DSA vs. System Design tweet

Blind 75 is a widely used 75-problem DSA checklist that many candidates cite as their core practice set for FAANG-style coding rounds. (neetcode.io) LeetCode maintains company-tagged problem lists (for Google, Amazon, Meta and others) that recruiters and candidates use to target practice to specific interview patterns. (leetcode.com) A recent dataset analysis compiled 10,385 verified interview questions across 259 companies and concluded firms recycle core algorithmic patterns while varying emphasis by role, underlining why targeted company-tag practice matters. (dsaprep.dev) High-level and low-level system design rounds are standard at top firms and are evaluated for architecture trade-offs and SLO reasoning; open-source guides like System Design Primer and courses built by ex-Meta/Amazon interviewers are widely used to prepare for those rounds. (github.com) Hands-on portfolio projects with modern stacks — examples include Next.js/React frontends, Node/Express or serverless backends, PostgreSQL/Prisma databases, Dockerized deployments and AWS/GCP hosting — are recommended by industry tutorials as demonstrable evidence of production skills. (freecodecamp.org) Structured behavioral assessments remain decisive: Amazon’s 16 Leadership Principles and Bar Raiser process, Google’s “Googleyness” and leadership rounds, and Meta’s behavioral loops are explicitly used to evaluate communication, ownership and team fit alongside technical scores. (aboutamazon.com) Hiring patterns inside big-tech loops show coding screens often act as the early filter while system-design/product questions and behavioral interviews carry disproportionate weight in final hiring recommendations under hiring-committee or bar-raiser models. (fonzi.ai)