TL;DR: A spreadsheet only records that someone marked a test as passed, not that the behaviour was verified against the current build. That gap widens as an app grows, because checklist rows get carried forward instead of re-checked. Proving coverage before a release means replacing assertions with evidence: something you can open and check yourself before you ship.
Key Takeaways
The core problem: A spreadsheet cell records that someone marked a test as passed, not that the behaviour was actually verified against the current build.
Why it gets worse: app surface grows faster than a team's capacity to manually retest it every release, so checklist rows get carried forward instead of re-checked.
Scripts don't fix the trust gap: automated scripts still need selectors that break as the UI changes, and they don't independently review what they find.
Evidence beats assertion: TaloTrace backs every Finding with a recording, reasoning and step-by-step reproduction, reviewed before it reaches you.
Severity follows your rubric: TaloTrace's five-level severity scale can be rated against your own triage guidance, not a generic default.
Coverage stays current: scheduled Runs always test the latest finalized build, so evidence doesn't go stale between releases.
What Does "Proving Coverage" Look Like on a Checklist?
Without a coverage tool, the fallback is a spreadsheet: rows are test cases, columns are pass, fail and tester initials, and a release doesn't go out until enough of them are green.
Someone runs through the list by hand, ticks the boxes, maybe pastes in a screenshot, and a release lead skims the sheet before signing off. It works, in the sense that a release ships. Whether it proves anything is a separate question.
Why Does a Spreadsheet Stop Counting as Proof?
A ticked cell records a claim: someone believes this behaviour worked when they checked it. It doesn't record what they actually saw, when they saw it, or whether anyone else looked at the same thing.
If a bug slips through and two people disagree about whether that row was really tested, there's nothing to check. No recording, no reasoning, no second opinion, just a cell that says "pass" and a memory that may or may not be accurate.
That's the real gap. A spreadsheet can tell you what your team intended to test. It can't tell you what was verified, or who verified it, or against which build.
Why the Gap Between "Tested" and "Verified" Keeps Widening?
This isn't a discipline problem. It's a surface-area problem. Every new screen, state and flow you ship adds to what a thorough regression pass would need to cover, and that grows faster than any team's capacity to manually retest all of it before every release.
The checklist gets copied forward instead of retested, because redoing everything from scratch every release isn't realistic. Rows that "passed last time" stay untouched. The document ends up representing accumulated intent from past releases, not what's actually been exercised against the build you're about to ship.
What Teams Try Instead, and Where It Runs Out?
Each approach adds something and leaves the core gap standing:
Approach | What it adds | Where it runs out |
|---|---|---|
Pasting screenshots into the cell | A visual next to the claim | Still one person's word for what the screenshot shows and when |
Rotating regression duty | Spreads the workload | Severity judgement drifts with whoever's doing it that week |
Writing automated scripts | Removes manual burden | Selectors break on UI changes; maintenance grows with app size, not test count |
Doing none of this | Nothing | Ships on gut feel and last release's spot checks |
And doing none of this, shipping on gut feel and hoping the last release's spot checks still hold, is the option teams are trying to move away from when they start looking for something with real coverage analytics behind it.
What Would Evidence-Based Release Confidence Actually Look Like?
Not a bigger spreadsheet. What's missing isn't more rows, it's an artefact behind each claim: something you or anyone on your team can open, watch and check for yourselves, rather than a cell that just says a human believed it passed.
It also means separating who found an issue from who confirms it's real, so a "pass" in front of your release lead isn't the same person marking their own work. Treating a Run as evidence rather than a checkbox is what closes that gap.That's the reasoning behind treating a Run as evidence rather than a checkbox.
What makes TaloTrace different?
TaloTrace is an AI-powered QA testing platform built to replace the spreadsheet with something you can actually check yourself.
TaloTrace explores your running app and plans the journeys worth testing itself, using goal-based test building instead of hand-written scripts. TaloTrace works from your product documentation and saved test accounts.
Each Run, one execution of a Test Plan against a build, produces a Trace: not a ticked cell, but a record with context, evidence and severity attached to every Finding. Every Finding is backed by a screen recording, TaloTrace's reasoning, and step-by-step reproduction, so it's checkable rather than asserted.
Findings don't reach you raw. TaloTrace independently reviews what it surfaces before anything becomes visible, and results start hidden by default: a Finding only appears once it's been reviewed and approved, or the project is explicitly set to auto-approve. Low-confidence findings are held back from bulk release entirely.
Severity isn't a black box either. Findings carry one of five customer-visible levels, Critical through Trivial, each shown with its underlying P0 to P4 code, and you can supply your own severity rubric for TaloTrace to follow when it rates what it finds. Repeated instances of the same defect collapse into a single issue instead of cluttering the list.
Runs can be started on demand before a release, or set to a daily or weekly schedule at a fixed time in your timezone; a scheduled run always tests the latest finalized build, so the evidence behind a release doesn't go stale between checks. TaloTrace is dogfooded daily on Growtrics Academy, its first and most-tested customer app, and its navigation reliability is measured against a standardised internal benchmark using real apps and real devices. Every run's cost is tracked and visible. TaloTrace surfaces 4x more validated bugs compared to manual QA, and early teams report up to 90% lower QA spend.
How do you get TaloTrace for your release process?
Most tiers are published and buyable directly, see the pricing page for current plans, or book a demo if you want to walk through how it would fit your release process before committing.
If your team already tracks issues in Jira, Linear or GitHub, export can be turned on per project. It's off by default, and a Finding can only be exported once it's passed review, so nothing lands in your tracker unverified.
Frequently Asked Questions
Does TaloTrace replace manual QA testing entirely?
No. TaloTrace explores your app, drives each journey to a verifiable outcome, and independently reviews what it finds before it reaches you. Your team still decides what ships; TaloTrace's job is to make sure what reaches that decision has actually been checked, not just marked done.
What platforms does TaloTrace test?
TaloTrace runs on three cloud-hosted execution planes: a browser for web apps, an Android emulator, and an Apple iOS Simulator. The plane is chosen automatically from your app's platform, and there's no hardware to provision. Physical devices aren't offered on any platform.
How do I know a Finding is real before it reaches my team?
Every Run's results start hidden. A Finding only becomes visible once it's been independently reviewed and approved, or the project is configured to auto-approve. Low-confidence findings are held separately and can't be released in bulk by a run-level approval.
Can we set our own severity criteria instead of a generic default?
Yes. TaloTrace's five customer-visible severity levels, Critical through Trivial with their P0 to P4 codes, can be rated against a severity rubric you supply, so ratings follow your own triage guidance rather than a one-size-fits-all scale.
Does this fit into our existing ticketing system?
Findings live in TaloTrace's own issue view by default. If you want them in Jira, Linear or GitHub, export is configured per project and stays off until you turn it on, and a Finding that's already been exported gets commented on rather than filed twice.
Can TaloTrace run automatically before each release?
You can start a Run on demand any time, or set a daily or weekly recurring schedule at a wall-clock time in your timezone. A scheduled run always tests the latest finalized build, so there's no separate step to remember before you ship.
