The first five minutes: clarifying the problem
Ask a few smart questions and say your assumptions out loud before you draw anything.
What they’re listening for
- • Do you understand the problem before you solve it?
- • Do you ask about users, scale and the main use case?
- • Do you make your assumptions clear?
Many candidates start drawing boxes in the first minute. Interviewers usually want the opposite: a few minutes of questions, so you solve the right problem. You don't need a long list. Three or four good questions and a quick summary of your assumptions is enough.
Stiff vs. natural
Interviewer: “Let's design a URL shortener, like the ones people use to share links.”
Sounds stiff
“Okay. I will use a microservices architecture with Kafka, Redis and Kubernetes. The API gateway will send requests to the shortening service, which will store the data in Cassandra.”
Sounds natural
“Okay, fun one. Before I draw anything, can I ask a few quick questions? Who's using it: is this public, so anyone on the internet, or an internal tool? Do people need custom links or click stats, or is it just “paste a link, get a short one”? And roughly how much traffic are we thinking? My guess is way more people click links than create them, but I'd like to check.”
- “Before I draw anything” tells the interviewer you have a plan.
- Questions about users, features and traffic shape the whole design.
- Sharing your guess (more clicks than new links) shows thinking, not just asking.
- Naming tools in the first minute sounds like reciting, not designing.
How a good opening sounds
Interviewer
“Let's design a URL shortener.”
You
“Sure. So just to make sure we're on the same page: someone pastes a long URL, gets a short one back, and anyone who opens the short one gets redirected. Is that the core of it?”
Say the problem back in one sentence.
Interviewer
“Yep, that's the core.”
You
“Cool. Do links ever expire? And do we need click stats, or is it fair to leave analytics out for now?”
Agree on what's in and out of scope.
Interviewer
“Links last forever. Analytics is a nice-to-have.”
You
“Got it. And scale-wise, are we a small internal tool or a big public service?”
Interviewer
“Big public service. Say 100 million new links a month, and a lot more clicks than that.”
You
“Okay, so let me say my assumptions back. Lots of reads, far fewer writes, links never expire, analytics later if we have time. And redirects should feel instant. Sound right?”
Sum up your assumptions and check in.
Interviewer
“Sounds right. Go for it.”
Clarifying questions
- “Before I jump in, can I ask a few quick questions?”Starting without rushing.
- “Just to make sure we're on the same page…”Saying the problem back.
- “Who's using this, and for what?”Users and the main use case.
- “Roughly how much traffic are we talking about?”Asking about scale.
- “Is it fair to leave … out for now?”Agreeing on scope.
- “So my assumptions are… Does that sound right?”Summing up before you design.
Now say it out loud
Rehearse with the AI interviewer and get feedback on your answers.