00:00
Question 1
1/15
What best indicates that a prompt is working effectively in a business or productivity setting?

It generates detailed, formal language consistently

It leads to reliable outcomes across varied use cases or edge cases

It mirrors popular prompt templates seen online

The AI compliments your prompt structure and tone

Question 2
2/15
What’s the future of prompt writing, based on the experts' view?

AI will ask you questions and build the prompt with you

Everyone will memorize magic prompts

It’ll disappear completely

Only engineers will use prompts

Question 3
3/15
Which of the following most likely improves the factual accuracy of an AI’s response?

Asking it to cite sources for every sentence

Providing structured context and asking it to flag uncertain outputs

Telling it to “give only truthful answers”

Using GPT-4 instead of Claude

Question 4
4/15
How does strong product thinking improve your prompt design?

It aligns the prompt with user intent, edge cases, and expected outputs

It ensures your prompt always matches brand tone and style

It helps reduce token cost by trimming unnecessary language

It teaches the AI to prioritize UI/UX components

Question 5
5/15
What does “prompt engineering” mainly mean in real-world work?

Coding a new AI tool from scratch

Managing servers and APIs

Testing and improving how you ask AI to get better results

Writing essays using AI

Question 6
6/15
What separates average prompts from great ones?

Adding emojis and friendly greetings

Copy-pasting someone else’s prompt

Trying different versions and thinking of what might confuse the AI

Using the longest and most detailed instructions

Question 7
7/15
Why do philosophers make surprisingly good prompt engineers?

They like writing essays

They’re always right

They’re good at explaining things simply to anyone

They use long words

Question 8
8/15
Why is prompt engineering valuable for non-technical professionals like PMs or marketers?

It enhances clarity, ideation, and problem-solving with language models

It helps them use APIs more efficiently

It reduces reliance on developers for frontend design

It’s mainly for automating routine admin tasks

Question 9
9/15
Before spending hours tweaking a tough prompt, what should you check first?

If the AI understands the task the way you do

If the prompt has more than 500 characters

If your example was used in the prompt

If your internet is fast enough

Question 10
10/15
What’s a useful way to start a prompt when you’re unsure how to frame your request?

Ask the model to skip the explanation and give a direct answer

Begin by asking the model to analyze the problem or identify ambiguities

Insert an example output and ask it to imitate the style

Use casual, open-ended phrasing to see what the model generates

Question 11
11/15
What’s the problem with always starting prompts like “You are a helpful assistant”?

It can distract from the real task

It makes the model slow down

It’s too obvious

The AI doesn’t understand the word “helpful”

Question 12
12/15
Why is reading AI’s responses closely so important?

To copy-paste faster next time

To learn how the AI thinks and improve your prompt

To make it more human-like

To reduce your monthly usage cost

Question 13
13/15
What does it mean to “externalize your brain” when working with AI?

Ask the AI to guess your intent

Let the AI correct your grammar

Plug your brain into the internet

Write down all the context and details the AI needs

Question 14
14/15
What’s a common mistake beginners make when asking AI for help?

Asking for multiple answers in one message

Giving too many examples

Thinking everyone will type clearly and politely

Using short prompts

Question 15
15/15
What should you do if your prompt feels unclear or confusing?

Add more keywords randomly

Ask the AI to help rewrite or clarify your instructions

Just delete it and start fresh

Try again with more slang