Technical interviews — coding interviews for software roles, case interviews for consulting and strategy roles, and financial modeling interviews for finance roles — test a fundamentally different set of skills than behavioral interviews. They reward specific preparation approaches that many candidates do not know about, and they penalize the same good faith general preparation that works well for behavioral interviews. Here is the honest guide to technical interview preparation.
Coding interviews at major technology companies (FAANG and most tech companies above a certain scale) follow a format where candidates solve algorithmic problems on a whiteboard or shared coding environment under time pressure. The most reliable way to prepare: systematic practice on LeetCode, HackerRank, or AlgoExpert, starting with Easy problems, moving to Medium, and targeting Hard for senior roles. The specific preparation mistake most candidates make: practicing randomly across all problem types. The effective approach: pattern recognition — most coding interview problems fall into a limited set of patterns (two pointers, sliding window, binary search, BFS/DFS, dynamic programming, heap/priority queue). Recognizing which pattern applies to a given problem is often more important than knowing the implementation from scratch. Resources that focus on pattern recognition (Neetcode.io's structured roadmap, AlgoExpert's pattern-based curriculum) are more efficient than random problem practice.
The most important and most underemphasized technical interview skill: narrating your thinking process while solving. Interviewers at major technology companies are explicitly evaluating your thought process, not just your solution. A candidate who arrives at a correct solution silently gets less information about their thinking than a candidate who narrates their approach, identifies trade-offs, considers alternative solutions, and explains their reasoning even when the final answer is wrong. The think-aloud approach: state your initial understanding of the problem, ask clarifying questions (edge cases, input constraints, expected output format), describe your first approach and its time/space complexity, ask if that approach is acceptable before implementing, implement while narrating, and discuss optimizations afterward.
Case interviews (used by consulting firms like McKinsey, BCG, and Bain, and increasingly by strategy teams at tech and finance companies) present a business problem and ask candidates to work through an analysis live. They test structured thinking, quantitative reasoning, and the ability to communicate an organized analysis under time pressure. Preparation resources: Case In Point (book by Marc Cosentino), the consulting firm case libraries available on their websites, and case partners for practice (websites like PrepLounge connect practice partners). The critical skill: building and applying frameworks — not memorizing frameworks but developing the ability to construct an appropriate analytical structure for each specific problem type presented.
Honest Bottom Line: Coding interview preparation requires systematic pattern recognition practice (Neetcode.io roadmap is efficient) rather than random problem volume. Think-aloud narration of your problem-solving process is explicitly evaluated and often matters more than solution correctness — practice narrating your reasoning as much as coding the solution. Case interview preparation requires framework construction skill built through deliberate practice with a case partner — memorized frameworks without flexible application fail when the case does not fit the template. Both formats reward specific preparation approaches that generic interview advice does not address.