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Prompt Testing: A Guide for Manual Testers in AI
Prompt Testing: A Guide for Manual Testers in AI

Prompt Testing for Manual Exploratory Testers.

Charlie avatar
Written by Charlie
Updated over a week ago


Artificial Intelligence (AI) and generative AI are rapidly growing fields that can be daunting for those with a technical background. However, manual testers need to feel included in the action.

By performing prompt testing, we can help guarantee the quality of AI systems. With our input, AI systems can be made safer, more efficient, and more reliable. So, let's embrace the opportunity to contribute to this exciting and constantly evolving field!

What is an LLM Agent?

Imagine a super-powered language tutor who can hold conversations, translate languages, and even write creative content. That's what a large language model (LLM) agent is! These AI systems are trained on massive amounts of data, allowing them to generate human-quality text in response to a given prompt or question.

What is Prompt Testing?

Think of a prompt like a question or instruction given to the LLM agent. Prompt testing involves creating these prompts and evaluating the agent's responses. Essentially, you're the teacher checking the AI's homework!

Why is Prompt Testing Important?

LLM agents are powerful tools, but like any tool, they can malfunction. Prompt testing helps us identify these issues early on. Here's how:

  • Uncovers Biases: LLM agents are trained on data created by humans, and that data can contain biases. Prompt testing can help reveal these biases and ensure the agent's responses are fair and objective.

  • Ensures Accuracy: Imagine asking the LLM agent to write a news report. Prompt testing helps identify factual errors or nonsensical information the agent might generate. Even simple computations can go wrong!

  • Improves Functionality: The more we test the agent with different prompts, the better it understands and responds to our instructions.

Best Practices

Even without a technical background, you can be a valuable asset in prompt testing! Here are some tips to get you started:

  • Start Simple: Begin with clear, straightforward prompts. As you gain confidence, experiment with more complex instructions.

  • Think Outside the Box: Don't just ask typical questions. Challenge the LLM agent with unusual prompts to see how it responds in unexpected situations.

  • Focus on Meaning: Did the response make sense? Do you think it follows the intent of the prompt?

  • Report Issues: If you encounter nonsensical responses, factual errors, or biased language, report them to the development team.

Examples and evaluation methods we often use

  • Uncovering Biases:

    • Prompt: Write a product description for a toy car.

    • Evaluation: Look for gender bias in the description. Does it use stereotypical language like ❝perfect for boys❞ or ❝encourages adventurous play❞?

  • Ensuring Accuracy:

    • Prompt: Translate this sentence into Spanish: ❝The quick brown fox jumps over the lazy dog❞. (This sentence uses every letter of the alphabet)

    • Evaluation: Verify if the translated sentence accurately reflects the original sentence and uses proper Spanish grammar. You can use online translation tools to verify the agent's response.

  • Improving Functionality:

    • Prompt: Write a poem about a robot who falls in love with a human.

    • Evaluation: Does the poem rhyme and have a straightforward narrative? Does it capture the emotions of love and the difference between humans and robots?

Evaluation Methods:

  • Clarity and Conciseness: Is the response easy to understand and unnecessary fluff-free?

  • Relevance: Does the response directly address the prompt and its intent?

  • Originality: Is the response unique and exciting for creative prompts, or is it simply a repetition of information?

  • Factual Accuracy: Can facts be verified through credible sources? (For non-creative prompts)

  • Alignment with Target Audience: Does the response fit the intended audience (e.g., formal vs informal language)?


Thorough documentation is vital for effective prompt testing. By recording the prompt you used, the LLM agent's response, and your detailed evaluation, you create a valuable record for yourself and the development team. This record helps track progress, identify trends, and ensure consistency in testing. Additionally, documented test cases can be reused or adapted for future testing, saving time and effort.

Remember, clear and detailed documentation is crucial in improving the quality of LLM agents and ensuring their successful development.

The Future of Prompt Testing

Prompt testing is still evolving, as it is a collaborative effort between technical specialists and manual testers. As LLM agents become more sophisticated, prompt testing techniques will become more sophisticated, but by working together, we can ensure these powerful AI systems function effectively and ethically.

Remember: You don't need to be a tech whiz to be a valuable prompt tester. With a curious mind and a focus on clear communication, you can play a crucial role in shaping the future of AI!

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