Find out how to Supercharge Check Automation with AI and Playwright

Why Your Automation Technique Might Be Falling Behind

In case your QA group continues to be spending hours writing web page objects, take a look at locators, and knowledge factories by hand, you’re already behind.

Generative AI is reshaping take a look at automation at a staggering tempo, slashing coding duties from hours to minutes, and enabling engineers to provide 3–5x extra high-quality code per dash.

However whereas the hype round AI in QA is in all places, few leaders know how you can separate shiny “magic options” from sensible enterprise worth.

That’s the place Ben Fellows is available in.

Meet Ben Fellows

Ben Fellows is the founding father of a QA companies firm and a main voice on LinkedIn within the AI-powered QA motion.

With years of expertise serving to QA groups implement Playwright and AI-driven automation, Ben has educated trade leaders like Jim Hazen and Butch Mayhew by means of his hands-on workshops.

His focus?

Serving to QA leaders minimize by means of noise and apply AI the place it instantly accelerates supply, reduces prices, and boosts group productiveness.

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1. Use AI as a Productiveness Booster, Not a Silver Bullet

Based on Ben, too many distributors are promoting “AI brokers that do all of your testing for you.”

Whereas flashy, these options are sluggish, costly, and never production-ready.

As an alternative, the true worth at the moment is augmented coding—utilizing AI to generate the identical high-quality code your engineers would usually write, solely quicker.

• Instance: Writing a Playwright web page object mannequin that used to take 3–4 hours now takes 20 minutes or much less with AI.
• Enterprise consequence: Groups can ship options quicker, cut back backlog strain, and maintain tempo with accelerated improvement cycles.

2. Rethink QA Roles within the Age of AI

As AI instruments velocity up code era, the bottleneck has shifted. QA leaders are not struggling to provide sufficient code—they’re struggling to overview code at scale.
Ben notes that some corporations are rebalancing their org charts:

• Fewer engineers targeted on uncooked coding
• Extra emphasis on reviewers, architects, and take a look at strategists

This shift requires QA managers to rethink job descriptions, efficiency metrics, and group buildings.

3. Give attention to Excessive-Worth, Tedious Duties First

Need to get began?

Don’t goal for moonshots. Ben recommends making use of AI to repetitive, pattern-based duties that drain engineering hours:

• Web page Objects: Mechanically generate tons of of locators and strategies with accuracy charges above 80%
• Information Factories: Feed AI your schema and let it produce take a look at knowledge factories in minutes.
• API Insights: Level AI at an endpoint and get the article form, dependencies, and even higher Swagger documentation.

By focusing on these tedious duties first, QA leaders can shortly exhibit ROI and achieve buy-in from skeptical stakeholders.

4. Spend money on Premium Fashions and Guardrails

Not all AI is created equal. Ben warns that outcomes range dramatically relying on the mannequin. Groups utilizing low cost or outdated fashions usually dismiss AI prematurely as a result of outputs are poor.

Greatest practices:

• Price range $200–$250 per engineer/month for premium fashions like Claude or GPT-5.
• Use Cursor guidelines/templates to implement coding requirements throughout your group.
• All the time overview and debug AI-generated code—the aim is acceleration, not blind belief.

5. Put together for the Subsequent Wave: Picture-Primarily based Testing

Waiting for 2026, Ben predicts a shift away from DOM-based automation towards image-based or natural-language testing.

Think about instructing an AI: “Log in, navigate to the dashboard, and validate formatting matches the design.” The AI evaluates the web page visually—identical to an actual person—eradicating the necessity for brittle locators and assertions.

Whereas that is nonetheless costly and sluggish at the moment, the expertise is bettering shortly. QA leaders ought to begin experimenting now to keep away from being blindsided.

Actionable Takeaways for QA Leaders

Right here’s how you can begin making use of these insights in your group:

• Run a POC with premium AI fashions (Claude, GPT-5) utilizing Cursor or Copilot
• Goal tedious duties first—web page objects, locators, and knowledge factories.
• Shift your group combine towards reviewers and strategists, not simply coders.
• Set guardrails with templates and coding guidelines to make sure consistency.
• Discover future traits like Playwright MCP and image-based testing, however don’t wager the farm but.

Closing Ideas

AI received’t change nice testers—it would amplify one of the best ones. By adopting augmented coding at the moment, you’ll be able to free your group from repetitive drudgery, speed up supply, and put together for the following wave of AI-driven automation.

To dive deeper, take a look at the complete episode of the TestGuild Automation Podcast with Ben Fellows—together with reside demos of AI writing 500+ strains of production-ready Playwright code in minutes.

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