Kiran Susarla

I spent much of my career building, transforming, and leading quality engineering organizations - from global testing practices and enterprise QA transformations to the AI-enabled quality products I work on today.

My work has taken me across quality strategy, test automation, DevSecOps, SDLC governance, operating models, metrics, release readiness, vendor ecosystems, and large-scale delivery transformation. I built global QA and quality engineering practices, worked with enterprise clients across industries, and helped teams move from testing as a late-stage activity toward quality as an engineering discipline embedded throughout delivery.

Today, I am especially interested in how AI changes both software development and software quality. That includes AI-assisted requirements improvement, test generation and maintenance, evaluation of AI-enabled systems, human-in-the-loop controls, traceability, agentic development, responsible AI, and the practical question of where deterministic engineering is still the better answer than another model call.

I am also interested in the economics and operating realities behind AI adoption: what actually improves engineering productivity, what creates measurable value, what merely shifts cost or risk elsewhere, and how quality teams need to evolve as software increasingly includes probabilistic components.

I enjoy exchanging ideas with practitioners, challenging assumptions, learning from people who are doing the work, and contributing lessons from both large enterprise environments and hands-on product building. I am here to learn, share, debate constructively, and hopefully help advance what quality engineering needs to become next.