Use AI to Read Other People's Code (a Big Real-World Skill)

Real coding jobs are way more about READING code than writing it. Open source projects, your team's code, old code you have to maintain — you read way more than you write. AI helps you understand unfamiliar code fast.

Real examples

• 'Explain what this function does in plain English.'
• 'Walk me through this file and tell me what each section is for.'
• 'Compare these two functions — what is different about them?'
• 'I am new to this codebase. Where should I start reading to understand it?'

Try it yourself

Find a small open-source project on GitHub. Pick one file (under 100 lines). With AI's help, understand what it does. Then close the AI and try to explain the code to yourself. Notice the gaps.

When AI writes code, the temptation is to accept and move on. The trap: you have a working app and zero new skills. The fix is the 'Explain This Line' habit. Highlight one weird line, hit Copilot Chat or Cursor's inline chat, and ask 'what does this do, in plain English?'

Some examples

• Copilot writes `arr.reduce((a,b)=>a+b,0)` and you ask Cursor to break it down — now you understand reduce forever.
• Claude inserts an `await Promise.all(...)` and the explanation teaches you why parallel beats sequential.
• GitHub Copilot uses a regex; you ask 'what does each character mean?' and get a free regex lesson.
• ChatGPT uses Python's walrus operator `:=` and explaining it costs nothing but levels you up.

Try it!

Open your last AI-assisted file. Pick the three lines you understand the least. Ask the AI to explain each. Take a one-line note in your own words.

Reading other people's code is most of programming — open-source libraries, your teammate's PR, a tutorial repo. AI chatbots are surprisingly good tour guides: they'll explain function-by-function, name the patterns, and call out anything weird.

Some examples

• You paste a complex React hook into Claude and ask 'what does this do, in 3 sentences?'
• You drop a regex into ChatGPT and it explains each character class plainly.
• You feed a 200-line file to Cursor chat and ask 'what's the main entry point?'
• You ask Copilot Chat to rate the code's complexity and point out the trickiest function.

Try it!

Find a file in any GitHub repo you've never seen. Paste it into a chat. Ask for a tour. Then close the chat and try to explain it back without looking.

In any real job, you spend more time reading code than writing it. AI makes reading easy: paste a function into Claude, ask 'explain this in plain English'. Open-source projects you couldn't touch before are suddenly understandable. This is how interns 'ramp up' on huge codebases now — and how you can start contributing to real projects today.

Some examples

• Paste any function into Claude → 'explain in plain English'.
• Ask 'what does this codebase do?' with the README pasted in.
• Cursor 'Ask' mode reads your whole repo and answers.
• Find your first open-source PR — start small.

Try it!

Open any GitHub repo you've heard of. Open any single file. Paste it into Claude with 'explain this'. You just learned to read pro code.

Most professional developer time is spent reading existing code, not writing new code. AI tools turn unfamiliar repositories into something readable in minutes — letting you contribute to open source, learn from masters, and onboard at internships way faster than older developers ever could.

Some examples

• Drop a file into Claude and ask 'walk me through this like I'm new to the codebase.'
• Ask for a sequence diagram of how a function gets called.
• Have AI explain unfamiliar libraries before you use them.
• NotebookLM with a whole repo lets you query anything.

Try it!

Pick one open source project on GitHub you find interesting. Spend 30 minutes reading it with AI's help.