The FAANG prep mistake that wastes your coding energy

What this guide covers

You will learn how to streamline your FAANG interview prep by focusing on core problem patterns, mastering essential data structures and algorithms, and practicing timed mock interviews—cutting out the noise so you build real coding confidence efficiently.

When to use it

• Preparing for coding interviews at FAANG or similar top-tier tech companies
• Feeling burned out from cramming dozens of random coding problems without noticeable improvement
• Struggling to finish problems within time limits during practice
• Wanting to build a strong foundation in data structures, algorithms, and system design basics to pivot into tech roles

The move, step by step

1. Identify core problem patterns. Rather than collecting every interview question, focus on common categories like arrays, linked lists, trees, sorting, dynamic programming, hash maps, and graph traversal. Use resources like LeetCode’s “Top Interview Questions” list or company-specific guides.

2. Master key data structures and algorithms. Make sure you understand how these structures work, their time and space complexities, and can implement them from scratch. For example, know how to implement binary search, breadth-first search (BFS), and quicksort.

3. Practice timed mock interviews. Use platforms like LeetCode, HackerRank, or Pramp with a strict 30-45 minute timer per problem to simulate interview conditions. This builds your ability to think and code under pressure (LeetCode official docs).

4. Cut fluff and distractions. Avoid spending time on obscure problem types or rarely used language features that won’t appear in interviews. Also, skip solutions with unnecessary code length or complexity. Aim for clean, readable, and efficient code.

5. Review solutions and learn patterns. After each mock, study optimized solutions, understand why they work, and compare them with your code. This reinforces learning and helps you spot gaps in your knowledge.

6. Repeat consistently but focused. Instead of burning out by cramming all day, schedule regular focused sessions on core topics. For example, 1 hour daily on one data structure or pattern.

Example

Input problem: Check if all elements of array arr1 appear in array arr2 (subset check).

Code snippet (Python):

def is_subset(arr1, arr2):
    s = set(arr2)
    return all(x in s for x in arr1)

# O(n) subset check

Expected output:

print(is_subset([1, 2], [1, 2, 3]))  # True
print(is_subset([1, 4], [1, 2, 3]))  # False

This shows a clean, efficient solution using set containment that’s common in interview problems.

Common mistakes

• Mistake: Trying to memorize all possible questions → Fix: Focus on core problem patterns that cover most interview scenarios.
• Mistake: Practicing without time constraints → Fix: Always simulate timed mock interviews to build real-world pacing.
• Mistake: Diving into obscure algorithm variations → Fix: Stick to fundamental algorithms and data structures first.
• Mistake: Reading solutions without coding yourself → Fix: Write your own code, then review solutions to understand improvements.
• Mistake: Overloading sessions with too many problem types → Fix: Narrow your daily focus to 1-2 topics deeply for retention.

Next step

Pick one core data structure you struggle with (e.g., trees), find 3 related LeetCode problems tagged “easy” or “medium,” and try solving them within 30 minutes each. Time yourself, then review optimized solutions. Then come back and try the next move from the video.