One of the hardest things about building comprehensive and reliable test coverage is simply getting started. The size of the project and the number of moving parts to manage while continuing to build and ship the core product overwhelm QA and dev teams just trying to get from 0 to 1.
The key to getting started is not to bite off more than you can chew, and just to start with what you need right now. Test automation will never be finished, any more than the product will ever be “finished.” Approach your test suite and testing infrastructure as an iterative and evolving engineering initiative, not a daunting mountain to be scaled in one go.
Here are four common reasons test coverage stalls before getting off the ground.
#1: Over-engineering a testing infrastructure before you even have your happy paths
Nothing slows down test coverage like preparing for scale before proving value. All too often, teams begin by establishing the foundation, which typically includes CI pipelines, test runners, dashboards, flaky test retries, and possibly a custom-built runner agent. Or perhaps they start to implement a PR testing strategy with ephemeral test environments, but no tests. The team believes they are setting the project up for success, aiming to make test automation “production-ready.”
If the team hasn’t automated the application’s core happy paths yet, no one can know what infrastructure they will eventually need—or where it’ll break under pressure.
What they need is test coverage. But instead, they are producing infrastructure. And when you ask, “What’s protected?” the answer is something trivial and not tied to real user behavior or actual product risk.
Flip the order of your priorities: Start by identifying your riskiest or most common user flows. Encourage the team to automate at least one test in CI—flaky, messy, whatever. Once you’ve identified what breaks, you can then start building around what you know you need.
#2: Trying to build a QA process from spare parts
It’s tempting for the team to work with what’s already there. A couple of old Selenium jobs. Some Cypress code from a past sprint. A Jenkins job that might still run. The goal is usually to “get something working quickly” and maybe phase out the older tech later.
But this is a case of the sunk-cost fallacy in action.
What appears to be a head start is often a maintenance nightmare waiting to happen. The tools don’t fit together. The tests don’t reflect the existing state of the application’s workflows. And even when the suite runs, it doesn’t run reliably. Teams end up chasing CI failures, skipping tests to unblock releases, and pretending they have a working system, when in reality, nothing important is being tested.
Be willing to kill your darlings: Don’t assume you need to throw everything away. But don’t assume you can salvage it either. Give the team a time-boxed window—say, a sprint—to get one high-value test passing consistently using the existing stack. If it works, build from there. If it doesn’t, that’s their green light to start fresh with tooling that fits the product today.
#3: Over-planning a test matrix for a product that’s still changing
Some teams insist on writing out the entire coverage plan before deploying a single test into CI, including coverage goals, a browser and OS matrix, and variations of edge cases. It looks impressive, but it ignores the fact that software changes daily.
Extensive planning around a perfect version of the product—one that doesn’t exist yet—is a great way to build something no one can use. By the time the matrix is “finalized,” the product has already changed. Application specs are outdated. Edge cases are irrelevant. And no tests have been written.
Don’t get us wrong: a comprehensive coverage plan is crucial for building confidence, but you need tests, which means developing a plan and test code simultaneously. Later in this series, we detail a strategy that will take your team down the shortest path to that plan.
Just start with your high-priority tests: You already know what they are, and you don’t need a planning session to itemize them. They’re the workflows that generate support tickets, drive revenue, or frequently break after releases. Anchor early coverage to actual usage, not hypothetical risk. Your team will build momentum faster and avoid wasting time on the wrong test cases.
#4: Automation takes a back seat to everything else
Even when teams recognize the importance of automation, it often feels less urgent than other priorities. After all, manual QA gets the job done—for now, and, in an emergency, it’s easier to pull everyone off task for a bug bash than to get something substantive automated to get a release out the door. And every sprint brings new problems: urgent shipping deadlines, distracting product bugs, production firefighting, and so on.
So, automation becomes a side project—a “when we have time” initiative. Tests are written during slow weeks (if there are any) and left to gather dust when things get busy. Over time, the cost of doing nothing adds up until a major release goes sideways and automation suddenly becomes “critical” again.
The real problem is that manual testing is a self-perpetuating time sink. And without a long-term investment in automation, your team will never break the cycle.
Treat automation like product work: Put it on the roadmap. Assign ownership. Scope it into sprints. The longer it sits in the backlog, the more time your team spends rerunning the same checks by hand, and the harder it is to scale later.
Remove the obstacles
Test automation doesn’t fail because teams don’t care. It fails because they try to do everything upfront instead of doing the right things first.
QA Wolf helps teams start where it matters. We build coverage around real workflows, not guesswork. No infrastructure to manage. No stale scripts to resuscitate. Just fast, durable tests that run in parallel and scale with your product.
Coming up next: how to prioritize test coverage to deliver value fast—and set the foundation for long-term success.
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