Imagine you have been asked to manage thousands of guests searching for stays across cities, each with different check-in and check-out dates. How do you make sure no two guests are double-booked into the same home? And when demand surges, like during New Year’s Eve in Paris, how do you figure out the minimum number of listings needed to host everyone smoothly? This probably already has you thinking. It is a glimpse of the kind of practical challenges you can expect in Airbnb coding interviews.
Airbnb’s coding interviews typically emphasize practical problem-solving and clean coding style over unclear algorithm tricks. They also reflect the company’s core values: collaboration, clarity in communication, and thoughtful trade-offs often matter just as much as technical accuracy. Success comes from combining strong coding skills with a product-minded approach.
Grokking the Coding Interview Patterns
With thousands of potential questions to account for, preparing for the coding interview can feel like an impossible challenge. Yet with a strategic approach, coding interview prep doesn’t have to take more than a few weeks. Stop drilling endless sets of practice problems, and prepare more efficiently by learning coding interview patterns. This course teaches you the underlying patterns behind common coding interview questions. By learning these essential patterns, you will be able to unpack and answer any problem the right way — just by assessing the problem statement. This approach was created by FAANG hiring managers to help you prepare for the typical rounds of interviews at major tech companies like Apple, Google, Meta, Microsoft, and Amazon. Before long, you will have the skills you need to unlock even the most challenging questions, grok the coding interview, and level up your career with confidence. This course is also available in JavaScript, Python, Go, and C++ — with more coming soon!
So, how do you prepare for this uniquely blended evaluation criteria? Would you go for curated LeetCode problem lists like Blind 75 that many engineers use to target MAANG? Would you focus on Airbnb’s Top 62 questions? Or would you aim to master the underlying patterns of these LeetCode problems, which is a smarter and more adaptive way to prepare for coding interviews?
In this blog, I will put Blind 75 and Airbnb’s Top 62 questions side by side with the 28 LeetCode patterns from Grokking the Coding Interview Patterns. The goal isn't simply comparison; it's to help you create a preparation strategy that goes beyond problem lists and trains you to think in patterns, which is exactly what Airbnb’s interviews are designed to test.
Blind 75 is a curated list of 75 LeetCode problems that has become the go-to starting point for coding interview prep. It’s simple, finite, and gives you coverage of the most common data structures and algorithms. For example, it includes arrays, linked lists, binary trees, graphs, dynamic programming, and search techniques.
Airbnb’s Top 62 is a company-focused problem list, built from questions frequently reported in Airbnb interviews. It includes challenges that mirror Airbnb’s real-world needs, such as interval scheduling, graph problems, and search-based algorithms.
LeetCode patterns are 28 different reusable problem-solving strategies. Patterns like Sliding Window, Merge Intervals, or Backtracking teach you to recognize the underlying structure of a problem, so you can adapt even when the exact question is new or framed in a product context.
Blind 75 is a strong way to cover the core computer science topics, such as arrays, trees, graphs, dynamic programming, and more. It gives you the fundamentals every engineer needs. However, Blind 75 was originally built with MAANG interviews in mind, not Airbnb. While it sharpens core skills, it does not always reflect the product-driven challenges that Airbnb emphasizes.
With AI tools and shifting interview trends, questions now often come with new twists and constraints, even if the underlying logic stays the same. Static lists like Blind 75 can also make you subconsciously memorize solutions instead of truly understanding the pattern or core logic behind them. This is a critical gap, especially in Airbnb interviews, where success comes from showing adaptability, reasoning, and clarity in applying the right approach to new problem variations.
This is why relying only on Blind 75 might not be enough. It builds a solid foundation, but Airbnb interviews demand adaptability and pattern recognition that go beyond static lists.
As I mentioned earlier, every day at Airbnb, engineers grapple with real-world problems that go beyond textbook algorithms. You might find yourself designing a recommendation system that surfaces unique stays while balancing speed, fairness, and user trust. In those moments, it’s not enough to code a solution. You need to think through trade-offs, system constraints, and human impact. If you can do that, you’re on Airbnb’s wavelength.
This is where LeetCode patterns change the game. By learning the 28 fundamental patterns, such as Sliding Window, Merge Intervals, Backtracking, or Dynamic Programming, you train yourself to spot the underlying logic instead of relying on memory. Patterns teach you how to approach a problem systematically, reason through constraints, and adapt to variations.
For Airbnb, this adaptability is crucial. Consider a booking allocation challenge: it might look different from a meeting rooms problem you’ve seen before, but if you recognize it as a Merge Intervals pattern combined with a Heap, you can confidently solve it. That’s the power of patterns. You’re no longer tied to specific problems; you’re equipped to handle almost any new variation.
Preparing all 28 coding patterns at once can feel overwhelming. To make this more manageable, I have grouped them into four categories that help bring clarity and focus to your interview preparation.
Must-knows: These are the essential patterns that every candidate should master. They cover arrays, strings, trees, and graphs. Without these, you might struggle with even the most basic variations.
Very common, high-value: These patterns appear frequently because they test how you reason under constraints. Interviewers at Airbnb often look for clean solutions in scheduling, recursion, or frequency counting problems. Mastering these can quickly set you apart.
Solid but situational: These patterns may not appear as often, but when they do, they usually align with Airbnb’s product-like challenges, such as dependency resolution, search, or data organization. They are worth covering.
Finishing line helpers: These are niche patterns that rarely dominate interviews, but knowing them rounds out your preparation.
Airbnb interviews might focus more on some patterns than others, but it is still best to cover all 28. This way, you are ready for the common questions and any new variations that might show up.
Preparing for Airbnb interviews should feel focused rather than endless. A good strategy balances company-specific practice with full pattern coverage. Here is a plan I recommend:
Begin with the common ground: Work first on the problems that show up in both Blind 75 and Airbnb’s Top 62. This gives you a strong start as these problems combine general fundamentals with direct Airbnb relevance.
Dive into Airbnb’s Top 62: Next, complete the rest of Airbnb’s problem set. These questions highlight the company’s flavor of interviews, from scheduling and booking overlaps to graph-based searches. Solving them helps you get comfortable with Airbnb’s product-driven approach.
Return to Blind 75 for the missing pieces: After that, finish the Blind 75 problems that are not part of Airbnb’s list. This step widens your preparation and ensures you do not leave out important problem types that could still appear.
Close the loop with patterns: Finally, use LeetCode’s 28 patterns to strengthen any areas that are still uncovered. This step is what prepares you for the unexpected. Even if the interviewer frames a problem in a new way, recognizing the underlying pattern will help you solve it with confidence.
As you follow this plan, aim for depth in every pattern by following the rubric I introduced earlier in this series: solve at least one easy problem, two medium problems, and one hard problem. Using this benchmark adds up to 420 points across all 28 patterns. Reaching that level means you are not only complete in coverage but also interview-ready for Airbnb.
Starting with questions that overlap between Blind 75 and Airbnb’s Top 62 builds the right starting base. These problems reinforce the basics you cannot afford to miss, while also giving you early exposure to Airbnb-style challenges.
Let’s look at Blind 75 and Airbnb 62 to see how many problems overlap between the two lists.
Blind 75 (Problem Name) | Airbnb 62 (Problem Name) |
Text Justification | |
Maximum Profit in Job Scheduling | |
Flatten 2D Vector | |
Smallest Common Region | |
Pour Water | |
Sliding Puzzle | |
Cheapest Flights Within K Stops | |
Trapping Rain Water | |
Maximum Candies You Can Get from Boxes | |
Intersection of Two Linked Lists | |
Merge Two Sorted Lists | Simple Bank System |
Add Two Numbers | |
Basic Calculator II | |
Regular Expression Matching | |
Contains Duplicate III | |
Maximal Square | |
Mini Parser | |
Add Strings | |
IP to CIDR | |
Pyramid Transition Matrix | |
Convert to Base -2 | |
Robot Bounded In Circle | |
Minimize Rounding Error to Meet Target | |
Minimum Number of Flips to Convert Binary Matrix to Zero Matrix | |
Strings Differ by One Character | |
Minimum Number of Vertices to Reach All Nodes | |
Number of Ways to Build House of Cards | |
Shortest Path to Get All Keys | |
Design Excel Sum Formula | |
Subarray Product Less Than K | |
Shortest Uncommon Substring in an Array | |
Lowest Common Ancestor of a Binary Search Tree | |
Nth Digit | |
Design Circular Queue | |
Shopping Offers | |
Making A Large Island | |
Shortest Path in Binary Matrix | |
Construct Binary Tree from Preorder and Inorder Traversal | |
There are 13 problems that overlap between Blind 75 and Airbnb’s Top 62. That is a good starting point, but the real value is not in the number of problems. What matters more is how many patterns these questions introduce you to.
Let’s examine which patterns are covered through this overlap and how well they hold up against the 1-2-1 rubric. In the bar chart below, each bar represents a pattern. The length of the bar shows what percent of the full 15 points you’ve earned for that pattern, while the label highlights how many easy, medium, and hard problems went into that score.
From this overlap alone, you are introduced to 9 out of the 28 patterns, about 32%. None of them are fully covered yet, with only Sliding Window and Dynamic programming getting close, while the rest fall short of the 1-2-1 rubric. That means you still need more questions to complete each pattern.
But here is what matters: exposure itself is a big win. Once you know which patterns show up, you can intentionally close the gaps instead of preparing blindly. This shift from memorizing solutions to recognizing patterns is what sets you up for depth and adaptability in Airbnb interviews.
After the overlap, the Airbnb-only questions become the next logical step. These problems reflect challenges that are closer to Airbnb’s product context. Practicing them not only broadens the range of patterns you encounter but also sharpens your ability to apply those patterns in scenarios that mirror Airbnb’s real-world engineering problems. This is where your preparation starts to feel company-specific, building confidence for the actual interview setting.
Let’s look at the new patterns that Airbnb-specific questions introduce.
The list above shows that Airbnb-specific questions unlock 11 new patterns, taking the total from 20 out of 28 to about 71% coverage. This is a big leap. At this stage, you are not only widening your pattern exposure but also gaining clear insight into the kinds of patterns Airbnb values most in its interviews.
Now, let’s see how these patterns measure up with the 1-2-1 rubric. The bar chart below highlights the newly covered patterns in green on the y-axis.
The bar chart above shows that several patterns now reach well-covered status under the 1-2-1 rubric, including Sliding Window, Greedy Techniques, Dynamic Programming, Graphs, and Custom Data Structures. A few others, like Two Pointers, Merge Intervals, and Trie, move into partial coverage.
We also see new introductions such as Math and Geometry, Union Find, and Sort and Search, though most of these still sit below 60 percent and will need more problems to be fully covered. Patterns like Fast and Slow Pointers, Tree DFS, and Backtracking are still underrepresented with minimal progress and need your attention.
The takeaway is that Airbnb-only questions not only push previously introduced patterns toward completion but also unlock new ones. To reach full coverage, you still need to add targeted practice until each pattern meets the 1-2-1 rubric. But even partial progress matters, as once a pattern is on your radar, closing the gaps becomes a deliberate and manageable step.
The remaining Blind 75 questions play an important role in filling the gaps that Airbnb’s Top 62 does not touch. Solving these ensures your coverage is not limited to Airbnb’s core focus but extends to the full spectrum of patterns. This extra breadth is what makes you adaptable, i.e., ready not only for Airbnb’s typical problems but also for any unexpected variation that may come up in the interview.
Let’s see which new patterns this set adds to your interview preparation.
Pattern |
The remaining Blind 75 questions unlock 7 new patterns, which takes your total coverage to 27 out of 28 patterns, about 96%. This is tremendous progress and exactly what we expected from this step.
Now, let’s see how well these patterns measure up against the 1-2-1 rubric.
The chart above shows that six patterns are fully covered under the 1-2-1 rubric, while four need only an easy problem to be well covered. A few patterns, such as Bitwise Manipulation and Backtracking, are partially done and need 1–2 more problems each. The rest, such as Heaps, Tree BFS, Top K Elements, and Cyclic Sort, remain underrepresented and would need several more problems. Overall, almost every pattern is unlocked, with only targeted practice required to close the gaps.
Let’s visualize the progress so far. Let’s look at the bar chart below to see how well the 28 patterns are covered through this Airbnb-focused study plan and which areas still need your attention.
The bar chart above shows that the progress is impressive: most patterns are either fully or largely covered. But there are still some patterns that need your attention. For example, Heaps, K-way Merge, Sort and Search, and Matrices are about halfway there and would need around two additional problems each. Patterns like Linked List Manipulation, Tree BFS, Top K Elements, Fast and Slow Pointers, and Cyclic Sort are still at the very beginning and would need three problems to be fully covered.
More importantly, there is one pattern not covered at all by either Blind 75 or Airbnb’s Top 62: Subsets. This remains at zero, which means you will need to add problems yourself to complete it. A few good ones to practice are:
Pattern | Easy Problem | Medium Problems | Hard Problem |
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The pattern coverage grew step by step. The common problems between Blind 75 and Airbnb’s Top 62 gave the first big chunk, covering about 32% of all patterns. The Airbnb-only set added the most, pushing coverage to nearly 40% more and bringing many product-focused patterns into play. The remaining Blind 75 filled another 25%, rounding out coverage with patterns Airbnb does not emphasize directly, but that still matters for adaptability.
Only a very small percentage (3.6%) remained uncovered, showing how close this plan gets you to mastering all 28 patterns.
If we look at the score breakdown of this Airbnb interview prep strategy, you’ve earned 263 points out of the ideal 420. The biggest contribution came from the Airbnb-only questions (126 points), followed by the Blind 75-only set (94 points) and the common overlap (43 points). This shows that Airbnb-specific practice not only pushed pattern coverage higher but also gave the largest scoring lift.
What remains is 157 points, which may sound large but is very manageable. With the 1-2-1 rubric in hand, you can deliberately pick missing problems for each pattern to close the gap. This makes the remaining progress less about grinding endlessly and more about finishing with precision and confidence.
The smartest way to approach Airbnb interviews is to stop treating problems as isolated exercises and start viewing them as expressions of core patterns. When you ask yourself: Which pattern does this belong to?, instead of: Have I solved this problem before?, you unlock the adaptability that interviewers look for.
Working through Blind 75 and Airbnb’s Top 62 gives you a strong foundation and direct exposure to Airbnb-style challenges. Layering the 28 LeetCode patterns on top ensures that your preparation is not limited to familiar cases but extends to any new variation an interviewer might introduce.
This blended approach is what makes your prep complete. You build breadth with problem lists, depth with patterns, and confidence with practice. That combination is what will carry you through Airbnb’s interviews and help you succeed with clarity and confidence.
While this blog gives you a data-driven way to measure and close your prep gaps, the right learning tools can accelerate your progress even further. Here are two highly effective resources to complement your study plan:
Educative’s Personalized Interview Prep: It’s your tailored prep companion that adapts to your skill level and focuses on the 28 essential LeetCode patterns we’ve been discussing. You can work on the patterns that need the most attention, track progress with clear metrics, and know exactly what to tackle next. Whether it’s adding an easy problem to build confidence or a hard one to push for mastery, you’ll always be working on the right problems at the right time.
Educative’s Mock Interviews: Effective practice goes beyond solving problems. It also requires handling real interview pressure. Educative’s AI mock interviews let you simulate actual interview conditions, get actionable feedback, and improve in areas like problem-solving speed. This way, you are not only technically prepared but also confident and ready to perform under time constraints.
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