A testing agent is only as good as its failures
A red row with a screenshot assumes a human will interpret it. A usable failure states what was attempted, what the application did, and where those diverged, in a form the fixer can act on without reconstructing the story.
This matters twice over when the fixer is a coding agent, which cannot look at a screenshot and infer intent. Ask to see a real failure, not a passing run.
Two: whether the check can fail
Break something on purpose during evaluation. A save that no longer persists, a filter that silently returns everything. If the check stays green, it was never connected to your product.
Two ways this goes wrong. A check too vague to have an outcome, and a run that times out before reaching its assertions and reports as a pass. The second is worse because it looks like coverage.
Three: whether it runs without being asked
On demand only. Useful during a session, invisible afterwards.
On change. Triggered by a pull request or a deployment. This is the one that protects you.
On a schedule. Catches environment drift and external dependencies moving.
A testing agent that only acts when addressed is a better manual tester, which is worth something and is not what you were buying.
What to watch in the first week
Beyond the three properties, there are two behaviors in week one that predict whether this works out.
Does the coverage it creates reflect your product or the shape of your specification. An agent working from an API document will faithfully cover every endpoint including the ones nobody uses, and miss the one rule that lives in a comment. Reading the first plan tells you which you have, and correcting it early is much cheaper than correcting it at two hundred cases.
And does anybody read the failures. A testing agent produces more signal than a manual process, and signal that nobody consumes is just cost. If after a week the failures are being acknowledged rather than investigated, the problem is usually the failure format rather than the team, and it is worth raising before the habit sets.
The evaluation in half a day
Describe three flows. Break one thing. Merge something. If it catches the break, reports it usefully, and notices the merge without being asked, it is doing the job. If any of the three fails, no feature list compensates.
Terminal
npm install -g @testsprite/testsprite-cli
testsprite setup
If you would rather not install anything, the dashboard does the same thing. Everything else the command line can do is in the CLI repository.
The trigger matters more than the mechanism. Pointing it at your deployment event means every change is checked without anyone deciding to; the GitHub App does that from the dashboard, and a GitHub Actions step does it from inside your workflow.
How TestSprite answers the three
A failure returns as what was attempted, what the application did, and where those diverged, in a form a coding agent can act on without a person interpreting it first. Checks assert on something specific and a run that never reached its assertions is not reported as a pass. And it runs on the change: connect a repository and runs start from the deployment your pipeline already produces.
Coverage is generated from your product and refined in plain language, and setup installs the verification skill into the coding agent you already use, so creating and running a check happens inside the work rather than beside it.
What you get is the half-day evaluation passing: it catches the break, reports it usefully, and notices the merge without being asked.
What is the difference from a test framework?
A framework executes what you specified. An agent decides what to check and can iterate on the result, which is where the leverage is and where the review burden appears.
Does it need access to our code?
It verifies the deployed application through its interface. Your coding agent already has the code.
How much review do generated checks need?
Read the plan before the first run and treat new checks like code. Volume without review is the main failure mode.
Can it fix the bugs it finds?
It can hand a usable failure to a coding agent, which then proposes a fix that gets verified the same way. The loop closes; the judgement stays with you.
What does it cost to run?
Runs consume credits, so set expectations before a long session. An agent with a verification tool will use it.
Failure format, falsifiability, trigger.
A testing agent is worth having when a failure is usable by whoever fixes it, when its checks can be made to fail, and when it runs without being asked. Test all three in half a day rather than comparing feature lists.