4 Ways I 10xed My QA Productivity With ChatGPT (Prompts Included)

Since ChatGPT’s release in 2022, AI tools have rapidly become integral to many professionals’ workflows. From coding assistance to recipe suggestions, AI has amazed users with its capabilities. Today, AI is indispensable in boosting productivity for many QA engineers, including myself. In fact, I don’t think I can live without it.

So, in this article I’ll be sharing top use cases I’ve found working as a QA engineer that I know will boost your productivity.

1. Coding Assistant

Create Helper Class

QA engineers often spend significant time coding, particularly when developing automation test scripts or refining frameworks. Previously, if you had to create a helper class, you’d probably have to do it from scratch. Now, with AI assistance, the process is remarkably straightforward.

To generate the precise helper class you need, you need to specify three key elements.

• Type of helper: A helper to connect with PostgreSQL.
• Use case or circumstances: I will use this helper to provide and store test data for my automation test framework.
• Programming language: I'm using TypeScript.

The prompt might look like this:

Help me create a helper class to connect with PostgreSQL. I want to use this 
helper class to populate test data for my Playwright automation framework. 
I'm using TypeScript.

Just give that to chatGPT and voilà — the AI handles the heavy lifting, a helper class with a simple prompt.

Code Docs

Do you know what else can be a pain in coding? Documentation.

Writing documentation is essential for long-term project maintenance, but writing them can feel like a chore. Here’s my strategy to using AI for documentation that you could also use.

1. Grab a Function with Code Doc: Pick any function that already has code documentation. (If you don’t have one handy, you might need to write it yourself first — just this once! That’ll give the AI a base to work from.)
2. Feed It to the AI: Send the function and its code doc to the AI. Then, tell it to create similar documentation for other functions or methods you want to document.

And just like that, you have clean, consistent docs in no time! It’s a small effort upfront, but it saves so much time when you don’t have to start from scratch every time.

2. Drafting a Bug Ticket

Every QA should create bug tickets every day, right? Drafting descriptions, attaching evidence, and setting up the format — are tedious tasks. But not anymore. AI makes the entire process much more efficient.

To draft an effective bug ticket with AI, you need to be clear about:

• Tool you use. Mention if you’re using JIRA or another platform to help format the ticket to fit the tool.
• Structure do you need: Include sections like title, description, steps to reproduce (STR), expected result, actual result, environment, impact, priority, and severity.
• Issue Overview: Provide a brief overview, such as. “Google Translate has an issue where it can’t translate from English to French.”
• How to reproduce the defect: This one’s key. Your app might not be as popular as Google Translate, so it might not know the details of your app. Help it by providing clear steps.
• Environment: Mention the environment, like “UAT environment” or “Production,” so it’s easier for others to replicate.
• The Impact: Explain why it matters. For instance, “This feature is essential because many users rely on it. We need to resolve this before our release in five days to avoid impacting the user experience.”

Here’s what an effective prompt might look like

Please create a bug ticket for an issue found in JIRA. The structure 
should include title, description, steps to reproduce, expected result, actual result, 
environment, impact, priority, and severity. The issue is that Google Translate 
cannot translate from English to French. To reproduce this defect, you need to 
select English as the source language, then attempt to select French as the 
target language. Suddenly it becomes disabled. This issue occurs in the UAT 
environment. The impact is high because this translation feature is widely used, 
and we’re five days away from our next release, so a fix is needed urgently

And there you have it, AI makes drafting bug tickets a breeze. 

3. Writing Emails and Chats

After drafting a bug ticket, the next step is communication. It's essential to inform everyone involved, such as your business analyst, QA team members, or release manager. AI makes it much easier.

Here's how to create effective messages with AI

1. State the Message: Provide a summary of the message, outlining the main points
2. Identify the Recipient: Just as you would adjust your tone depending on who you’re speaking to, let the AI know who will be reading the message. This way, it can tailor the tone, level of formality, and structure based on whether you’re messaging a colleague, a senior leader, or a client.
3. Choose the style. Whether you need a formal, semi-formal, or casual tone, specifying this creates a message in your preferred style. For instance, you might want a friendly tone for a message to a teammate but a more formal approach for a client or project manager.
4. Provide context if needed. Sometimes you’ll be replying within a larger email thread, especially for long, ongoing conversations. In that case, share a bit of context with the AI to ensure your response fits naturally within the conversation.

Here’s an example:

Help me draft a formal email to my release manager, Patrick, informing him that 
I’ve identified a critical bug documented in JIRA-1123. I consider this bug a 
blocker, and with the release scheduled for the day after tomorrow, I recommend 
we prioritize a fix or discuss a potential reversion. Please include a request 
for a meeting with the development and BA teams to address this before the 
release

With just these few details, the AI takes over and crafts the message to fit the situation. You’re saving time and ensuring the message comes across the way you intended.

4. Test Case Creation

AI might not be the best tool for creating test cases, as explaining feature requirements to it can be challenging.

That being said, it’s great for brainstorming test cases that you might have missed. It’s similar to having a coding assistant acting as a check-and-balance mechanism to ensure your test cases are comprehensive.

We’ve Only Scratched The Surface

As you might have noticed, I only covered conversational AI (chatGPT), but I'm in no way exclusively endorsing ChatGPT. There are code assistant tools like copilot and other generative AI tools that will provide similar results as chatGPT with these prompts.

There's no denying, however, that AI's potential is huge! I am convinced that this AI era will transform our work in ways we are just starting to imagine. The real question is, will we adapt and harness AI to amplify our productivity and maintain our lead, or will we fall behind as others advance?

I will leave you with a quote from the CEO of one of the most valuable companies in the world. 

“AI is not just a tool; it is a profound force, more transformative than fire or electricity.” — Sundar Pichai

The decision is ours — which will you choose?