Guide

For QA engineers

What actually changes day to day, and where your judgment still matters.

Nothing here replaces test design skill. It removes the parts of the job that are pure overhead: chasing vague tickets, re-typing test cases, re-fixing brittle selectors, manually closing bugs, so more of your day goes to the testing that needs a person: exploratory testing, edge cases, risk-based prioritization.

Vague tickets stop being your problem to catch

Before a ticket reaches you, TestCatalyst can score it across six readiness dimensions: description clarity, acceptance criteria, scope, test data, auth requirements, and blocking unknowns. A ticket scored not ready gets transitioned back to To Do automatically, with an AI-written comment listing exactly what's missing. You stop being the person who has to say "this isn't testable yet" in standup. The system already said it, with specifics, before it reached you.

Drafting a suite

From Generate, point TestCatalyst at a ticket, a PRD, or another connected tracker (Trello, ClickUp, GitHub, Zoho Sprints) and it drafts a structured test suite. Treat the output as a first draft from a very fast, very literal junior tester: it covers the stated requirements well and misses the things only domain knowledge catches. That gap (negative cases, boundary values, weird user sequences, things the ticket author didn't think to mention) is where your time should go.

Prefer testing by doing rather than writing? Use Record: click through the flow once in-browser, and it becomes a structured, replayable suite, with AI suggesting a resilient selector for each step as you go.

Running tests without babysitting selectors

Kick off a run from Runs → Run Tests. If a selector breaks (a class got renamed, a button moved), TestCatalyst repairs it from a live DOM snapshot mid-run instead of failing the whole suite over something that isn't a real regression. You'll still see it noted on the run; you just won't lose twenty minutes re-recording a step because of a CSS refactor.

Bugs that don't need follow-up

A failed step files a bug automatically, with severity, steps to reproduce, and a screenshot or (for API failures) a request/response snapshot already attached. Adjust severity or add context, then push it: one action creates the Jira issue (or Trello card) and notifies the right engineer on Slack or Teams by name. When the fix ships and you re-run the suite, a bug tied to a passing test case closes itself. You never have to remember to go mark it resolved.

Where risk-based testing gets its time back

The honest pitch: generation, execution, selector maintenance, and bug bookkeeping are the highest-volume, lowest-judgment parts of the job, and they're what TestCatalyst automates. What's left for you is testing that actually requires a person:

Deciding which of the ten things that could break are worth testing before a release, given what actually changed.
Exploratory sessions where you're looking for what you didn't expect, not confirming what you did.
Edge cases that come from knowing the product's history, not from reading the current ticket.

Reporting without writing a report

Reports generates a branded document from a run or suite (Comprehensive, Exploratory, Regression, or API Test) that you can email, export to Confluence, or download as a PDF. It carries your workspace's logo and colors, not TestCatalyst's. See Reports & exports.

What's next

AI features goes deeper on the ticket-readiness pipeline and generation internals. For developers explains what your engineering counterparts see on their side of the same runs.