She is passionate about shaping the future role of QA professionals in the AI era — shifting from traditional testing to strategic quality leadership, where testers influence architecture decisions, risk management, and business impact. Revathi actively advocates for building strong quality cultures, leveraging AI in testing, and enabling teams to deliver reliable software faster and with greater confidence.

Currently, Revathi works in one of the world’s leading logistics companies, where she leads QA initiatives and helps teams navigate the evolving landscape of AI-driven software development and quality engineering."

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