How to Pass Technical Interviews Without Grinding LeetCode

Key Takeaways

You don't need to solve 500 le code problems to pass technical interviews. I know that sounds crazy, but hear me out. Now, there's this idea floating around that the only way to get hired at a top tech company is to grind le code for months, solve hundreds of problems, and basically dedicate your entire life to memorizing algorithms. And yes, some people do that, but most of them still fail interviews. And the ones who pass, they're not passing because they solve more problems. They're passing because they understand something that most people don't. Now, today I'm going to show you how to pass technical interviews without the endless grind. Now, I'm talking about a smarter approach that actually works and one that got me hired at Microsoft without solving 500 random problems. Here's what most people do when they start preparing for interviews. They go to Le Code, they see 3,000 plus problems, and they just start solving. No plan, no structure. They're just picking random problems and hoping that something sticks. You finish 50 problems and feel productive. You finish a 100red and think you're making progress. and you hit 200 and you're convinced that you're ready, but then you walk into an actual interview and you see a problem that you've never seen before and your mind goes completely blank. Why? Because you weren't learning, you were memorizing. And memorization doesn't transfer. The second an interviewer changes one small detail about a problem that you've seen before, you're lost. You didn't learn how to think through problems. You learned how to recognize specific questions and regurgitate answers. And let's be real, grinding 500 problems is exhausting. It takes months. It destroys your motivation. And by the time you actually get to the interview, you're so burnt out that you can't even think clearly. Now, I've talked to engineers who spent six months grinding lead code every single day and still failed their interviews. It's not because they weren't smart. It's not because they didn't work hard, but because they were preparing the wrong way. Now, there's a better approach, and it doesn't require you to become a leak code monk. Here's the secret the top candidates know. Almost every coding interview question is based on a small set of repeatable patterns. We're talking maybe 15 to 20 core patterns that show up over and over again across thousands of problems. Think things like two pointers, sliding window, fast and slow pointers, merge intervals, binary search variations, depth for search, breath for search, dynamic programming, backtracking, and a handful of others. Once you understand these patterns, once you really internalize how they work, and when you apply them, you can solve problems you've never seen before. You're not memorizing answers anymore. You're building a mental toolkit that lets you break down any problem into something familiar. Now, think about it this way. If you solve 500 random problems, you might see 500 different variations. But if you learn the 15 to 20 underlying patterns, you realize that those 500 problems are just different flavors of the same concepts. Let me give you an example. The twop pointers pattern alone can solve dozens of problems. Things like finding pairs that sum to a target, removing duplicates from a sorted array, checking if a string is a palendrome and a lot more. Once you understand that pattern, you don't need to memorize each individual problem. You just recognize, oh, this is a two-pointer problem and you go right into that approach. Same thing with sliding window. Once you understand how to expand and contract a window across an array or a string, you can solve problems like finding the longest substring without repeating characters, maximum sum of a subarray or you know size k etc. Right? Different problems but the same underlying pattern. Now this is why 100 well understood problems always beats 500 rushed ones every time. I've seen it countless countless times. Interviewers don't care how many problems you've solved. They care whether you can think through a new problem in real time because that's what you're actually going to do on the job. And that ability comes from understanding patterns, not from memorizing solutions. The engineers who pass interviews at Google, Meta, Amazon, they're not smarter than you. They just learn to recognize these patterns and to apply them effectively. This is the skill that you need to focus on developing. Now, let me break down the most important patterns that you need to master. These cover probably 80% of what you'll see in technical interviews. So, first two pointers. This is where you use two indices to traverse an array or a linked list, usually from opposite ends, or at least at different speeds. It's great for problems involving pairs, sorted arrays, or linked list cycles. Second, sliding window. You create a dynamic window that moves across a sequence, expanding or shrinking based on certain conditions. This is perfect for problems involving continuous subarrays or substrings. Third, fast and slow pointers. So two pointers moving at different speeds typically used to detect cycles and link lists or find the middle element. Fourth, binary search variations. Not just basic binary search, but modified versions for rotated arrays, finding boundaries or searching in infinite sequences. Fifth, depth first search and breadth first search. These are essential for tree and graph problems. DFS goes deep before exploring the siblings whereas BFS explores level by level. Sixth, dynamic programming. So, breaking problems into overlapping subpros and storing solutions to avoid redundant work. Now, this one's harder, but once you get it, you can solve optimization and counting problems very easily. Seventh, backtracking. So, exploring all possible solutions by building candidates incrementally and abandoning paths that don't work. So, this is great for permutations, combinations, and constraint satisfaction problems. Think something like Sudoku. Now, there are more. You have things like merge intervals, you know, topological sort, union, fine, tries, you know, monotonic stacks, right? But if you can nail those core seven patterns, you already cover most of the core ones you're going to see in interviews, and you're already ahead of most candidates. Now, the key here is to learn one pattern at a time. Don't try to master them all simultaneously. Pick one pattern, understand the concept deeply, and then solve five to 10 problems that use that pattern. You really need to understand why the pattern works for those problems. then you can move on to the next pattern. Now, this is so much more efficient than just randomly grinding because instead of solving 500 scattered problems, you're doing maybe like a 100 to 150 targeted problems that each reinforce a specific skill that you're actually going to retain and remember. Now, here's something that most people don't realize. Interviewers aren't just evaluating whether you can solve the problem. They're evaluating how you think, how you communicate, and how you handle what happens when you get stuck. Now, I've seen candidates who got the optimal solution, but still got rejected because they couldn't explain their reasoning. And I've seen candidates who needed hints, didn't get the perfect solution, but got hired because they demonstrated clear thinking and strong communication. Now, when you're in an interview, talk through your thought process out loud. Ask clarifying questions before you start coding. Discuss the different approaches and their trade-offs and explain why you're choosing a particular data structure. Walk through your solution with examples. Right? This is something that lead code grinding doesn't teach you at all. You're sitting alone solving problems in silence and you never practice what the actual interview skill is, right? Which is communicating your thinking in real time. Now, if you want to get better at this, you need to do mock interviews, right? Practice with friends, use free platforms like Prmp or find a study buddy, even your mom sitting in front of you, even just someone there is going to be helpful. Now, the ability to think out loud while coding is a skill, right? And like any skill, you have to practice it. Don't expect to show up to the interview and do this, you know, perfect the first time you've tried it. So, with that said, here's how I'd approach interview prep if I was starting from scratch. First, make sure your fundamentals are solid, right? You need to know basic data structures, arrays, link list, stacks, cues, hashmaps, trees, graphs, heaps, you name it. You need to understand that. You also need to know bigo notation and be able to analyze the time and space complexity. Now, if you're rusty on this stuff, spend a week or two reviewing this before you start solving problems. Second, learn the core patterns one by one. Don't solve random problems. Be deliberate. Pick a pattern, understand it conceptually, solve five to 10 problems that use that pattern and then move on. Third, do mock interviews regularly. Start doing them early. So maybe after you've done 20 or 30 problems, not just right before your interviews. You need to practice communicating your thinking under time pressure. Fourth, review and reflect. After every problem, ask yourself, what pattern was this? What did I struggle with? How can I recognize this faster next time? You know, this reflection is what actually turns practice into real learning where you're improving. You're not just doing the same thing over and over again. Now, if you're consistent, to be honest, you can be interview ready in six to eight weeks here. Most people online are going to tell you six months, but if you do this with the right approach, I promise you, and I've seen this with hundreds of people, that's all it takes to get ready. Now, that's way less than the 6 months that some people spend grinding aimlessly. Now, the key is focused, deliberate practice, not just accumulating problem counts. It doesn't matter how many problems you've done if you can't solve something new that you haven't seen before. So, that's how you pass technical interviews without grinding leak code for months. Like I said, it's not about solving 500 problems. It's about understanding the patterns that those problems are built on. It's about learning how to think through new problems in real time and about communicating your reasoning clearly. Now, the resource that I personally used to prepare for my interviews and the one that helped me get hired at Microsoft was Algo Expert. I'm going to go on the platform and I want to show you exactly why I use this because it follows the approach that I just broke down with you. Okay, so this is Algo Expert and again this is actually what I used when I was preparing for my interviews. Now, not only do they have Algo Expert, which is kind of similar to Le code in terms of the types of coding questions, but a lot more structured as you're going to see, but they have systems expert, front-end expert, ML expert, infra, iOS, blockchain, etc. So, no matter what type of niche you're getting into or if you're going for like a senior level interview, for example, you can use the same consistent platform and highquality resource to prepare for. Now, anyways, let me go through the coding interview questions. So on Algo Expert they have 200 questions as I mentioned. You can sort them by their difficulty which is right here. You can star them, right? You can strike through whatever if you've completed them. And notice that they're all categorized by pattern. So you have arrays, binary search trees, you know, binary trees, dynamic programming. And this is the way that you should approach these like I mentioned, right? So you can click into one of the problems, you can see the prompt and you can see in-depth video explanations that actually explain to you the conceptual overview behind the problem, all of the coding. If you scroll forward, you'll be able to see uh what is it the coded solution here as well. But the reason why I use this is because when you're just getting started, it's very difficult to get these solutions right and you're going to struggle even with easy problems. But if you're able to actually watch someone explain to you the intuition and how you can come up with the answer without having to just memorize it, that's what gets you better at this. Right? So when I was starting on Algo Expert, I was always going to these video explanations and referring to the official solutions that they had to make sure that I actually understood what was going on and that I was learning that intuition and that pattern recognition. If I just tried to solve the problem and I failed and went right to the solution every single time, I don't think I would have gotten as far and it would have taken me a lot longer to get better at it. Now, as well as that, they also have data structures crash course to get, you know, refreshed on those fundamentals, coding interview assessments, and then mock coding interviews as well as coding interview tips. I'm not going to go through everything. The point is guys, if you use something that is structured where you actually have good explanations and you build the intuition, you're going to cut your problem count in half because it's again not about the number of problems. It's about the quality and ensuring you're doing ones that are actually going to teach you the patterns, which is exactly how Algo Expert was designed. And by the way, at least at the time of recording this, Algo Expert is now making all of their products available under one bundle for just $119, normally nearly $700. So, if you do want to pick it up, I would recommend doing that relatively soon because again, you get literally everything, not just Algo Expert, but all of the other prep products which are extremely valuable again for some more difficult interviews you might get in that particular niche. So, look guys, that's all that I have for you in this video. Let me know how your experience has been with technical interviews and anything else you want to see on this channel.