Getting test automation started is challenging, and even getting one test running in CI is a significant achievement that many teams struggle to attain. At that point, the team runs a handful of tests in CI. They wire in some alerts. They even catch a few bugs.
But the hard work has just begun, and it’s not uncommon for things to slow down. Coverage stalls. Failures stack up. Developers lose trust in the test suite, QA stops maintaining it, or gets overwhelmed and slows down delivery.
If your team is struggling to scale from proof of concept to 80% coverage, one or more of the following problems may already be occurring.
We’ll show you how to fix each one, so you don’t just ship tests, you ship a system that holds up.
#1: Testing what’s convenient instead of what customers use
To get things working, many QA teams focus on what’s easiest to automate: login edge cases, isolated component states, or flows that don’t require test data. But those flows may or may not be the highest priority, or the ones that keep customers happy and catch real bugs.
Meanwhile, the workflows that matter most—checkout, onboarding, multi-user collaboration, role-based permissions—go untested because they’re harder to build and maintain. Subsequently, the test count rises, and confidence in the automation drops.
To get things working, many QA teams focus on what’s easiest to automate: login edge cases, isolated component states, or flows that don’t require test data. That makes sense in the early days. But as coverage expands, this shortcut becomes a bottleneck.
Modern apps are built on a web of third-party APIs, services, and integrations. The workflows that matter most—checkout, onboarding, role-based permissions, multi-user collaboration—cut across systems, platforms, and data boundaries. They’re hard to test. And many legacy frameworks (Selenium, Cypress, Cucumber) just can’t handle them.
Tricentis found that 71% of QA engineers write tests based on technical feasibility, not business priority. That’s how you end up with a bloated test suite that skips the most valuable flows. You’re testing what’s possible, not what matters.
Fix: Anchor coverage to actual customer behavior. Start with your highest-risk workflows, identified through live demos, product analytics, and stakeholder interviews. Build coverage around what breaks most often or costs you the most when it does. And don’t let framework limitations define your coverage map.
#2: Treating testing like it’s not an engineering problem
Test execution needs systems and processes. Without the same rigor that you apply to your application code, test suites become brittle, unscalable, and impossible to debug. Low-code and no-code tools play into that illusion, selling the idea that test automation is just clicking through a UI and recording what happens. That anyone, with the right tool, can own it.
But low-code still means some code. And tests are still software. If the person creating them doesn’t have a firm grasp of system architecture, debugging, or test design, then you’re laying a foundation of spaghetti. That fragility only gets worse when those same tests break, and the person responsible doesn’t have the skills to fix them.
Tests written this way won’t scale. They won’t be reliable. And developers won’t trust or use them. Instead, the tests will just add to their backlog.
Fix: Treat test automation like software engineering. The people responsible for writing and maintaining tests need the same core skills as developers: version control, CI experience, and enough product context to debug failure states. If your test tooling assumes otherwise, it’s not making life easier. It’s masking tech debt and handing it to the wrong team.
#3: Choosing a test framework without considering what it needs to do
Few teams give thoughtful consideration to their test framework. Most just inherit whatever the frontend team is already using—Cypress, Selenium, or whatever was in place last quarter. Others carefully evaluate options, only to have them overridden: someone mandates BDD for “readability,” or an architect chooses a framework in a language nobody else on the team knows.
These decisions rarely reflect the actual needs of the testing team or the complexity of the product.
Modern apps aren’t simple. They involve real-time updates, multi-user flows, browser extensions, mobile components, flaky third-party APIs, and edge-case state management. A framework that can’t handle those workflows—or can’t be extended easily—will block progress fast. Tests often end up being written based on what’s feasible, rather than what’s important.
That’s how you get brittle, shallow coverage—and how important bugs slip through.
Fix: Select a testing framework that supports your app. Choosing a framework is an important decision, and your team should be empowered to select the one most capable of providing maximum application coverage. We build tests in Playwright, which supports cross-browser and mobile flows out of the box, and adds custom logic for more complex cases, including multi-tab state, real-time sync, SMS/email flows, blockchain wallets, browser extensions, media playback, and more.
#4: Infrastructure bottlenecks grind your team’s progress to a halt
Once real coverage is in place, infrastructure starts to strain. Most teams try to scale by sharding tests across multiple CI workers. But sharding isn’t true parallelism—it just spreads the pain. Your teams are still competing with each other for CPU, memory, and browser resources.
Cloud SCMs, like GitHub Actions, work fine for small suites. But after 50–100 end-to-end tests, everything slows down. Queues build up. Tests flake or fail from OOM errors. Developers start skipping test runs. QA throttles coverage to stay within the budget. Meanwhile, leadership starts wondering why the suite is so slow and still missing bugs.
Want more concurrency? That costs money. Don’t want to pay? You’ll need to build your own infrastructure and assign someone to maintain it.
Fix: Run everything fully parallel. Parallelism is the solution to the QA bottleneck, full stop. Run all your tests at once, and you cut the feedback loop, speed up releases, and keep your CI pipeline from turning into a traffic jam. But spinning up parallel infrastructure that can scale with your team takes serious work. You’ll need containers, orchestration, and someone to keep the whole thing from falling over. This is just math.
#5: Treating test creation like a project instead of a system
Many teams treat their initial automation push like a one-time effort. The QA team writes the first batch of tests, runs them in CI, and considers the work complete. It’s understandable—getting started is hard. Creating those first tests feels like a milestone. And it is.
But creation isn’t the hard part. Sustaining coverage is. In our experience, maintaining a suite takes nearly twice as much time and effort as building it in the first place. As your product evolves, workflows drift. Selectors break. New features ship without coverage.
Fix: Plan for capacity, not just coverage. It’s hard to stand by your guns when the industry still treats maintenance like an afterthought. We know. Every day, we fight the pervasive myth that once the tests are written, the hard part’s over. But a healthy test suite doesn’t maintain itself. You’ll need time, people, and process to keep it running. Plan to hire 1 QA engineer for every 50–75 tests, plus SDETs to manage infrastructure, debug flaky runs, and keep pipelines fast.
#6: Accumulating test debt without a plan to pay it down
Most teams view test coverage as a linear progression—more tests equal more confidence. But if you’re not ready to support that coverage long-term, every new test is a liability.
We’ve seen it over and over: after a successful kickoff, teams go wide fast. Dozens of new tests get added in a sprint or two. But the team hasn’t developed the necessary systems to support them—flake tracking, test reliability metrics, investigation ownership, or capacity planning. There’s no budget, time, or headcount for maintaining what was just built.
Fix: Build coverage in layers. As we saw above, when expanding coverage, you need maintenance that scales with it, not just from a test perspective, but also from a tooling perspective. If your tools can’t support the coverage you built, that coverage isn’t providing value.
One approach that works for us is building coverage in layers and managing debt as we progress, tracking flakes, owning investigations, and continually improving test reliability.
#7:No shared ownership of test automation outcomes
Test automation isn’t just a QA problem. It’s a teamwide responsibility. But too often, no one acts like it.
Developers often ship features without considering how those features will be tested. QA gets stuck automating complex workflows they didn’t design, with no support when things break. Testers go wide by nature—they have to cover every interaction, every flow—but they’re often left chasing brittle bugs in systems they don’t own and can’t fully understand.
Sometimes it’s unclear who owns the feature. Sometimes, everyone assumes someone else will handle it. Either way, the result is the same: tests break, alerts get muted, and the suite gradually loses its usefulness.
Fix: Make automation outcomes a shared responsibility. Expect your developers to write testable code, expose hooks and data when needed, and respond when tests tied to their features fail. QA should focus on coverage, breadth, and orchestration. And when tests do break, the right owner should get notified with sufficient context and the authority to fix it.
The real challenge is staying in motion
Getting your first few tests running is a milestone. But most test automation efforts fail after kickoff—not because the tech is wrong, but because the strategy breaks down. No process. No ownership. No alignment to actual product risk.
QA Wolf helps teams move past that plateau. We don’t just ship tests—we build, maintain, and run your suite in full parallel, keeping it aligned to real user behavior, and take care of the day-to-day work so your engineers and QA leads can focus on the product, not the plumbing.
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