Skip to content
ElementaryMBA
Browse Catalog
Live
Instructors
Sign in
☰
←
Building an AI-Powered Product or Service
Lesson 13 of 13
Lessons
1 · From a validated need to a product idea
2 · Build vs. buy vs. no-code
3 · Designing the experience (UX) around AI
4 · The human-in-the-loop (your quality and trust engine)
5 · Practice: design and build choices
6 · What it costs to run (tokens, subscriptions, unit economics)
7 · Pricing an AI product or service
8 · Quality and trust: handling wrong answers, disclosure, and support
9 · Legal and ethical basics (privacy, copyright, honest claims)
10 · Launching small and getting feedback
11 · Protecting your brand from AI slop
12 · Capstone: your one-page AI product plan
▸
13 · Check your understanding
13 · Check your understanding
↗
Share
1. What's the right order when turning a validated need into an AI product?
Pick a cool AI tool first, then find a use for it
Need first, AI second — aim AI at the job it can do reliably, with you accountable
Build the biggest version possible to look impressive
Skip the customer and trust the model
2. Your idea is 'when a request comes in, summarize it and draft a reply.' Which build path fits the first version best?
Build a custom model from scratch
No-code / low-code with an AI step in the middle
Hire an engineering team immediately
Nothing — it can't be built
3. Why does 'just a text box on a model' usually fail as an AI product?
Models are too cheap to run
Because the product is what you wrap around the model — expectations, control, sources, and a graceful failure
Because users prefer no instructions
Because AI is always right
4. What does 'human-in-the-loop' mean, and when is it most required?
A human writes everything; AI is never used
A person checks/approves AI before it ships — most required for anything a customer relies on or that's irreversible
The AI supervises the human
It only applies to big companies
5. Why can an AI feature that's 'free' in testing become a real bill at scale?
APIs charge a one-time fee
You pay per token (input + output) on every call, for every customer — so cost grows with usage
Testing always costs more than production
AI tools never charge for usage
6. In pricing an AI product, what sets the floor and what sets the ceiling?
The floor is whatever competitors charge; the ceiling is unlimited
Your cost-to-serve sets the floor; the value you deliver to the customer sets the ceiling
There is no floor; price as low as possible
The model's name sets both
7. Which approach to a possible AI wrong answer BUILDS trust?
Always answer confidently, even when unsure
Make uncertainty visible, verify what matters before it ships, and let customers correct/report it
Hide that AI was involved
Remove all ways to reach a human
8. What does the FTC say about claims that your product 'uses AI' or about what your AI can do?
You can say anything as long as it sounds impressive
AI performance claims must be truthful and substantiated; 'the AI said so' is not a defense
Only claims about price are regulated
Claims don't matter for small businesses
9. Can you copyright a logo you got from a single AI prompt, according to the U.S. Copyright Office?
Yes — anything AI makes for you is automatically yours
Purely AI-generated output isn't protected; copyright needs human authorship, and prompting alone isn't enough
Yes, if the prompt was detailed
Only if you paid for the AI tool
10. What's the goal of a small first launch of an AI product?
To go viral immediately
To learn fast and cheap with real users whether it solves the problem — then scale what's proven
To avoid ever talking to customers
To ship the most polished version possible before anyone uses it
Submit answers
Sign in to track your progress
← Previous
13 lessons to finish
🐞 Report a problem