Repairing Playwright Test with Specialised AI Agents & Graph RAG |10th NY Meetup

10th New York Meetup – Repairing Playwright Tests with Specialised AI Agents and Graph RAG

When a Playwright test fails, the failure isn't always a broken application.
It could be an outdated locator, a synchronization issue, or a genuine regression. Before repairing the test, you need to understand what actually went wrong.

At The Test Tribe’s 10th New York Meetup, Srinivas Rao Jonnakuti will explore how Graph Retrieval-Augmented Generation (Graph RAG) can connect requirements, source code, tests, and execution evidence to help AI agents diagnose and repair Playwright failures more intelligently.

Event Details

Date: 28 October 2026
Time: 06:00 PM – 08:00 PM ET
Venue: 307 W 38th St 1401, New York, NY 10018, USA

Session – Repairing Playwright Tests with Specialised AI Agents and Graph RAG

Speaker: Srinivas Rao Jonnakuti

Using an illustrative checkout scenario, the session explores a workflow where specialised agents handle different stages of the testing process from planning and test generation to execution, diagnosis, and repair.

You’ll explore:

How Graph RAG connects related software artefacts to provide context for test diagnosis and repair.
How specialised agents can divide responsibilities across the testing workflow.
How traces, network evidence, and repository changes can help distinguish test defects, application regressions, and synchronization issues.
How AI-assisted repairs can be validated while preserving existing assertions and keeping application defects visible.
Safeguards such as regression checks, repair limits, and human review for high-risk changes.

How This Meetup Solves Your Problem

Playwright failures take too long to diagnose? Explore how connected software context can help agents identify the likely cause.
AI repairs risk hiding real application bugs? Learn how to preserve assertions and validate targeted fixes.
Not every failure is a test defect? See how execution evidence can help distinguish broken tests from genuine regressions.
Concerned about autonomous test repair? Explore practical safeguards and where human review remains important.

Why Show Up on 28 October?

Because fixing a failed test starts with understanding why it failed.
Because AI-assisted repair is more useful when agents have context across requirements, code, tests, and execution evidence.
Because specialised agents can divide complex testing workflows into focused responsibilities.
Because autonomous repair needs safeguards — not just automation.
Because the goal isn't to make AI fix more tests. It's to make sure it fixes the right tests without hiding real defects.

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