How to Crack Grammarly Coding Interviews in 2026

Grammarly’s coding interviews assess your ability to solve algorithmic problems under pressure, typically through a platform like CoderPad. The process often involves one or two technical rounds focusing on data structures, algorithms, and clean code. Success hinges on methodical problem-solving and clear communication, not just getting the correct answer.

By the Numbers — Difficulty Breakdown and What It Means

Based on an analysis of 26 questions, the difficulty distribution is:

• Easy: 6 (23%)
• Medium: 17 (65%)
• Hard: 3 (12%)

This breakdown is telling. The overwhelming majority of questions are Medium difficulty. This means Grammarly is primarily testing for strong, all-around competency. You must reliably solve problems involving common patterns with optimal or near-optimal solutions. The few Hard questions likely serve as tie-breakers for top candidates. Your preparation should be laser-focused on mastering Medium-level problems across the core topics.

Top Topics to Focus On

The most frequent topics are String, Array, Hash Table, Dynamic Programming, and Math. Here’s how to prioritize them.

String & Array Manipulation: These are the bedrock. Expect problems involving traversal, two-pointer techniques, sliding windows, and in-place modifications. Mastery here is non-negotiable.

Hash Table: The go-to tool for achieving O(1) lookups to optimize solutions. It’s frequently combined with other patterns, like using a hash map to store indices for a two-pointer problem or counts for a sliding window.

Dynamic Programming (DP): A key differentiator. Grammarly includes DP problems to test your ability to break down complex problems into overlapping subproblems. Start with classic one-dimensional and two-dimensional DP patterns.

Math: Often involves number theory, modular arithmetic, or clever computations. While less frequent than Arrays or Strings, a math problem can appear and test your analytical thinking.

For a top pattern like the Sliding Window (common in String/Array problems), here is a template for finding the longest substring with at most K distinct characters:

def longest_substring_k_distinct(s, k):
    char_count = {}
    left = 0
    max_len = 0

    for right in range(len(s)):
        char_count[s[right]] = char_count.get(s[right], 0) + 1

        while len(char_count) > k:
            char_count[s[left]] -= 1
            if char_count[s[left]] == 0:
                del char_count[s[left]]
            left += 1

        max_len = max(max_len, right - left + 1)

    return max_len

Preparation Strategy — A 4-6 Week Study Plan

Weeks 1-2: Foundation & Core Topics

• Days 1-7: Deep dive into Arrays & Strings. Practice all major patterns: two-pointers (for pairs, palindromes), sliding window (fixed and variable), and prefix sums.
• Days 8-14: Master Hash Tables and Linked Lists. Use hash maps to solve problems involving frequency, pairs, and subarray sums. Combine with the patterns from Week 1.

Weeks 3-4: Advanced Patterns & Problem Integration

• Days 15-21: Tackle Dynamic Programming. Start with the fundamentals: Fibonacci, Climbing Stairs, 0/1 Knapsack, and Longest Common Subsequence. Understand memoization vs. tabulation.
• Days 22-28: Study Trees & Graphs (BFS/DFS) and Math problems. While less frequent for Grammarly, these round out your skill set. Dedicate time to recursion and backtracking.

Weeks 5-6: Mock Interviews & Company-Specific Practice

• Days 29-35: Start doing timed mock interviews (2-3 per week). Simulate the real environment: 45 minutes, camera on, talking through your thought process.
• Days 36-42: Focus exclusively on Medium-difficulty problems from Grammarly's known question list. Practice articulating your approach before coding and discussing edge cases.

Key Tips

1. Communicate Relentlessly: Narrate your thought process from the moment you see the problem. Explain the brute-force approach first, then discuss optimizations. This is as important as your code.
2. Validate with Examples: Before coding, walk through 2-3 test cases, including edge cases (empty input, single element, large values). This catches logic errors early.
3. Prioritize Correctness Over Cleverness: A working, well-explained O(n²) solution is better than a buggy, silent O(n) attempt. You can always optimize later if time permits.
4. Write Clean, Modular Code: Use descriptive variable names. Extract logical chunks into helper functions (e.g., isPalindrome()). This demonstrates professional coding habits.
5. Practice on CoderPad: Get familiar with the interface. Know how to run code, add test cases, and use the collaborative editor smoothly.

Consistent, focused practice on Medium problems across Strings, Arrays, Hash Tables, and DP will build the muscle memory you need. Start your final review with the most relevant problems.

Browse all Grammarly questions on CodeJeet