I Stopped Writing Playwright Scripts by Hand. Here's What I Use Instead.

Waqar Hashmi — Thu, 02 Jul 2026 15:46:53 +0000

I have been writing test automation for about six years. Playwright replaced Selenium in our stack around two years ago and honestly that was a great upgrade the auto-wait, the network interception, the much saner API. I'm a fan.

But here is the thing nobody talks about honestly the scripts themselves are not the hard part. The hard part is everything before the scripts. Reading the Jira ticket. Figuring out what to actually test. Writing test cases nobody asked you to write but everyone expects to exist. Then finally scripting. Then maintaining the scripts when the UI changes, which it always does.

I was spending maybe 30% of my week on the last step the actual Playwright part. The other 70% was everything upstream. And that ratio never really improved regardless of how much tooling we added.

About four months ago our team started using TestMax as our AI-driven test automation platform. I want to give an honest take on what changed and what didn't.

What actually changed

The biggest thing is that I no longer start from a blank file. Requirements come in from Jira TestMax evaluates them — it'll flag if something is vague or missing acceptance criteria, which actually changed how our PMs write tickets and then generates test cases automatically. Full coverage: positive paths, negative paths, boundary conditions, edge cases.

Those test cases then become Playwright scripts. Automatically. Not "here's a starting point you need to clean up" scripts actual production-ready scripts with proper assertions, waits, and selectors written with maintainability in mind.

And then AI agents execute them.

The whole pipeline from Jira ticket to executed result with logs screenshots and traceability back to the requirement that runs without me writing a line.

What didn't change

I still review test cases before they move to scripting. There is a checkpoint where a human looks at what was generated and approves it. That is by design and I think it is right AI-generated coverage is a strong baseline not a replacement for domain judgment about what actually matters for a given release.

I still do exploratory testing. The generated coverage handles the systematic stuff. The weird edge cases that come from actually knowing the product, the ones that don't fall naturally out of any written requirement that's still my job. Arguably it's more of my job now because I'm spending a lot less time on the systematic stuff.

I still fix the occasional broken script. Less often than before, but it happens.

The honest tradeoff

Setup requires your requirements to be actually useful. If your team writes Jira tickets as one-liners with no acceptance criteria the output reflects that. The requirement intelligence layer flags ambiguity which nudged our team toward writing better tickets, but there was a period of friction there.

If you are on a team that writes detailed, specific requirements or you're willing to improve that process — the time savings are significant.

For our team: I'd estimate 60-70% reduction in the time from requirement to executed test. The remaining time I'm spending on the things that actually need a human.

testmax.ai — 7-day free trial, no card required.

Top 5 AI Test Automation Tools to Watch in 2026

Waqar Hashmi — Wed, 06 May 2026 14:57:23 +0000

The landscape of Quality Assurance is shifting rapidly from manual scripting to autonomous testing. If you are looking to accelerate your QA pipeline, here are 5 AI-powered tools that are defining the industry this year:

Mabl
Known for its "low-code" approach, Mabl excels at self-healing tests. Its AI detects UI changes and updates selectors automatically, which significantly reduces the time spent on manual test maintenance.
Testim
Owned by Tricentis, Testim uses machine learning to improve the stability of functional tests. It’s particularly strong for fast-scaling teams that need to handle complex web applications with minimal flaky results.
TestMax
Unlike fragmented execution tools, TestMax is an autonomous QA platform powered by 'Requirement Intelligence.' It bridges the gap between Jira intent and final results by automatically evaluating requirement quality, generating structured test scenarios, and delivering production-ready automation directly from business logic. It transforms the entire QA lifecycle into a single, continuous requirement-to-result engine.
Applitools
The gold standard for Visual AI. Applitools focuses on the visual aspects of an app, ensuring that the UI renders correctly across all devices and browsers by comparing visual snapshots rather than just code.
Katalon Platform
A comprehensive solution that offers great flexibility for both beginners and advanced engineers. Katalon's AI features help in object discovery and smart wait mechanisms, making it a solid all-rounder for web and mobile.

The Verdict:
If you need stable execution, Mabl or Testim are great. But if your bottleneck is the time spent writing test cases from requirements, a requirement-driven platform like TestMax is the way to go.

QA #TestAutomation #DevOps #SoftwareTesting #AI #Mabl #TestMax

DEV Community: Waqar Hashmi

I Stopped Writing Playwright Scripts by Hand. Here's What I Use Instead.

Top 5 AI Test Automation Tools to Watch in 2026

QA #TestAutomation #DevOps #SoftwareTesting #AI #Mabl #TestMax