What FAANG means and how to prepare for coding interviews
Learn what FAANG stands for, which companies it refers to, and how to build a coding interview plan around skills, role requirements, and recall.
What does FAANG stand for?
FAANG stands for Facebook, Amazon, Apple, Netflix, and Google. Facebook is now part of Meta, and Google is part of Alphabet. The familiar acronym uses the historical names. Nasdaq's explanation of the term describes its origins as a stock-market grouping.
| Letter | Historical name | Company context |
|---|---|---|
| F | Meta | |
| A | Amazon | Amazon |
| A | Apple | Apple |
| N | Netflix | Netflix |
| G | Alphabet is Google's parent |
In interview preparation, people often use FAANG more loosely to mean major technology employers. Microsoft, Nvidia, OpenAI, and Anthropic are not letters in the original acronym. If you are searching for stock analysis, this article does not cover that subject. The rest of this guide concerns software engineering interview preparation.
There is no universal FAANG interview
Start from your actual role and recruiting instructions. An early-career coding interview, a senior distributed-systems discussion, and a machine-learning research interview test overlapping but different skills. An identical study checklist for all three would waste preparation time.
For example, Amazon's official software development topics cover programming, data structures, algorithms, design, and other technical areas. The page recommends asking your recruiting contact which subjects are relevant to your interview. Use that principle when planning for any employer: verify the format instead of treating the acronym as a syllabus.
Ask what kind of coding environment to expect, which language you can use, what areas are in scope, and whether separate design or behavioral sessions are planned. Save those answers next to your practice plan. If your invitation changes, revise the plan rather than finishing an irrelevant checklist.
Diagnose the skill that is actually missing
Try a short problem without an explanation, then classify the first point where you get stuck. Choose your next action from the failure, not from a company logo beside a question.
| Observed difficulty | Next practice step | Evidence of improvement |
|---|---|---|
| Cannot choose an approach | Compare brute force with one relevant pattern | Explain which constraint makes the pattern useful |
| Know the idea, forget the code | Reconstruct critical lines from memory | Implement again later without opening the solution |
| Fail boundary cases | Trace the smallest counterexample | State the invariant and test both sides of a boundary |
| Correct code, unclear explanation | Talk through a timed solution | Explain assumptions and complexity without reading notes |
| Weak design discussion | Practice requirements, trade-offs, and failure modes | Defend a decision when a constraint changes |
A worked example: configuration history
Original practice scenario: configuration revisions are [(2, 'green'), (2, 'blue'), (8, 'red')] in chronological order.
For each query time, return the last revision at or before it.
When times are equal, the later entry wins.
Queries [1, 2, 7, 8] should return [null, 'blue', 'blue', 'red'].
The interesting boundary is the first revision strictly after the query. Its predecessor is the answer, unless the insertion position is zero. This is an upper-bound binary search. Choosing the first matching timestamp would incorrectly return green for time 2.
Before coding, explain why an exact match is not enough when timestamps repeat. After coding, test an empty history, a query before the first revision, and a query after the last revision. Then hide the answer and rebuild the search condition. Use the binary-search guide to review the boundary reasoning, and Binary Search for an existing practice problem. These are skill exercises, not claims about questions asked by a FAANG company.
Build a two-week plan from your diagnostic
- Days 1-2: baseline. Attempt array, hash-map, and search problems without hints. Record the specific failure and your explanation quality.
- Days 3-5: repair foundations. Study only the patterns needed to fix those failures. Trace examples before repeating implementation.
- Days 6-8: recall and variation. Rebuild previously learned solutions, then change the input or output contract.
- Days 9-11: role-specific work. Add design, practical coding, or another area confirmed by your recruiter.
- Days 12-14: rehearsal. Practice explaining, testing, and revising a solution under a realistic timebox.
This is an example schedule, not a promise that two weeks is enough. If foundational work is still difficult, extend that phase. If your role is primarily frontend, data, or research, replace irrelevant algorithm sessions with representative work.
Measure readiness with observable behavior
Count successful independent attempts, not pages read or videos watched. For each practice session, record whether you clarified the input, produced correct code, explained complexity, and handled a follow-up. Use AlgoDrill's interview course for a structured learning path and recall practice for solutions you understand but cannot reconstruct.
AlgoDrill does not replace mock interviews, a full system-design curriculum, or an employer's own guidance. Its role in the plan is to help you practice retrieving the coding details that disappear when the explanation is hidden.
Sources and scope
Checked November 2, 2026: Nasdaq on the FAANG acronym and Amazon's software development interview topics. The diagnostic, configuration example, and suggested schedule are original AlgoDrill teaching material. AlgoDrill is not affiliated with the companies named here and does not claim access to their private interview banks.
Learn the pattern, then drill it from memory.
Read the guide, practice the critical lines, and track the parts you miss. Every AlgoDrill pattern guide connects directly to drillable problems.
Start with pattern guides Try a free Two Sum recall drill