Harness Engineering: Production-Ready AI Agents
Meet the Speakers
Satyaprasad Dakinedi
Quality Architect
EPAM Systems
With 17 years spanning QE and DevOps, he drives enterprise AI adoption as EPAM's Agentic AI Champion and global tech speaker.
Neeraj Kumar
Principal product Manager
AI initiatives
Passionate about leveraging AI and Data Science to solve challenges in Fintech, HealthTech, and SaaS for India’s growth.
Build a faster testing pipeline with autonomous AI agents.
Stop losing engineering hours to broken locators.
Your team spends days debugging flaky scripts. By enabling self-healing agents, you can remediate locators at runtime and reduce failure analysis time by 95 percent.
The model is rented. The harness is owned.
The engineering layer surrounding your AI model determines if your agentic system survives production. We reverse-engineered Ai models to show you exactly how to build a resilient harness.
What you’ll learn
- Remediate broken locators at runtime with self-healing AI.
- Master the core subsystems of a production-ready AI harness.
- Discover architectural choices that make or break AI teams.
What Our Customers Have to Say
With AI-powered Visual Testing embedded in our quality pipeline, we’ve moved beyond code validation—into protecting the brand experience at scale, with precision and speed.
Zohar Liran
Director, Head of Engineering, Construction Platform, Autodesk
A test could come out true, but the screen does not look anything like you want it to look. That’s where visual testing with Percy comes in.
Ayushi Arora
SDET Lead, Nykaa
We have successfully brought down the regression time from 4 days to 1.5 days, resulting in short turnaround time on the life cycle of apps.
Vijay Selvam
Manager, Test Engineering, Swiggy
We will continue encouraging more teams to integrate automated tests with BrowserStack to increase their test coverage, reduce their feedback loops and deliver high-quality products faster.
Georgiana-Lucia Baragan
Senior Engineering Manager, Booking.com
The most major impact I have noticed is that we are able to deliver fast. We are also able to maintain the robustness and stability of our tests; the tests are more reliable now. And if anything fails, we have the video recording to go back and analyse where, when and why the test failed – is it a genuine issue or flakiness associated with our test case.
Harit Narke
Lead Software Engineer, Mastercard
Don’t miss out !
If you're managing, leading QA teams and looking to get inspired, learn, or connect, you'll want to be a part of our Webinar