AI-Assisted Coding Interview Experience — Microsoft SDE2
If you've been prepping for SWE interviews and heard whispers of an "AI-assisted coding round," you're not imagining it — and you're also not going to find much written about it. That's the gap this piece is trying to close, pulled together from real candidate accounts and interviewer feedback shared across interview-prep communities over the past few months.
The problem asked for Microsoft's AI platform org was the usual load balancer with a two-heap approach. What's different is how you're expected to solve it — how well you use AI to prompt and debug it, and fix any mistakes the model made.
Candidates are given a coding environment — often HackerRank or CoderPad, sometimes a shared repo — and told they can use any AI tool they're comfortable with, whatever they'd use on the job. The catch: you're asked not to paste the raw question into the tool. You have to translate the problem into a prompt yourself — that might be the real challenge, walking the line between rephrasing the whole question and giving a guided prompt that hands over the solution and technique.
One candidate shared the actual prompt structure they used, worth adapting into a personal template. The interviewer isn't watching to see if you can write a prompt — they're watching what happens after the AI responds, evaluating your ability to catch errors, explain code logic, and reprompt effectively while maintaining technical ownership.
What's actually being tested
Several candidates asked some version of "what are they even assessing here?" Based on the pattern across accounts, it comes down to three things:
- Reasoning ownership
- Debugging under AI assistance
- Tool fluency without over-reliance
One interviewer reportedly advised a candidate to use an IDE with an integrated AI plugin next time, rather than switching between a browser-based tool and a separate AI chat window — less friction, less context-switching, cleaner signal for everyone.
The real risk isn't the algorithm, it's the setup
The most useful account in this whole thread wasn't about the coding problem at all. One candidate's AI-assisted round nearly fell apart before it started: no HackerRank link had been sent, the interviewer shared a GitHub repo instead, the candidate didn't have AI tool credits provisioned, and repo cloning issues ate up close to 40 minutes of a 60-minute slot. The round couldn't properly happen, and the candidate was left uncertain whether it would even count.
Tips: be ready with an AI tool you're used to (Claude or Codex), and carry at least one active subscription.
This isn't just a Microsoft thing
Industry coaches tracking interview formats note that Meta introduced an AI-enabled coding round last year (running on CoderPad rather than VS Code), and similar formats have appeared at Canva and LinkedIn. The direction is fairly clear: as AI-assisted development becomes normal on the job, interview loops are starting to test for it directly, rather than pretending engineers still write every line unaided.
Why this matters for how people prep
That gap — real hiring formats moving faster than real prep tools — is exactly the problem emerging assessment platforms are starting to address: evaluating how candidates reason with AI, not just whether they can produce correct answers independently. Good prompting and debugging with these tools matters significantly.
A candidate's actual experience (shared on Reddit)
The interviewer asked them to use any comfortable IDE. They used HackerRank and switched between that and Claude. They received a load balancer problem via a HackerRank link but were instructed not to copy-paste the entire question into their tool. After paraphrasing the problem, they prompted Claude to use two min-heaps. The interviewer focused on observing their questioning, debugging approach, error identification, and reprompting effectiveness. It proved less intimidating than anticipated.
Interviewer tip: use VS Code with the Claude plugin instead of switching between applications — though the candidate questioned how that would work with hidden test cases.
Pre-interview expectations, from the recruiter:
- Any AI tool allowed (GitHub Copilot, Claude, ChatGPT)
- Questions could range from LeetCode-style to systems engineering (e.g., rebuilding GitHub)
- Consider hardware/software limitations, distributed systems, performance, reliability, scaling, caching, traffic management, users, machines, and data volume
Originally published on Medium.