I'm researching pain points in automated testing reporting, specifically for Playwright. Our team is hitting some roadblocks with current solutions, and I'm curious if others are experiencing similar issues.

Current limitations we're facing:

1. Basic pass/fail metrics without deeper analysis

2. Hard to identify patterns in flaky tests

3. Difficult to trace failures back to specific code changes

4. No AI-assisted root cause analysis, we are doing that manually with chatgpt

5. Limited cross-environment comparisons

I'm wondering:

1. What tools/frameworks are you currently using for Playwright test reporting?

2. What would an ideal test analysis solution look like for your team?

3. Would AI-powered insights into test failures be valuable to you? (e.g., pattern recognition, root cause analysis) - Did any one tried AI MCP solutions

4. How much time does your team spend manually analyzing test failures each week?

5. Are you paying for any solution that provides deeper insights into test failures and patterns?

6. For those in larger organizations: how do you communicate test insights to non-technical stakeholders?

I'm asking because we're at a crossroads - either invest in building internal tools or find something that already exists. Any experiences (good or bad) would be super helpful!

Thanks for any insights!