If a company sanctions an AI-assisted round, preparing for it is no different from preparing for a system-design round — it's the actual test they're giving you. What changes is the skill being measured: not "can you recall an algorithm from memory," but "can you specify a problem, drive an assistant, catch its mistakes, and verify the result." This post is about preparing for that honestly. (If AI isn't sanctioned in your round, using it covertly is cheating — see how coding interviews changed in the AI era.)
A quick reality check before specifics: interview formats are evolving and vary by company, team, and role. Treat anything below as the general shape reported publicly — and always confirm your exact format with your recruiter.
What an AI-assisted round actually is
In a sanctioned AI-assisted (sometimes "AI-enabled") interview, the company gives you an AI coding assistant inside the interview environment and evaluates how you collaborate with it. Based on public reporting and candidate accounts, Meta began rolling AI-enabled coding interviews into some pipelines in late 2025, and Google has been piloting AI-assisted formats — typically: a shared editor, your choice of assistant, and a problem that's harder than a classic round because you have help. (For format write-ups, see Hello Interview and interviewing.io.) Expect this list to grow and the details to shift — verify before you sit.
What they're really grading
The rubric moves up a level of abstraction. Strong candidates demonstrate:
| Signal | What it looks like |
|---|---|
| Problem framing | You restate the problem, surface constraints, and define the interface before writing anything |
| Decomposition | You break the task into small steps and drive the assistant one step at a time |
| Critical reading | You read every line the assistant produces and catch the wrong/inefficient bits |
| Verification | You write or request tests and edge cases instead of trusting output |
| Communication | You narrate your reasoning, just like a classic round |
The anti-pattern that fails these rounds is "let the AI drive" — pasting a prompt, accepting whatever comes back, and being unable to explain or debug it. The assistant amplifies your judgment; it can't replace it.
How to prepare (the workflow)
You prepare for this by practicing the workflow, not by memorizing more solutions:
- Spec first. Take a medium/hard problem and, before any code, write the constraints, the I/O contract, and 2–3 edge cases yourself.
- Drive in small steps. Ask the assistant for one piece at a time ("just the parsing", "now the core loop"), and read each diff critically.
- Verify, don't trust. For every chunk, add a test or trace an example by hand. Assume the first version is subtly wrong.
- Refactor and explain. Tighten the code and be able to justify complexity and trade-offs out loud.
- Time-box it. Do this under 35–45 minutes so the collaboration becomes fast and natural.
Crucially, your fundamentals carry this whole process. You can't catch a wrong approach, pick the right data structure, or analyze complexity if you never built those muscles. Weak fundamentals make you a worse AI operator, not a better one — which is why the classic prep still comes first.
A two-track practice plan
- Track 1 — fundamentals (most of your time): patterns, data structures, complexity, solving out loud with no tools. Build a schedule with our free study-plan generator.
- Track 2 — collaboration reps (a few sessions/week): run the 5-step workflow above on problems you've already solved unaided, so you're practicing the driving skill, not outsourcing the thinking. (See how to use AI for interview prep — that's about studying, not in-interview shortcuts.)
The integrity line, one more time
AI-assisted rounds are legitimate because the company chose them. The same actions in a round where AI isn't sanctioned are cheating. The rule that covers every case: ask your recruiter which tools are allowed, in writing, before the interview. Then prepare for exactly that.
Bottom line
AI-assisted interviews reward the engineer who has both deep fundamentals and disciplined collaboration habits. Train the fundamentals first, layer the workflow on top, confirm your format, and these rounds become an advantage rather than a surprise.
Written by Amit Singh — Senior SDE at Amazon, Claude Certified Architect, and founder of AlgoEngineer. Our live cohorts drill both the fundamentals and the AI-collaboration workflow that these rounds test. Explore the courses.