AI Prompting: From Zero to FAANG-Ready
Stop guessing with AI. Build a personal Prompt Library of battle-tested prompts for coding, debugging, research, and FAANG interview prep. Every lesson adds a real, reusable prompt to your arsenal.
Build it yourself, get guided when you are stuck, and leave with proof you can actually show.
What you learn by building this
- Write precise prompts that get useful outputs on the first try
- Use role and context framing to unlock expert-level AI responses
- Build a personal Prompt Library with reusable templates for coding and research
- Prompt AI effectively for DSA explanations, code review, and debugging
- Use AI to accelerate FAANG interview prep — system design, behavioral, and technical
Challenge
Think first, then write
Do This Before Reading Anything
Open ChatGPT, Claude, or whatever AI tool you use. Send this exact prompt — no changes:
explain linked lists
explain linked lists
Read what you get. Don't skip this step.
Now send this one:
I'm a CS student who knows arrays well but has never implemented a linked list.
Explain how a linked list works differently from an array, focusing on memory
and pointer structure. Use a concrete example with 3 nodes. Keep it under
200 words.
I'm a CS student who knows arrays well but has never implemented a linked list.
Explain how a linked list works differently from an array, focusing on memory
and pointer structure. Use a concrete example with 3 nodes. Keep it under
200 words.
Read that response too.
Before scrolling down: In one sentence, what's the difference between the two responses you just got?
Write your answer somewhere — a sticky note, a comment, anything. You'll come back to it.
What Just Happened
The two prompts asked for the same information. The AI isn't smarter or dumber in either case — the difference was entirely in what you gave it to work with.
Prompt 1 ("explain linked lists") leaves every decision to the AI:
- What level are you? Unknown. Assume average.
- How much detail? Unknown. Give everything.
- What format? Unknown. Pick one.
- What's your goal? Unknown. Cover the basics.
The AI hedges. It writes for a middle-of-the-road imaginary person who isn't you.
Prompt 2 gave the AI four signals in two sentences:
- Your background — CS student, knows arrays
- What's confusing you — how it's different from arrays
- What to focus on — memory and pointer structure
- Constraints — concrete example, 3 nodes, under 200 words
The AI stopped guessing and started answering your question.
This is the core of good prompting: the AI is only as specific as the information you give it. It can't read your mind. Every vague prompt forces it to fill in blanks — and those blank-fillers are almost never what you actually needed.
You're not teaching the AI anything. You're just giving it enough information to stop guessing.
Tasks
Run the Experiment Again — Your Own Topic
Pick something you actually need to understand right now. A data structure, a React concept, something from your classes — anything real.
Step 1. Write the vague version first. One line. The thing you'd normally type out of habit.
[your vague prompt here]
[your vague prompt here]
Send it. Read the response. Note what's missing or off about it.
Step 2. Now rewrite it with these four signals baked in:
- Your background (what you already know)
- The specific thing that's confusing you
- What you want to focus on
- One concrete constraint (length, format, examples)
Send the revised prompt. Compare.
Step 3. Write down this one observation: what was the most useful thing the second response added that the first one didn't?
You don't need to find the perfect prompt. The point right now is just to notice the gap — and feel how much control you actually have over what the AI produces.
Predict
What will happen?
What Would This Get You?
Look at this prompt:
how does recursion work
how does recursion work
Before you send it — predict: what will the AI probably do? Check all that apply:
- Start with a definition of recursion
- Include a code example (probably factorial or fibonacci)
- Ask you clarifying questions about your background
- Explain base cases and call stack
- Tailor the explanation to your skill level
- Cover common beginner mistakes
Now look at your predictions. Which ones involve the AI actually knowing anything about you?
That's the point. "how does recursion work" gets you the AI's best guess at a general-audience recursion lesson. Which is fine — but it's not the same as getting an answer written for someone at your level, with your gaps, toward your goal.
In the next lesson, you'll see exactly what separates prompts that get generic from prompts that get great.
How this build unfolds
Why Your Prompts Are Failing
Context and Role: The Multiplier
Prompting for Code
Prompting for Research
FAANG Interview Prep Prompts
Learn by building your own version.
Remix this public project to open the workspace, follow the guided build, and let the AI mentor teach you through the work instead of doing it for you.