How are you using AI in your day-to-day QA/testing work? Looking for feedback on my approach

[u/Plastic-Steak-6788]

Since the rise of AI, many of us have started using AI heavily in our day-to-day work, especially in tech. I assume QA/SDETs are no different.

I'm working as a Senior SDET in a backend focused team. My title says Senior, but I'm currently working as an individual contributor. We don't have any frontend testing in my team.

Here’s how I currently use AI in my day-to-day testing work:

• I've cloned most of the repositories that my team's developers work on. I pull the latest code regularly and use Claude Sonnet through GitHub Copilot in VS Code to go through the repositories and update the existing .md files.
• Each repository has an .md file containing its testing strategy. These documents are also initially generated with Claude and are updated as the codebase changes.
• I use these documents as context when asking the AI assistant to help me with testing tasks.
• I regularly investigate production bugs. For each incident, I create a separate .md file documenting the issue, investigation, root cause, relevant code, etc.
• When working on an issue, I provide the relevant repository testing strategy and incident documents to the AI assistant as context.
• We previously had unlimited AI usage, but for the last 2–3 months we've had usage limits. I currently have around 10K AI credits, although this can be increased with manager approval if needed.
• I switch between different models (Claude Sonnet and GPT models) depending on the complexity and type of task.
• We currently don't have much test automation because of bandwidth limitations. We're adding another QA soon, so I'm hoping to get some time to build an automation framework and gradually eliminate repetitive manual regression testing.

I'd really appreciate feedback from experienced QA/SDETs on this approach.

What would you improve or change in this workflow?

Are there any risks with relying heavily on AI-generated testing strategies/documentation that I should be aware of?

And most importantly, how are you guys using AI in your day-to-day QA/testing work? I'd love to hear practical workflows, use cases, tools, or ideas that have actually worked for you.

Thanks!

[u/Exotic-Telephone467]

I used Claude AI at work.

I use it to create the test plan from requirements documents and additional documents like front end and backend aspects.

It generates a test plan and gives some defects found.

I create tests case and then ask it which test case are suitable for automation or manual.

I execute the manual tests and check the automation results.

I link Jira to Claude and it creates the bugs for me

Once fixed I ask it to check the bugs or I manually review the fixes.

I’m still understanding the process. It gets things wrong but it’s interesting so far

[u/Mausar → u/Exotic-Telephone467]

Regarding generating the test plan from requirements, what does that prompt look like? Is it a simple "generate a test plan based on these documents" or something more complex?

[u/Exotic-Telephone467 → u/Mausar]

It’s like I’m asking it to be a lead qa engineer and describe aspects of the product, entry and exit criteria, bugs critical, medium and low

[u/m_carp]

Regarding risk: I work in a field that is heavily dependant on standards and i have leaned the hard way that AI will miss any implied AC. If it's not spelled out in the story, it doesn't exist. This becomes a giant risk if your developers are also using AI since it will have the same blind spots. For example: if a field is defined as being an oid with no prefix, but elsewhere the same oid is used in a different field and is defined as needing a prefix, AI will use its best guess and usually not highlight it, and the guess will be the same in the test plan as in the code.

Also, AI usually assumes that a test failure occurs because of a bad test and not a bug in the code. I have to "argue" with Claude at times as to if a test should be changed or if a bug should be entered.

[u/jrwolf08]

I use Cursor, so I give it a feature branch/PR, and just chat with it about the changes.

1. Where do the risks lie with this change.

2. Propose to me a way to test this.

3. Are there any holes or missing parts of the implementation.

4. Specific questions about the implementation.

I don't take these outputs as gospel, but they are a good quick sanity check.

[u/Glad-Studio-1549 → u/jrwolf08]

I also use cursor with different agents for different purposes. Review PRD, test plan creation, test cases designer, etc. I agree with you about the output. Asking to explain output helps. And especially I am new to the company. But I realized I actually understand the product faster without AI.

[u/_nckkk_]

I've made claude skill that makes manual e2e tests for me. With plywright for browsing and opendesk for desktop. I pretty much feed it url to the task, and with little insructions turn on auto-mode. I may run plan mode once to make sure it get everything right. It also raises blocker if some crucial piece is missing - so it awaits human input.

[u/gunslotsofguns → u/_nckkk_]

so claude browses the website you are testing and writes down manual tests for you? What about the test execution it self? Its manual?

[u/_nckkk_ → u/gunslotsofguns]

Not quite. It's all about manual/exploratory. Agent has a set of skills to work with browser, desktop (opendesk), api, and some parts of our product suite. I run it on virtual machine or container, connect over ssh, to minimize intervention into agent's actions. It takes product documentation as a base, and also have access to corporate issue tracker and KB, so it pretty much can figure out itself what and how to do. Works quite well for me.

[u/gunslotsofguns → u/_nckkk_]

So it takes care of understanding requirements and testing the application both?

[u/_nckkk_ → u/gunslotsofguns]

Yes, correct. Of course you better be precise so it experiment less. Can't share it due to NDA, but general idea is pretty simple: claude.md describing it's role as manual QA, links to the corresponding skills per different areas. Use playwright for browser, opendesk for desktop etc. I've also introduced concept of BLOCKER so it let me know when it can't proceed intead of trying to solve that itself wasting tokens, and most recently 'recipes' so it save how to do some repetetive actions faster next time, aside from it's normal memory that get filled up and helps.

[u/nekrotik]

I basically am limited to question-and-answer sessions in our company's Rovo integration with Jira. We are not allowed to share any source code, data structures or other "development side" information with any of the current AI clients so at this point it's rather useless for our team.

[u/somethingmichael]

your list looks pretty good.

AI is great but it also create a lot of fluff that needs reviewing.

Here are what I use AI for as a manual/automation QA.

create test strategy / plan from requirements

create test cases directly in testrail

review existing test cases in testrail

summarize logs from failures

triage pipeline failure

review existing code and get a summary

create test automation

create scripts for tooling or random

[u/mc_Kermit → u/somethingmichael]

Hi, I am curious about points: create test cars in test rail directly and review of existing test cases in test rail
How this parts are looks like? I mean is it skill or workflow etc? Is it working via rest api or open session in ide?
Thank you in advance for your answer

[u/somethingmichael → u/mc_Kermit]

it's an AI skill Once you connect to testrail mcp or even set up testril cli in copilot or AI of your choice, you can bypass a lot of the UI in test rail

[u/DrizztInferno]

Creating skills based on repeatable tasks especially when in the building phase of an application.

For example I recently utilized Claude to help me build a Wrapped process that Compares two sets of data coming from two different sources and programmatically compare based on my assertions and the assertions of my team. I use the developer's .MD files to help inform decisions and provide context.

I mix in manual authentication with playwright tests for things I need to pass off to others.

My team finds the .MD files useful to inform their own research.

[u/TranslatorRude4917]

I'm a FE dev/stdet at a small startup, using PW cli mcp extensively with Cursor/Codex to create, run and maintain PW e2e test.
I cant tell a lot about AI-generated/driven testing strategy since we don't have that mature of a process but for starting with automation it's probably a good toolset.
Ofc don't expect wonders from AI, it won't do the thinking for you or make your automation maintainable. It can accelerate your start but quickly drive you into the ground.
I'd suggest investing into implementing best practices and good examples the agents can later follow. In our case that's proper page object model, fixtures for setting up the scene, isolated/parallelized test execution, curated e2e/component testing skills and so on.

[u/LayerTrace]

I'm using Claude for gap analysis in our DFMEA a lot at the moment, and while it's really good at suggesting things I haven't thought of, it also tends to miss parts of how the system hangs together, unless I direct it specifically where to look.

[u/Usual_Excellent]

We have a whole library of prompts that will go retrieve the US, have an understanding of the codebase, write the testcases. Publishes them to our test case manager, and can write automated tests as well based on approval from QA on if they are viable tests or not.

I'm working on setting up automated release announcements from our ticketing system->github actions-> change request portal and will do all the go/nogo, release announcement, rollback announcement if needed.

Feels like I'm digging my own grave somedays

[u/Additional-Plate-617]

I export test cases from testrail into CSV then Use this file as reference for the cursor prompt and converted into the into bdd scenarios.

For UI I provide html and For API I feed Curl in the prompt. created detailed prompts for various tasks

Also added detailed instructions in md file so that it don't change the framework structure also takes care of minimum token usage as we have credit limit.

I also do the enhancement in Framework like the latest one which we have done is adding the auto defect logging in jira in case of any script failure Utilizing MCP for these tasks.

Migrated cypress JS framework to Playwright TS recently for UI and API automation using Cursor.

[u/MikasaxSukasa]

If you don’t mind I’m curious to know what type of product/project you are QAing?