LeetCode Premium Company Tags: Most People Use Them Wrong

You just bought LeetCode Premium. Or you're debating whether to. Either way, you've heard the pitch: "Company tags show you exactly what Google/Meta/Amazon asks!"

That's true. But here's what nobody tells you: most people use company tags inefficiently, either over-relying on them or not knowing how to prioritize the hundreds of questions tagged for each company.

This guide shows you how to use LeetCode Premium company tags strategically—maximizing your ROI and interview success without grinding aimlessly.

TL;DR

• What company tags are: Premium feature showing which problems each company has asked in real interviews, often with frequency data
• Why they matter: Companies recycle questions heavily; Meta's top 50 questions have a high hit rate in actual interviews
• How to use them effectively: Filter by recency (last 6 months), prioritize high-frequency problems, and combine with pattern learning
• Common mistakes: Grinding company lists without understanding patterns, or waiting until the last minute
• What you'll learn: A complete 4-week framework for turning company tags into interview offers

What Are LeetCode Premium Company Tags?

LeetCode Premium unlocks company-specific filtering that shows you:

• Which companies asked each problem (tagged by company name)
• Recency (when the problem was last reported—last 6 months, 1 year, 2 years, etc.)
• Frequency bars (how often the problem appears relative to other problems for that company)

For example, if you filter by "Meta" and sort by frequency, you'll see the problems that appear most often in Meta's actual coding interviews.

Why This Data Matters

Big tech companies don't create new problems for every interview. They rotate through a pool of questions, and certain problems appear repeatedly because:

1. They test core competencies (data structures, algorithms, problem-solving)
2. Interviewers are trained on specific question sets
3. Problems have been validated as fair and calibrated

This creates an asymmetric advantage: if you know what's likely to be asked, you can focus your limited study time on high-probability questions.

The 4-Week Company Tag Strategy

Here's a battle-tested approach for candidates with an interview scheduled 4+ weeks out.

Week 1-2: Build Pattern Foundations

Don't start with company tags. This is the most common mistake.

Company-tagged questions span every pattern: two pointers, sliding window, dynamic programming, graphs, etc. If you haven't built pattern recognition skills first, you'll be:

• Solving problems one at a time without transferable learning
• Unable to solve slight variations in the actual interview
• Wasting time on hard problems you don't have the prerequisites for

Instead:

1. Complete foundational patterns through a structured DSA learning path
2. Focus on core patterns: arrays, hash maps, two pointers, sliding window, BFS/DFS, basic DP
3. For each pattern, solve 5-8 problems until you can recognize when to apply it

This foundation makes company-tagged problems dramatically easier.

Week 3: Company-Specific Deep Dive

Now you're ready to use company tags effectively.

Step 1: Filter the right problems

1. Go to LeetCode's "Problems" page
2. Filter by your target company
3. Critical: Set recency to "Last 6 months" or "Last year"
4. Sort by frequency (highest first)

Older questions (2+ years) are less likely to appear. Interviewers and problem pools change.

Step 2: Identify your hit list

From the filtered list, identify 20-30 problems that are:

• High frequency
• Cover different patterns (don't do 10 array problems in a row)
• Match the difficulty level typically asked (for most companies: 1 Easy, 2-3 Mediums per round)

Step 3: Solve strategically

For each problem:

1. Time yourself (25-30 minutes for Medium)
2. If stuck after 15 minutes, get a progressive hint instead of immediately reading solutions
3. After solving, write a 2-line summary: "Pattern used" + "Key insight"
4. Add especially tricky problems to your review list

Week 4: Review, Mock, and Fill Gaps

Review phase:

• Re-solve problems from Week 3 without looking at your notes
• Focus on problems you needed hints for—these reveal pattern gaps
• If you can't solve a problem you "solved" last week, you didn't actually learn it

Mock interview phase:

• Do timed sessions: pick 2 random problems from your company list
• 45 minutes total: read, solve, and explain both
• Practice articulating your thought process out loud—this is as important as the code

Gap-filling:

• If your mocks reveal weak areas (e.g., graph problems), do targeted practice on that pattern
• Don't panic-grind—better to deeply understand 25 problems than half-understand 100

Company-Specific Insights

Not all company tags are equally useful. Here's what to know:

Meta/Facebook

Tag reliability: Very High

Meta has historically shown the highest question repetition rate. Their top 50 list is worth memorizing-level familiarity. Expect:

• Heavy array/string problems
• Tree traversals
• Graph basics (especially BFS)

Google

Tag reliability: Medium

Google actively removes leaked questions and rotates their pool faster. However, the style remains consistent:

• More algorithm-focused (less string manipulation, more optimization)
• Higher likelihood of graph problems
• May ask follow-up optimization questions

Use tags to understand Google's style, but don't memorize expecting exact repeats.

Amazon

Tag reliability: High for patterns, less for exact questions

Amazon's coding questions vary more by team, but certain patterns dominate:

• Tree problems (especially binary trees)
• BFS/DFS applications
• Design-oriented questions ("implement LRU cache")

Also prepare heavily for behavioral questions—Amazon's Leadership Principles matter as much as code.

Startups

Tag reliability: Low

Most startups don't have enough interview data points for reliable tags. Focus on:

• General pattern coverage
• Practical coding (cleaner code, edge case handling)
• Often more conversation-oriented than pure algorithm tests

Code Example: Tracking Your Company Tag Progress

Here's a simple tracker to stay organized during your company-focused prep:

from datetime import date

class CompanyPrepTracker:
    def __init__(self, company_name):
        self.company = company_name
        self.problems = {}
    
    def add_problem(self, title, difficulty, pattern, solved_independently):
        """Add a problem to your company prep list."""
        self.problems[title] = {
            "difficulty": difficulty,
            "pattern": pattern,
            "solved_independently": solved_independently,
            "first_attempt": str(date.today()),
            "needs_review": not solved_independently,
        }
    
    def get_review_list(self):
        """Get problems that need review before interview."""
        return [p for p, data in self.problems.items() if data["needs_review"]]
    
    def pattern_coverage(self):
        """Show which patterns you've covered."""
        patterns = {}
        for data in self.problems.values():
            pattern = data["pattern"]
            patterns[pattern] = patterns.get(pattern, 0) + 1
        return patterns
    
    def summary(self):
        total = len(self.problems)
        independent = sum(1 for p in self.problems.values() if p["solved_independently"])
        print(f"{self.company} Prep Summary:")
        print(f"  Total problems: {total}")
        print(f"  Solved independently: {independent} ({100*independent//total if total else 0}%)")
        print(f"  Need review: {len(self.get_review_list())}")

# Usage
meta_prep = CompanyPrepTracker("Meta")
meta_prep.add_problem("Two Sum", "Easy", "Hash Map", True)
meta_prep.add_problem("LRU Cache", "Medium", "Design", False)
meta_prep.add_problem("Binary Tree Level Order", "Medium", "BFS", True)
meta_prep.summary()

This keeps you honest about what you actually know vs. what you've just "seen."

Common Mistakes to Avoid

Mistake 1: Grinding Company Lists Without Pattern Foundations

You solve 50 Meta-tagged problems but can't recognize a sliding window when you see it. Sound familiar?

Fix: Spend your first 1-2 weeks on pattern learning, not company tags. The pattern recognition approach transfers to any company's questions.

Mistake 2: Only Doing High-Frequency Problems

Frequency bars show what's asked often, but interviewers sometimes pull from the long tail. If you've only done the top 20, you may face something unfamiliar.

Fix: Cover the top 30-40, ensuring you have 2-3 problems from each major pattern.

Mistake 3: Rushing Through Problems

You "solved" a problem with heavy hints, checked it off, and moved on. But you didn't learn anything transferable.

Fix: Force yourself to explain the solution out loud. If you can't explain it, you didn't learn it. Tools like LeetCopilot can help by providing incremental hints that keep you in problem-solving mode rather than passive reading.

Mistake 4: Waiting Until the Last Week

Company tags are most useful with 3-4 weeks of lead time. One week isn't enough to deeply learn 30+ problems.

Fix: Start company-specific prep as soon as you have a scheduled interview. Even if it's 6 weeks out, the extra time lets you do proper spaced repetition.

Mistake 5: Ignoring Behavioral Prep

Passing the coding interview only matters if you also pass behavioral rounds. Company tags can't help you here.

Fix: Allocate at least 25% of your prep time to behavioral questions, especially for Amazon.

Combining Premium Tags with Free Resources

You don't need Premium for everything. Here's how to layer resources:

The optimal stack: build foundations with free resources, then use Premium strategically for the 3-4 weeks before your target interview.

Is LeetCode Premium Worth It Just for Company Tags?

Short answer: Yes, but time it right.

If you're actively interviewing at companies with strong tag data (Meta, Amazon, some unicorns), one month of Premium ($35) is high-ROI. The asymmetric advantage of knowing likely questions outweighs the cost.

But: Don't buy a year subscription "just in case." Buy for 1-2 months when you have scheduled interviews. This keeps you accountable and maximizes value.

For a deeper cost-benefit analysis, see our full breakdown of whether LeetCode Premium is worth it.

FAQ

How accurate are company tags really?

They're reported by users who interviewed at the company. High-frequency problems (many reports) are usually accurate. Low-frequency problems may be one-off experiences. Weight your prep toward frequently-reported questions.

Should I do ALL problems tagged for my target company?

No. Focus on high-frequency problems from the last 6-12 months. Trying to do all 300+ tagged problems is inefficient. 30-40 well-chosen problems is more effective.

What if my interview is in less than 2 weeks?

Prioritize ruthlessly. Do the top 15 most frequent problems, ensuring you understand the patterns, not just the solutions. Skip obscure hard problems. Focus on execution speed and clear communication.

Do company tags work for non-FAANG companies?

Depends on data availability. Larger companies (Uber, Airbnb, Stripe) have decent tag data. Smaller startups usually don't. For less-tagged companies, fall back to general pattern practice.

Can I succeed without LeetCode Premium?

Absolutely. Premium gives an edge for company targeting, but it's not essential. Free curated lists, YouTube explanations, and disciplined pattern practice can get you far.

Conclusion

LeetCode Premium company tags are powerful—when used correctly. The key is combining them with strong pattern foundations, strategic filtering (recency + frequency), and honest self-assessment of what you actually know.

Don't just grind through lists. Learn patterns first, then use company tags to focus your final preparation on high-probability questions. Track what you've truly mastered versus what you've only seen, and prioritize review over new problems as your interview approaches.

The candidates who succeed aren't necessarily the ones who solved the most problems. They're the ones who deeply understood the right problems—and could solve variations under pressure.