Lesson 198 of 1570
AI Pet Namer Capstone
Use everything you've learned to design the ultimate pet-naming AI.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1Final Boss: Build the Pet Namer
- 2prompt engineering
- 3temperature
- 4evaluation
Concept cluster
Terms to connect while reading
Section 1
Final Boss: Build the Pet Namer
You have met prompts, tokens, temperature, bias, and hallucination. Now you put it all together. Your mission: build a prompt that names pets better than any random person on the internet. Let's go. 🐶
- 1Decide what the AI needs to know (animal, color, vibe)
- 2Write a role + task prompt
- 3Pick a temperature (hint: go high for creativity)
- 4Test it with three different pets
- 5Refine based on which names feel right
Interactive
Build a prompt
Build your Pet Namer prompt. Aim for 5 fun names per pet.
Goal: make it A reusable pet-namer prompt with a clear format and creative range.
Drag blocks here, or tap + on a block.
AI Preview
Nothing yet…
Empty prompts just confuse the AI.
Interactive
Temperature dial
Try your prompt on a sample pet (orange tabby, chill vibes). Compare temps.
Question to the AI: Describe a dog.
Temperature: 0.50 · Playful
AI response
“A dog is a tail-wagging sidekick who thinks the mail carrier is a villain.”
Low temperature: the AI picks safe, likely words. High temperature: it picks weirder, less likely words. Same question — very different vibes.
Evaluate like a pro
- Are the names actually different from each other?
- Would a kid say them out loud and smile?
- Any names that feel stereotyped? Push back on those.
- Would you use any of these in real life?
Interactive
Hallucination hunt
Your AI suggested these 'fun facts' about each name. Which are real, and which did it make up?
Garfield is a famous orange cartoon cat from a comic strip.
The name Biscuit was the top pet name in France in 1742.
Mango is a fruit that grows on mango trees.
Every cat named Kevin is legally required to wear a tiny hat.
4 statements unanswered
Key terms in this lesson
The big idea: you just used role, task, format, temperature, and bias-checking all at once. You didn't just learn about AI. You used it like a builder. That's the whole Tendril move.
End-of-lesson quiz
Check what stuck
15 questions · Score saves to your progress.
Tutor
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