How to Use AI to Understand Someone Else's Code (Without Asking Them)

That Moment You Stare at Code and Feel Absolutely Nothing

It happened to me about six months into learning to code. I joined a small side project with a friend, cloned the repo, opened the main file, and just... stared. It was Python. I knew Python. But I had no idea what I was looking at.

There were decorators, weird class inheritance, something called __slots__, and a method that looped through a dictionary in a way I'd never seen before. I didn't want to bug my friend with a hundred "what does this do?" questions. So I did what any reasonable person does — I panicked quietly for a while.

Then I pasted the whole thing into Claude and typed: "Can you explain what this code does, like I'm someone who knows Python basics but hasn't seen patterns like this before?"

Five minutes later, I actually understood it. Not just what it did — but why it was written that way. That felt like a superpower.

This article is about that skill: using AI to decode unfamiliar code. Whether you inherited a colleague's project, forked something from GitHub, or you're studying someone else's tutorial code and it's not clicking — here's a system that actually works.

Step 1: Give the AI Enough Context to Actually Help You

The biggest mistake beginners make is pasting code and just asking "what does this do?" That works okay for tiny snippets. But for anything more than 10-15 lines, you need to give the AI a frame of reference.

Here's the prompt structure I use now:

That last line — "point out any patterns or techniques I might not recognize yet" — is the one that changed everything for me. Without it, the AI explains what the code does. With it, the AI also flags things like "this is using a factory pattern" or "this decorator is doing dependency injection" — stuff I didn't know I didn't know.

Step 2: Ask for a Plain-English Summary First, Then Go Deep

When I'm reading unfamiliar code, I've learned to go top-down. Start with the big picture, then zoom in. AI is really good at this if you structure your questions that way.

First prompt: get the summary.

Second prompt: break it into sections.

That second prompt is sneaky good. It forces a slower pace. When AI just dumps a wall of explanation, I zone out by the third paragraph. Making it interactive keeps me focused — and honestly, I ask more questions when I'm given the pause.

Step 3: Ask "Why" Not Just "What"

Here's the thing most people miss. Understanding what code does is the first step. Understanding why it was written that way is what actually makes you a better developer.

After the AI explains a section, follow up with:

I asked this about a memoization pattern I found in a JavaScript project once. I understood that it was caching function results. But when I asked why, the AI explained that without it, the function was recalculating the same expensive operation hundreds of times on scroll events. That one follow-up question made the whole thing click in a way I still remember.

Step 4: Get the AI to Add Comments Directly to the Code

Reading an explanation next to a block of uncommented code is harder than it sounds. Your eye has to jump between the AI's response and the code constantly. There's a better way.

Ask the AI to return the code with inline comments added:

Now you've got a study version of the code you can save, open in your editor, and read like a tutorial. I keep a folder on my desktop called "annotated examples" where I dump these. When I'm learning a new pattern, I'll go back and read through them. It's one of the most underrated study habits I've picked up.

Step 5: Test Your Understanding by Explaining It Back

This is the step most people skip, and it's the most important one. Once the AI has walked you through the code, close the explanation and try to explain it back — either out loud, in a note, or by prompting the AI to quiz you.

The first time I tried this, I was humbled. I thought I understood a React component fully. When I explained it back, the AI gently pointed out that I'd completely missed why useCallback was being used and just assumed it was a regular function. That gap would have bitten me the second I tried to modify anything.

This technique — which I now call the "explain it back" test — has become a regular part of how I work through any code I didn't write myself.

When the AI Gets It Wrong (It Happens)

AI isn't infallible. Sometimes it misreads intent, especially if the code is poorly named, domain-specific, or relies on external context it doesn't have (like what's in a config file it can't see).

Signs the AI might be off:

• The explanation doesn't match what the code actually produces when you run it
• The AI hedges with phrases like "this appears to" or "I believe this is" — worth double checking
• You paste more of the codebase and the explanation changes significantly

The fix is usually more context. Try adding the files it imports from, or describe what the application actually does. The more the AI understands the surrounding system, the better it explains any individual piece.

A Complete Workflow You Can Start Using Today

Here's the whole thing as a repeatable process:

1. Paste the code with context — tell the AI your experience level, where the code came from, and what you think it does.

2. Ask for the big picture first — get a 3-sentence summary before any detailed breakdown.

3. Walk through it section by section — ask the AI to pause between sections so you can ask questions.

4. Ask why, not just what — follow up on any pattern or approach that feels unfamiliar.

5. Request an annotated version — save it to your "annotated examples" folder.

6. Explain it back — test your own understanding by summarizing it to the AI and asking for corrections.

The whole process takes maybe 20-30 minutes for a medium-sized file. That's nothing compared to how long it used to take me to decipher unfamiliar code by Googling every syntax I didn't recognize.

You're not cheating by using AI for this. You're learning faster. The goal isn't to figure it out alone — it's to actually understand it. AI just happens to be a remarkably patient, available, and knowledgeable study partner who never makes you feel dumb for asking.

Start with the next piece of code that confuses you. Paste it in. Ask good questions. You'll be surprised how quickly it starts making sense.