57 articles
Master system design interviews in 2026 using the RADIO framework across seven canonical problems — URL shortener, Instagram, WhatsApp, Netflix, rate limiter, and key-value store. Aimed at engineers preparing for FAANG and senior-level rounds.
Master data structures and algorithms for tech interviews in 2026 by learning 14 core patterns that solve 90% of LeetCode problems, with a structured 90-day study plan. Built for engineers targeting FAANG and top-tier coding rounds.
Write a software engineer resume that survives ATS filters and earns interviews at FAANG companies in 2026, using the XYZ bullet formula, proven section structure, and before/after examples for junior and senior engineers.
Ace behavioral interviews in 2026 with the STAR method, a full breakdown of Amazon Leadership Principles, a reusable story bank framework, and word-for-word answer examples for the 10 most common questions. For engineers targeting FAANG and senior-level roles.
Negotiate your software engineer salary effectively in 2026 with total compensation breakdowns, word-for-word negotiation scripts, equity negotiation tactics, and market rate data for US and India. For engineers at all levels who want to stop leaving money on the table.
A complete pattern guide to arrays and strings problems from LeetCode used by Google, Meta, Amazon, Apple, and Microsoft. Covers prefix sum, Kadane, two pointers, sliding window, hash maps, and Dutch flag in Python and JavaScript.
Master every binary search pattern used at FAANG interviews — classic exact match, left and right boundary, rotated array, binary search on answer, parity, and 2D matrix — with copy-pasteable templates and a 23-problem index.
The complete Binary Search interview cheatsheet covering all 7 patterns, the universal template, Binary Search on Answer playbook, complexity reference, and MAANG priority order. Bookmark this for the day before any FAANG interview.
Master BFS and DFS on graphs and grids with the seven core patterns that show up in 90 percent of FAANG graph interviews. Learn flood fill, multi-source BFS, shortest path on unweighted graphs, and connected components with Python and JavaScript code.
Master Clone Graph (LeetCode 133): a FAANG favorite that tests BFS, DFS, graph traversal, hash map state, and cycle handling. We trace it step by step, derive the optimal pattern, and fortify you against the classic mistakes interviewers love to spot.
LeetCode 547 Number of Provinces is the canonical connected-components question. Learn the DFS, BFS, and Union Find solutions, master the adjacency-matrix walk, and rehearse the FAANG interview script.
LeetCode 126 Word Ladder II asks for every shortest transformation path between two words. Master the layered BFS plus parent-map DFS pattern that survives the brutal time limits at Amazon, Google, and Facebook interviews.
LeetCode 815 Bus Routes is deceptively hard. The trick is that BFS levels count buses, not stops, so the graph you traverse is a route graph. Master the stop-to-routes inversion that beats the time limit at FAANG interviews.
LeetCode 886 Possible Bipartition reduces a real-world group split to a bipartite check. Master the BFS 2-coloring, DFS coloring, and Union Find variants that recruiters expect at FAANG.
LeetCode 785 Is Graph Bipartite asks whether you can 2-color a graph. Master the BFS and DFS coloring patterns, the disconnected-component handling, and the FAANG interview script that proves you understand bipartite theory.
LeetCode 1654 Minimum Jumps to Reach Home looks like a number line puzzle, but it is a graph traversal in disguise. Master the state space BFS where direction is part of the node identity, plus the upper-bound trick that beats the time limit.
LeetCode 399 Evaluate Division turns equations like A/B equals 2 into a weighted graph. Master the BFS, DFS, and Union Find solutions plus the FAANG-grade interview script.
LeetCode 882 Reachable Nodes in Subdivided Graph blends Dijkstra with an edge-budget counting trick. Master the optimal pattern that interviewers at Google and Amazon use to filter senior candidates.
A complete FAANG-ready guide to greedy algorithms and monotonic stacks: interval scheduling, exchange arguments, next greater element, histogram problems, and trapping rain water patterns.
Complete master recap of the Heaps and Priority Queues section. Covers 7 core heap patterns, complexity tables, and a full FAANG-style problem index for systematic interview preparation.
The complete system for FAANG mock interview preparation: a 5-week progressive schedule, the UMPIRE problem-solving framework, a 6-axis scoring rubric, and a self-graded session tracker that converts practice into real interview performance.
Week 1 of the FAANG mock interview program pairs easy and medium problems from arrays and trees. The goal is not ceiling testing — it is installing the think-aloud habits that distinguish passing candidates before difficulty ramps up in week 2.
Week 2 of the FAANG mock program pairs Number of Islands and Longest Increasing Subsequence. Solve each correctly, then deliver one optimization upgrade and handle a live follow-up question — the pattern that separates "passes" from "strong hire" ratings.
Week 3 of the FAANG mock program pairs Burst Balloons and Word Ladder II as hard problems under timed pressure. Learn the stuck-recovery protocol, the inversion insight, and why partial credit plus continuous communication beats silence every time.
Week 4 of the FAANG mock program runs full company-specific simulations matching the actual format, difficulty mix, and evaluation rubric of Google, Meta, and Amazon. The same problem communicated differently wins different ratings at each company.
Week 5 combines a 15-minute system design phase with a 30-minute coding implementation of one core component. This mirrors the senior-level interview format at Google, Meta, and Amazon where design breadth and implementation depth are tested together.
Raw mock practice without structured analysis does not compound. This framework covers error classification, a weekly improvement cycle, a 3-day drill pattern, and a performance tracking chart that turns each session into targeted, measurable growth.
Exact time allocation for a 45-minute FAANG coding interview covering one hard problem or two mediums. Includes the five common time traps, a stuck-recovery escalation protocol, and the 5-minute warning procedure that protects your score when you run out of time.
Master the STAR method for FAANG behavioral interviews. Covers the 10 must-prepare stories, how to connect technical decisions to measurable outcomes, answer length guidelines by interview type, and the red flags that cost candidates offers at the behavioral stage.
Map Amazon's 16 Leadership Principles to coding and behavioral interview behaviors. Includes the LP-to-question mapping, how to weave LP language naturally into technical explanations, the Bar Raiser format, and a per-LP preparation template.
Google interviews evaluate Googleyness alongside coding ability. This guide covers the 5-step coding walkthrough, the Googleyness criteria, the top 6 Google-favorite algorithm topics ranked by frequency, and the rubric interviewers use to score each round.
Meta's interview format is the most speed-intensive of the major FAANG companies: 4 problems in 70 minutes across two coding rounds. This guide covers Meta's core values evaluation, the speed techniques that matter, the practice problem set with time targets, and the impact framing Meta rewards.
A repeatable 45-minute framework for FAANG system design interviews covering requirements gathering, capacity estimation, high-level architecture, component deep dive, and trade-off discussion. Includes a vocabulary reference and a complete Twitter design walkthrough.
The 15 most common coding interview mistakes that cost candidates FAANG offers. Each mistake includes the root cause, what it signals to the interviewer, and the exact fix to apply in your next mock session.
The complete 7-day countdown plan for the week before a FAANG coding interview. Daily focus areas, what to review, what to skip, how to peak on interview day, and a pre-interview checklist covering logistics, mindset, and warm-up protocol.
The complete interview readiness reference: pattern recognition guide, complexity cheatsheet, STAR story index with LP mapping, UMPIRE checklist, company quick reference, and the three closing mindset principles that carry candidates through FAANG loops.
Master 21 LeetCode design problems frequently asked at Google, Meta, Amazon, and Apple — LRU/LFU caches, Twitter feed, hit counter, autocomplete and more, all built from first principles.
The complete binary tree interview playbook for 2026 — 9 patterns, ready-to-paste DFS/BFS templates, and a curated index of 75 LeetCode tree problems asked at Google, Meta, Amazon, Apple, and Microsoft.
LeetCode 211 walkthrough — implement WordDictionary supporting add and search where the search query can contain a "." wildcard. The optimal solution combines a trie with DFS branching at every wildcard, a textbook FAANG interview pattern.
LeetCode 212 — find every dictionary word hidden in a board. The optimal solution builds a trie over the words and DFS-traverses the grid once, pruning entire branches the moment the path leaves the trie. A textbook FAANG hard problem.
LeetCode 648 — replace each word in a sentence with the shortest dictionary root that prefixes it. The trie walks one character at a time, returning the first isEnd we hit. A clean autocomplete-style problem.
LeetCode 421 — find the maximum XOR pair in an array of integers in O(N times 32) using a binary trie. The classic introduction to bit-trie pattern that powers competitive programming and database query optimisers.
LeetCode 1268 — return up to three lexicographically smallest products for every prefix of a search query. The trie autocomplete pattern that backs Google search, Amazon product search, and command palettes everywhere.
LeetCode 720 — find the longest word in a dictionary that can be built one character at a time, with each prefix also in the dictionary. Trie + BFS gives lex-smallest tie-breaking for free.
LeetCode 336 — find every pair (i,j) such that words[i] + words[j] is a palindrome. The trie solution stores reversed words and tags palindrome-suffix indices, enabling O((N times K^2)) lookup.
LeetCode 1032 — design a class that returns true whenever the suffix of a streamed character sequence matches any dictionary word. Solved with a reverse trie and a bounded sliding buffer in O(W) per query.
LeetCode 745 — design a structure that returns the highest-indexed word matching a given prefix and suffix. The combined-key trie inserts every (suffix#word) variant, turning a 2D query into a 1D trie walk.
LeetCode 2416 — for each word, sum the scores of all its non-empty prefixes where score = number of words sharing that prefix. The counted trie pattern aggregates O(N times L) work into O(N times L) trie nodes with a count counter.
LeetCode 472 — find every word that can be formed by concatenating two or more shorter words from the same list. Trie accelerates the prefix-membership test inside a Word Break DP, turning O(2^L) brute force into O(N times L^2).
LeetCode 820 — encode a list of words into the shortest reference string where each word appears as a suffix terminated by #. Build a trie of reversed words; only words at trie leaves contribute their length plus one to the answer.
LeetCode 677 — design a structure supporting insert(key, value) and sum(prefix) returning the total of values for all keys with that prefix. The key trick is propagating delta sums along the trie path so prefix queries become a single O(L) walk.
LeetCode 2185 — count how many strings in words have pref as a prefix. The simple linear scan is optimal for a single query; the trie shines once you anticipate many queries against the same word list.
LeetCode 1707 — for each query (xi, mi), find max xi XOR nums[j] where nums[j] does not exceed mi. Sort queries by mi, sort nums, insert lazily into a binary trie, answer each query in O(32). The offline-trie pattern unlocks bounded XOR queries.
LeetCode 3043 — find the longest common prefix length between any number in arr1 and any number in arr2 (compared as digit strings). A digit trie of arr1 makes each arr2 lookup O(D) where D is the number of digits.
Map of every important trie variant you need for FAANG interviews — binary trie for XOR, reverse trie for suffix matching, counted trie for prefix scoring, offline trie for bounded queries, and the design patterns that compose them.
Count the number of distinct substrings of a string. The elegant trick: every substring is a prefix of some suffix, so a suffix trie has exactly one node per distinct non-empty substring. Count nodes during insertion in O(N^2).
Master the two pointer and sliding window patterns that drive 15-20 percent of FAANG array and string interviews at Meta, Google, Amazon, Apple, and Netflix. This guide indexes 60 problems and the techniques behind every variant.