Week 1
Why QA Automation Is About More Than Speed
QA automation is often sold as a way to move faster. But speed isn’t the real value. What matters more is trust.
Automation helps teams catch issues early. It gives developers clear feedback. It keeps releasing stable versions. That’s what builds confidence, not just in the product, but in the process.
Microsoft’s approach shows this well. Their QA agents don’t just run tests. They
- Analyze failures
- Generate test data
- Help teams understand what went wrong
This leads to faster fixes and fewer surprises. You can see how it works here: Microsoft’s QA Testing Agent Scenario.
In Power Platform, Microsoft uses layered testing. They
- Start with critical functions
- Expand coverage gradually
It’s not about testing everything at once. It’s about testing what matters, when it matters. That’s how they keep updates reliable. Learn more here: Effective Automated Testing Strategies.
Automation also helps teams scale. When tests run consistently,
- Releases happen more often
- Teams stay in control
- Quality doesn’t slip
Automation helps reduce burnout. Manual testing takes time and feels repetitive. You run the same checks again and again, often under pressure.
With automation, teams get that time back. They can
- Focus on harder problems
- Fix bugs that affect users
- Improve how the product feels
That shift makes the work more meaningful. It also boosts morale and leads to better results.
And it’s not just about the team. Reliable automation builds trust with clients and users. It shows that
- Quality isn’t an afterthought
- Stakeholders can count on stability
- People stop worrying about what might break
QA automation isn’t a shortcut. It’s a safety net. It’s how you build a product that people can count on.
Here’s another example of how automation improves software quality at scale: Cigen’s QA Reliability Guide.
#QA #Automation #SoftwareTesting #Microsoft #TrustInTech #ReliabilityOverSpeed #PowerPlatform #QualityAssurance
Week 2
Automating Everything Is a Mistake
Automation helps. But automating everything? That’s a mistake.
Many teams chase full coverage, thinking more scripts mean better quality. In practice,
- It creates confusion and extra work
- It’s harder to spot what’s actually important
- It leads to brittle systems and wasted effort
Smart automation means choosing what to test and what to skip. You focus on what breaks often and what users depend on. And you target the parts that slow things down. The rest? You test manually or monitor in production.
Netflix doesn’t aim for 100% coverage. They focus on making systems strong. Their teams
- Simulate failures using chaos engineering
- Test how systems break and recover
- Prioritize resilience over perfection
Read more on Netflix’s Chaos Engineering Approach.
Google takes a similar approach. They
- Focus on high-risk, high-impact areas
- Avoid overloading pipelines with end-to-end tests
- Warn against false confidence from excessive automation
See their take here: Google’s Testing Blog.
Automating everything might feel thorough, but it often backfires. Tests break for the wrong reasons. Teams waste time fixing broken tests instead of making the product better. And when automation becomes a checkbox, it loses its value.
Here’s the real issue: full automation creates a false sense of safety. Just because something is tested doesn’t mean it’s tested well.
- Coverage maps show quantity, not quality
- Quantity alone doesn’t protect your users
Instead, build a strategy:
- Know your weak spots
- Automate where it adds confidence
- Leave space for human judgment
- Use exploratory testing to catch real-world bugs
Good automation supports your team. It doesn’t overwhelm them. It doesn’t replace thinking. It helps people focus on what matters.
Reliable automation also improves morale. When tests are useful, people trust them. When scripts are noisy, people ignore them. That’s when risk creeps in.
Here’s a practical guide to doing it right: Thoughtworks on Strategic Test Automation.
Automation should be a tool, not a trap. Use it wisely.
#QA #Automation #SoftwareTesting #Netflix #Google #TestStrategy #SmartAutomation #QualityOverCoverage #TechLeadership #EngineeringExcellence
Week 3
Flaky Tests Kill Confidence
Flaky tests are more than a nuisance; they’re a trust killer.
When tests fail randomly, teams stop believing in the results. They
- Ignore failures
- Rerun pipelines without fixing the root cause
- Hope for the best instead of relying on the system
That’s not resilience. That’s roulette.
Shopify faced this head-on. Their CI pipelines were clogged with unreliable tests. Developers couldn’t tell if failures were real or just noise. It
- Slowed down releases
- Drained team morale
- Undermined confidence in automation
Instead of chasing full coverage, they focused on stability. You can read their story here: Shopify’s CI Pipeline Optimization Story
Flaky tests break the feedback loop. They waste time, erode confidence, and make teams question the value of automation. And when trust fades, so does discipline. People skip checks. Bugs slip through. Quality drops.
So what can you do?
Start with retries, but use them wisely. Shopify added retry logic to
- Separate real failures from random ones
- Reduce noise in the pipeline
- Improve signal clarity
They also built dashboards to track flakiness over time. That visibility changed everything. Teams could spot patterns, prioritize fixes, and hold each other accountable. Learn more about the approach here: Flaky Test Detection and Prevention Guide
Another fix: quarantine unstable tests. Don’t let one flaky script block the whole pipeline. Flag it, isolate it, and fix it without slowing everyone down. This keeps the pipeline clean and the team focused.
Also, invest in test ownership. Every test should have a clear owner. If it fails, someone’s responsible. That accountability keeps quality high and flakiness low.
Flaky tests won’t go away on their own. You need
- A plan
- Visibility
- A mindset that treats test stability like a product feature, not an afterthought
Pipeline resilience isn’t just about speed. It’s about trust. And trust starts with reliable tests.
#QA #Automation #CI_CD #Shopify #SoftwareTesting #PipelineResilience #FlakyTests #TestStrategy #EngineeringExcellence #DevOps
Week 4
AI Is Making Regression Smarter
Regression testing used to be a slow, repetitive task. Every change meant rerunning hundreds of scripts—just to make sure nothing broke. It was safe, but not smart.
Now AI is changing that. It’s not replacing QA teams. It’s helping them work faster and focus on what matters.
One shift is predictive testing. Instead of running every test, AI looks at code changes and past bugs to guess where problems might show up. That means
- Fewer tests
- Faster feedback
- Smarter coverage
GenQE explains how AI can rank tests by risk and relevance—like focusing on login flows after an update to authentication.
Another change is adaptive scripts. Traditional tests break when the UI changes. AI can fix that. It
- Spot layout shifts, or renamed buttons
- Updates scripts automatically
- Keeps pipelines stable with less maintenance
This self-healing feature saves time and keeps pipelines stable. LambdaTest shows how AI tools now write and repair scripts using plain language.
AI also helps teams spot patterns. It learns from past test runs, logs, and user behavior. It flags flaky tests, predicts failures, and suggests what to fix. That kind of insight used to take hours. Now it’s built into the workflow.
But AI doesn’t replace human judgment. It doesn’t handle edge cases or usability. It just:
- Clears the noise
- Highlights what matters
- Supports deeper testing
Katalon’s research shows how AI-powered regression tools improve speed, reduce errors, and expand coverage. Their TrueTest platform is built to bring this into everyday QA.
The future of QA isn’t about running more tests. It’s about running the right ones. AI helps teams:
- Test less but learn more
- Turn regression into a smart safety net
- Build confidence without slowing down
And that’s what better testing looks like.
#QA #RegressionTesting #AIinTesting #Automation #PredictiveTesting #AdaptiveScripts #LambdaTest #GenQE #Katalon #SoftwareQuality #FutureOfQA #EngineeringExcellence