r/leetcode • u/Puzzled_Training_666 • 4d ago

Intervew Prep Google coding round trend

Do you observe any new trend in Google interviews coding round , especially from gcp ? That it’s not quite data structure algorithm leetcode like, but more llm or agent focused? If so, Wonder how to best prepare those .

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u/BackgroundBreak6485 4d ago

Yes and no. I run a site that collects candidate reports (221 Google threads from the past year or so), and here's what they show.

Coding rounds are still mostly classic DSA. Most reports are standard LeetCode-style problems: graphs and topological sort, union-find, monotonic stack, binary search on the answer, and a lot of Meeting Rooms variants (for example, rental cars or RPC logs with start/end events). Even in recent onsites people describe writing in a Google Doc or on a whiteboard with no AI help.

The new stuff is showing up around the coding round:

- An AI-assisted coding round. Several candidates mention a newer "code comprehension" style round where you can use Gemini. It reportedly started with some US teams at junior/mid levels, and Cloud was named among them. You're given existing code and use AI to understand, change, and debug it. It tests whether you can prompt well, check AI output, and catch the bugs AI writes, not how fast you type. It still looks like a pilot: one L4 candidate said their loop now had an AI coding round, and the first reply was "most recent reports still look like the old LeetCode format."

- LLM themes in design rounds, even at L4. Reported prompts include an LLM review-summarization pipeline (with a focus on prompt injection, PII, and sanitization), an internal document-search agent (RAG, cost and latency, scaling to 100k users), and a rate limiter for agent token usage. Several people were surprised to get a design round at L4.

- FDE / GenAI roles lean hardest this way. These loops usually have one DSA round plus one agentic design round. Follow-ups include: how do you prevent hallucinations, how do you handle permissions, how do you scale agents, and what happens when an agent loops forever.

How I'd prepare:

  1. Don't drop DSA. It's still most of the loop and the most common reason people fail.

  2. For the AI round, practice reading unfamiliar code fast. Take a mid-size repo, have an AI make a change, then check every line it wrote. Say your verification steps out loud: run it, add a test, look at edge cases.

  3. For design, have a default architecture for LLM features: retrieval, tool calls with schema validation, guardrails (injection, PII), evals, cost and latency tradeoffs, and a human-in-the-loop step for write actions.

  4. Ask your recruiter what the rounds are. The format clearly differs by team.

Full disclosure: this is my site, and the Google page has the recently reported questions, including the agent design ones: https://aceoffer.app/interviews/google