6 Lessons from LIVE coding interview at Data and AI company
Live Coding interviews are behavioural interviews
Hey, Prasad here 👋 I’m the voice behind the weekly newsletter “Big Tech Careers.”
This week, I’m sharing tips from recent experience of my mentee clearing a LIVE coding interview round at Data and AI company
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One of my mentee recently cleared a Live Coding Interview at a Data and AI Company.
They had no idea what to expect walking into a live coding interview at a major Data and AI company and somehow came out the other side with a pass.
Here’s what they learned.
The Biggest Misconception About Live Coding Interviews
Everyone thinks a live coding interview is a technical test. It is not.
Yes, there is code involved. Yes, you are solving a technical problem. But the coding part is actually the easy bit. You are given a problem, you use AI tools to generate the code, and you work through it step by step.
So if the coding is easy, what are they actually testing?
They are testing how you think. How you communicate. How you approach a problem you have never seen before. How you behave when something goes wrong. How you explain a technical decision to a non-technical person. How you react when you are stuck.
Every single one of those is a behavioural signal.
The interviewer is sitting next to you asking themselves: is this how this person would show up in front of a real customer? Would I want them on my team? Can they handle pressure and still communicate clearly?
That is the real interview. The code is just the context it happens in.
With AI coding assistants now doing most of the heavy lifting, the technical barrier to writing working code is lower than ever. Anyone can generate a working data pipeline with a good prompt. What separates candidates is everything that happens around the code. The questions they ask. The way they explain their thinking. The calm they show when an error appears. The business reasoning behind every decision.
Prepare for that. That is what is being tested.
6 behavioral tips to apply in your next live coding interview
1. Think out loud constantly
Never go silent. This is the single most important thing.
Narrate every decision you make. Say what you are about to do before you do it. Say what you notice when you look at the output. Say what concerns you about a piece of code.
Silence reads as confusion. Talking makes you look confident even when you’re figuring things out.
2. Ask clarifying questions before touching anything
Spend the first few minutes understanding the problem properly. Ask about the business context. Ask about data volumes. Ask about quality expectations.
It mirrors how professionals actually work with clients and shows structured thinking.
3. Validate as you go, not at the end
Run code in small increments and check output at each step. Don’t solve the full problem before you start validating.
Catching issues early shows discipline and prevents compounding errors that are harder to debug later.
4. Debug out loud when things break
When something breaks, slow down and narrate your debugging process.
Read the error message out loud. Name the root cause. Explain your fix before you apply it.
Interviewers care more about how you handle failure than whether everything runs perfectly first time.
5. Connect every technical decision to a business reason
Do not just say what you are doing. Say why it matters. “I am removing duplicate records to avoid double counting revenue.” “I am using a left join to keep all customers even if they have no orders.”
This is the difference between someone who codes and someone who solves business problems with code.
5. Pilot your tools, don’t just use them Whether it’s AI, documentation or Stack Overflow — always audit the output. Catch things that look wrong, explain what the code is doing in your own words, and push back when something doesn’t make sense. Showing critical judgment over tools is what separates strong candidates from everyone else.
6. Vibe code with intention
AI assistants are fair game. Use them. But catch the things that look wrong. Explain what the code does in your own words. Push back when something doesn’t make sense. Identify opportunities to optimize the code.
The candidates who impress are the ones who direct the AI with specific, detailed prompts and then audit what comes back. Vague prompts produce vague code.
Showing critical judgment while using AI to generate code is what separates strong candidates from everyone else.
Final Thought
The interviewer is not trying to catch you out. They want to see a future colleague in action. Stay calm, keep talking, and show them you can think clearly under pressure.
That is all they are really testing.
My mentee was not a data engineer and had minimal experience with data analytics going into this interview. If someone like them can clear it, technical skills are clearly not the main concern.
What they showed was simple. They worked through an unfamiliar problem methodically. They communicated their thinking at every step. They treated the interviewer as a collaborator to solve the problem together.
That is what the interviewers look for. Someone who can sit across from a customer, navigate ambiguity, and get to a solution without falling apart. The coding is just the vehicle. The behaviour is the test.
Here is what I covered in the full-day, 8-hour bootcamp on AI-Powered Big Tech Interview Prep for Tech ICs and Leaders!
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