LeetCode: How Much Is Actually Enough

TL;DR

75–150 problems done well beats 500 problems done fast. Pattern recognition is the goal.
FAANG and top-tier tech companies require more prep than most mid-size and startup roles.
LeetCode doesn't replace a portfolio. Interviewers hire the whole package, not just your algorithm speed.
If you've done 100 problems and understand the underlying patterns, you're ready to start applying.
Endless prep without applying is a form of avoidance. Set a deadline and commit to it.

The number of problems you need to solve on LeetCode is not 500. It's also not 20. And the answer isn't "it depends" either, which is what most posts on this topic will tell you before giving you nothing useful.

Here's a direct answer: 75 to 150 problems, solved with genuine understanding, covers the coding interview for the vast majority of software engineering roles. That's the range. For FAANG and top-tier companies, you'll want to be at the higher end and beyond. For the majority of companies that are actually hiring new grads right now, 75–100 problems focused on core patterns will get you through the technical screen.

This article breaks down how much LeetCode prep you actually need, what to focus on, how to know when you're ready, and when to stop preparing and start applying.

One thing to clarify upfront: LeetCode preparation and take-home coding challenges are completely different skills. Take-homes test your ability to write clean, well-structured code on a real problem with no time pressure. LeetCode tests pattern recognition under a clock. The prep approach for each is different, and conflating them leads people to over-prepare for one and show up underprepared for the other.

Why Most LeetCode Advice Is Useless

The typical advice from competitive programmers and FAANG engineers is to solve 300–600 problems. That advice is accurate for them and largely irrelevant for you.

The people giving that advice work at Google, Meta, or Amazon. They're describing what it took to clear the most competitive technical screens in the industry. Those screens are genuinely hard. They require fast, confident pattern recognition across a wide range of problem types, and the bar is high enough that volume matters.

But here's the thing: those companies represent a small fraction of the software engineering market. The market for entry-level software engineers is mostly mid-size companies, scale-ups, regional tech employers, and companies in non-tech industries that run engineering teams. These employers run coding interviews that test basic problem-solving, not competitive programming. A candidate who has done 100 problems thoughtfully and can explain their reasoning clearly will clear most of these screens.

The 300+ number gets repeated because it's said loudly by high-credibility voices. It doesn't describe what most job seekers actually need.

The 75–150 Problem Range

There's a reason 75 problems became a benchmark. The "Blind 75" list, originally compiled and shared on the Blind forum, covers the core patterns that show up in the majority of coding interviews: arrays, two pointers, sliding window, linked lists, trees, dynamic programming basics, binary search, graphs, and a few others.

If you work through those 75 problems and genuinely understand why each solution works (not just that it does), you'll be able to recognize and approach most problems you encounter in an interview. That's the goal. Not memorization. Pattern recognition.

From 75, you can extend to 100–150 by drilling the areas where you feel weakest, doing timed practice, and adding a few problems from the company-specific lists if you have a target employer. That range is enough for most roles.

Going beyond 150 makes sense in a few situations: you're specifically targeting FAANG or similar, you want to compete for senior-adjacent roles where the bar is higher, or you have extra time and find algorithmic problems genuinely engaging. If none of those apply to you, 150 is the ceiling on useful prep time for most job seekers.

Patterns Over Volume

The single biggest mistake people make with LeetCode is treating it as a volume game. Solve 500 problems. Grind every day. Hit a streak. This produces diminishing returns fast.

The point of coding interview prep isn't to have seen every possible problem. You can't do that. New problems get added constantly and interviewers can always construct something slightly different from what you've practiced. The point is to build pattern recognition fast enough and deep enough that you can reason through an unfamiliar problem from first principles.

The 5 algorithmic patterns that cover roughly 80% of coding interview questions are worth understanding at that level. When you see a problem involving a sliding window, you should immediately know the general shape of the solution. When you see a graph problem, you should be reaching for BFS or DFS without hesitation. That fluency comes from understanding patterns deeply, not from solving more problems.

In practice, this means: when you solve a LeetCode problem, don't just get to an accepted answer and move on. Ask yourself what the pattern is. Why does this approach work? What would make this approach fail? Could you explain it to someone else without looking at the code? If the answer to that last question is no, you haven't actually learned it yet.

Reviewing problems you've already solved is more valuable than constantly doing new ones. Spaced repetition, the same technique used for language learning, works here. Coming back to a problem after a few days and solving it again from memory is better signal than solving 10 new problems you half-understand.

What FAANG vs. Non-FAANG Actually Requires

Let's be specific about the difference, because it's real.

FAANG and equivalent companies (Google, Meta, Amazon, Apple, Microsoft, and companies with similar technical bars like Stripe, Coinbase, Jane Street, Two Sigma, Palantir) run interviews specifically designed to filter on algorithmic fluency. The questions are harder. Time pressure is real. Interviewers expect you to optimize, not just solve. Some questions require knowledge of advanced data structures or dynamic programming patterns that are rarely tested elsewhere. For these companies, 150+ problems and consistent timed practice is appropriate. You should also study topics like tries, segment trees, bit manipulation, and advanced graph algorithms if you're targeting this tier.

The rest of the market runs more practical interviews. Mid-size tech companies, Series B/C startups, non-tech companies with engineering teams, regional employers: these roles often include a coding screen, but the problems test basic problem-solving ability and clean code, not advanced algorithms. A two-pointer solution, a simple tree traversal, a hash map usage question. These are the problems that 75–100 solved thoughtfully will prepare you for.

Knowing which tier you're targeting matters, because over-preparing for FAANG-level interviews costs you weeks of time you could be spending applying and interviewing elsewhere.

Most people reading this article are not primarily targeting FAANG. If you are, adjust up. If you're targeting a realistic range of companies for entry-level roles, 75–150 is the range and you don't need to feel behind because you haven't hit 300.

How to Structure Your Prep

A reasonable LeetCode plan for someone starting from scratch looks like this:

Weeks 1–3: Core patterns. Work through the Blind 75 list systematically, grouped by topic rather than random. Do arrays first, then hashing, then two pointers and sliding window. Don't skip topics that feel hard. Spend extra time on dynamic programming and graphs, which are the two areas most people avoid and most often appear in interviews.

Weeks 4–5: Timed practice. Start doing problems under time pressure. 25–35 minutes per medium problem, 15 minutes per easy. The goal isn't just to solve it but to solve it and explain it clearly within the time. Practice saying your thought process out loud, even if you're working alone.

Week 6+: Company-specific and review. If you have specific targets, look at the frequently-asked lists for those companies on LeetCode's company filter or on sites like Glassdoor. Review problems you've already solved from memory. Address weak spots.

At this point, you have 100+ problems under your belt, you've done timed practice, and you know the core patterns. You're ready.

When to Stop Prepping and Start Applying

This is the part most articles leave out.

There's a very specific trap that serious, conscientious people fall into: treating LeetCode prep as a prerequisite that needs to be completely finished before job searching begins. The logic feels responsible. Get ready, then apply. But it leads to months of prep with no applications, no interviews, and no feedback on whether the prep is actually working.

We've seen this pattern consistently in students who come to us after extended job searches: they spent months on algorithmic prep, never applied in parallel, and missed a window where they could have gotten interviews, gathered real feedback, and adjusted their approach. The prep becomes a comfortable way to feel productive without doing the scariest thing, which is actually putting yourself in front of companies.

Here's a better mental model: LeetCode prep and job searching are parallel tracks, not sequential ones. You do enough prep to clear a screen, then you start applying. You keep doing problems as you go. You get feedback from real interviews and fill in gaps. You learn more from a real interview, even one you don't advance in, than from another week of unseen problems.

If you've solved 75 problems and you understand the patterns, start applying to companies where a basic coding screen is the expected bar. You're ready enough. The additional prep you do while actively searching is more targeted and more effective than prep done in isolation.

The question to ask yourself is not "have I done enough problems?" It's "have I done enough that I'll pass a screen at the companies I'm targeting?" For most roles, 75–100 is that threshold.

The Trap of Endless Prep

It's worth naming the psychological piece directly.

Preparing for interviews feels safe. Applying feels vulnerable. Rejection from a company stings in a way that a failed LeetCode problem doesn't. So it's rational to stay in prep mode longer than necessary. It feels like you're making progress, you're getting better, you're building skills. But without applications, there's no real feedback loop. You don't know what's actually blocking you.

The candidates who break through fastest treat the job search itself as the primary activity. Prep is fuel for the search. It's not the search itself. When prep becomes the main thing and applying becomes something you'll start "once you're ready," you've stopped searching and started studying indefinitely.

Set a concrete number. "When I've done 100 problems and can solve a medium problem in 30 minutes without looking things up, I'm applying." Then actually apply when you hit it.

LeetCode Doesn't Replace Your Portfolio

One more thing that's easy to lose sight of during an intense prep period: most of the reasons new grads don't get interviews have nothing to do with algorithmic interviews.

The first filter is the resume. Then the GitHub. Then the initial phone screen. The LeetCode-style technical screen comes later in the process. If you're not getting past the application stage, grinding more problems won't fix that. The issue is somewhere else.

Your GitHub profile and the projects you show there signal something different from your interview performance. It signals how you write code when you have time to think, how you structure a project, whether you deploy things, whether you can write a coherent README. That signal matters to hiring managers doing the first pass on applications, and no amount of LeetCode prep substitutes for it.

Do the prep. Learn the patterns. Get to 75–150 problems at genuine understanding depth. Then apply, with a portfolio that shows real work alongside your interview readiness.

Where You Actually Stand

Here's how to assess yourself honestly. If you can do the following, you're ready to start applying:

Solve most easy problems without hints in under 15 minutes
Solve medium problems in 25–35 minutes with some struggle but consistent success
Explain your solution out loud, including why it works and what the time/space complexity is
Recognize the major patterns: sliding window, two pointers, BFS/DFS, binary search, hash maps, basic dynamic programming
Work through a problem you've never seen by identifying which pattern likely applies

If you can do all of that with 75–100 problems under your belt, you're ready for the screens at most companies. You're not ready for Google L3 without more work. You're ready for the realistic pool of entry-level roles in the market.

Stop treating the number of problems as the goal. The goal is interview readiness. That's a real threshold you can actually hit, usually faster than you think.

The point of LeetCode prep is to get interviews and pass screens, not to hit a number. Get to genuine understanding across the core patterns, do timed practice, and start applying in parallel. Real interviews will teach you more than any additional week of prep in isolation.

For what happens inside the actual interview, how to think out loud in a live coding screen covers the communication side. What to do when you don't know the answer covers the moment most candidates dread. And if you have a specific interview coming up soon, how to prepare for a technical interview in one week has a day-by-day plan. For the portfolio side, the GitHub profile that actually gets you hired covers what hiring managers look at alongside your interview performance.