You Can’t Test In Quality: Why QE Is About Prevention, Not Detection

“Quality can’t be tested in—it has to be engineered in.”

I’ve said this line more times than I can count. Not because it’s catchy—but because it’s the core truth that too many engineering leaders still ignore.

When most teams talk about “quality,” what they’re really describing is testing—bug tickets, automation scripts, and CI failures. But testing is only one tiny slice of the quality equation. And when testing becomes the only approach to quality, it sets up a reactive culture that’s doomed to fail at scale.

True Quality Engineering (QE) flips the script. It doesn’t just find problems—it prevents them. It’s not about doing more testing—it’s about removing the need for it in the first place.

So let’s talk about what that actually means.

The Legacy Mindset: QA as the Final Checkpoint

In many organizations, quality assurance is still treated like a gatekeeping function at the end of the pipeline. Features are built, merged, and handed off to a QA team for “validation.” Only once the QA team gives a thumbs up does a release go out.

There are a few major issues with this model:

1. Testing is reactive. It catches problems after they’ve already been coded—and sometimes, after they’ve already shipped.
2. Testers lack context. They’re often looped in too late to influence upstream design decisions or prevent ambiguity in requirements.
3. Responsibility is siloed. Developers “build,” QA “tests,” and neither owns quality end-to-end.

The result? Slow releases, expensive rework, and finger-pointing when bugs slip through.

The QE Mindset: Quality as a Design Constraint

Quality Engineering doesn’t start at the end. It starts before the first line of code is written.

In a QE-first culture, quality is engineered in at every layer:

• Architecture: QE partners help design resilient, observable systems before a ticket is even groomed.
• Development: Engineers build with testability in mind—layering in logging, hooks, and coverage instrumentation as they code.
• Tooling: Automation is treated like infrastructure—versioned, scalable, and part of the core build pipeline.
• Feedback loops: Telemetry, monitoring, and test analytics inform what to test next, not just what broke last.

This is about changing the role of QA from “test executors” to quality engineers—strategic contributors who influence how software is built, not just how it’s checked.

Common Pain Points in the Shift from QA to QE

Here’s what I’ve seen over and over in companies struggling to make the leap:

1. Testing is reactive, not embedded

Teams wait until a feature is built to think about tests. By then, it’s too late to shape the architecture, reduce edge cases, or define clear validation paths. QE flips this: validation starts at design.

2. QE voices are missing from architecture reviews

Engineers discuss performance, scalability, and cost—but not testability. If QE isn’t at the table early, they’re stuck reverse-engineering brittle test strategies later.

3. Dev and QA don’t share ownership

Devs say, “QA will catch it.” QA says, “We didn’t build it.” This blame-ping-pong is a symptom of siloed accountability. In high-functioning teams, everyone owns quality.

4. Leadership doesn’t understand the difference between QA and QE

To many execs, “QA” means test cases and bug reports. But QE is about designing systems that don’t need as much testing—because they’re stable by default.

According to Testlio’s State of Software Testing, 72% of teams say they still struggle to adopt proactive quality strategies. That statistic doesn’t surprise me. Most orgs are still running QA like it’s 2009.

QE Isn’t About More Testing—It’s About Less

One of the most misunderstood truths in modern software development is this:

The best QE teams aren’t testing more.
They’re making it so there’s less that needs to be tested.

How?

• Reducing ambiguous requirements with better triad collaboration between Product, Dev, and QE.
• Improving component isolation, so unit and integration tests cover 80% of the surface area without brittle end-to-end scenarios.
• Investing in observability, so quality is monitored continuously—not just at test time.
• Shifting failure detection into staging telemetry, not user reports.

Every hour spent designing a testable system saves five debugging flaky pipelines later.

What It Looks Like in Practice

At my current company, we made the shift to a QE-first model without bloating our process. Here’s what we did:

• QE sits in architecture planning. Every new feature or refactor includes a “testability review.” We ask: Can we observe this? Can we isolate it? Can we fail it cleanly?
• Test coverage isn’t just %—it’s relevance. We use LLMs and CI signals to assess where our tests actually protect critical paths.
• Automation is treated as infra. No one-off scripts. Tests are built, reviewed, and deployed like code.
• Telemetry closes the loop. We track production defects back to gaps in our test strategy—then fix both the code and the process that missed it.

The impact? Fewer regressions, less time fixing tests, and faster delivery without compromising on confidence.

How We Built a QE-First Culture (Without the Bloat)

When we made the shift to a Quality Engineering–first approach, we had two non-negotiables:

1. It couldn’t slow us down
2. It couldn’t become a governance-heavy process nightmare

Here’s how we made the shift—fast, lean, and effective:

✅ Step 1: Bake Quality into Planning, Not QA Cycles

We didn’t launch a new team or write a 50-page testing strategy. We did something simpler: we changed how we planned.

Every new feature or refactor now gets a Testability Check during planning. It’s just 10 minutes in the same planning meeting, but it forces us to ask:

• Can this be tested easily?
• What metrics or logs will tell us it’s working in prod?
• Are there any failure modes we’re blind to?

This one change aligned Dev, QE, and Product—without adding any process overhead.

✅ Step 2: Turn Automation Into Infrastructure

Instead of writing more tests, we focused on writing better, reusable test scaffolding.

• Every new test suite is version-controlled, reviewed like app code, and lives next to the service it covers.
• We introduced lightweight domain test harnesses—thin layers that make tests readable, reusable, and stable.
• We invested in tools like Allure TestOps and GitHub Actions to give visibility without dashboard sprawl.

No bloated test plans. No manual QA handoffs. Just infrastructure that reinforces quality at speed.

✅ Step 3: Close the Feedback Loop With Real-World Signals

We didn’t rely on test coverage alone. We started using production signals to steer our quality efforts:

• What types of errors are most common in the logs?
• Where are users dropping off in key workflows?
• What incidents could have been caught with better observability?

That feedback loop helped us prioritize test coverage where it actually mattered—not where it looked good on paper.

The Hardest Part? Mindset.

The hardest part of all this isn’t technical. It’s cultural.

You need buy-in across engineering leadership to stop treating QA like a separate department and start embedding it into how you build. That means:

• Redefining career paths for testers to become quality architects, not test case writers.
• Training devs on writing reliable tests—and holding them accountable.
• Rewarding prevention just as much as reaction.

And most importantly, you need to speak in terms your leadership understands. Quality isn’t about being bug-free. It’s about being predictable, scalable, and trustworthy.

Final Thought: Treat Quality Like a Design Constraint

You wouldn’t build a system without thinking about cost, latency, or scalability.

So why build one without thinking about quality?

Quality Engineering isn’t a phase. It’s a mindset, a strategy, and a practice—one that pays compounding dividends as your team and system scale.

And no, you can’t test it in at the end.