Candidates who clear Google loops consistently describe drilling core data structures and algorithms until fluent, then separately preparing for system design and the Googlyness round rather than treating the whole loop as one blob of prep.
A track-by-track roadmap
DSA: Google leans on graphs, dynamic programming, intervals and hashing/array problems more than pure brute-force questions, and interviewers push hard on discussing multiple approaches before settling on one. Work through the DSA Interview Questions here, practice on a plain text editor without autocomplete, and revisit core CS fundamentals — a strong SQL foundation helps too if the role touches data-heavy systems.
System Design: Structure every answer the same way — requirements, API design, data model, then caching/scaling — rather than jumping straight to boxes and arrows. See the System Design Interview Questions.
Googlyness / Behavioral: Prepare 2–3 real stories that can each answer multiple themes — ambiguity, collaboration without authority, ownership — in STAR format. See Behavioral & Culture-Fit Questions.
One recurring piece of advice across candidate reports: keep narrating your approach out loud while coding, and always walk through your finished code afterward even if the interviewer doesn't explicitly ask — silence during implementation reads poorly even when the code itself is correct.
Read real, round-by-round Google Interview Experiences to see how this plays out in an actual loop.