The Parenting Challenge
You’ve been grinding LeetCode for months. You’ve solved hundreds of problems, watched countless tutorials, and still feel stuck at the medium level. Every time you open a job posting from Google, Amazon, or Microsoft, the salary figure—50 LPA, 60 LPA, even 70+ LPA—feels like a distant dream. You wonder: "Do I need an IIT tag? Do I need to be a competitive programming prodigy? Or am I just missing the right strategy?"
This is the exact frustration that drives thousands of software engineers and students into a spiral of random problem-solving. They jump from arrays to graphs to dynamic programming without a clear plan. They burn out. They give up. And they never realize that the secret to cracking those top-tier packages isn’t about solving more problems—it’s about solving the *right* problems in the *right* order.
In a recent live session on the GeeksforGeeks Podcast, Anmol Agarwal—an NSIT graduate who landed a 70+ LPA role without an IIT degree—broke down the exact DSA roadmap and interview strategy that got him there. This article unpacks that roadmap, explains why it works, and gives you a step-by-step plan to replicate his success.
What the Research Says
What the research actually shows is that the most successful candidates don’t just practice DSA—they practice *strategically*. A 2023 study by the National Bureau of Economic Research found that structured, spaced repetition learning improves retention by 50% compared to massed practice (cramming). For DSA, this means you should cycle through topics multiple times, gradually increasing difficulty, rather than trying to master one topic completely before moving on.
Anmol’s approach mirrors this. He recommends starting with easy problems on arrays and strings, then moving to medium-level problems on linked lists, stacks, and queues, and only then tackling trees, graphs, and dynamic programming. The key insight? Most MNC interviews focus on a core set of 8-10 data structures and algorithms. According to interview data from Glassdoor and LeetCode, arrays, strings, hash maps, trees, graphs, dynamic programming, and recursion appear in over 80% of technical interviews at Google, Amazon, and Microsoft.
Here’s what most parenting advice gets wrong—or in this case, what most DSA advice gets wrong: they tell you to “just practice more.” But without a roadmap, you’re like a parent trying to teach a toddler to run before they can crawl. You need to build foundational skills first. For DSA, that means mastering time complexity analysis, recursion thinking, and basic data structures before attempting hard problems.
Practical Strategies
Here’s exactly what to do if you’re targeting a 50-70 LPA role in 2026. Anmol’s roadmap breaks down into three phases:
**Phase 1: Foundation (Weeks 1-4)**
Start with easy problems on arrays, strings, and hash maps. Solve at least 2-3 problems daily. The goal is not speed but understanding. For each problem, write out the brute-force solution first, then optimize. Use the "five whys" technique: ask yourself why each step works. This builds the mental models you’ll need later.
**Phase 2: Core DSA (Weeks 5-12)**
Move to medium problems on linked lists, stacks, queues, trees, and graphs. Focus on pattern recognition. For example, many tree problems are just variations of BFS or DFS. Graph problems often boil down to detecting cycles or finding shortest paths. Anmol recommends solving 5-10 problems per topic, then moving on. Don’t get stuck—you’ll revisit topics later.
**Phase 3: Advanced & Interview Prep (Weeks 13-24)**
Tackle dynamic programming, hard problems, and system design basics. Here, competitive programming helps. Anmol suggests participating in weekly contests on Codeforces or LeetCode to build speed and confidence. But don’t overdo it—CP is a tool, not the goal. The real goal is to simulate interview conditions: solve problems under time pressure, explain your thought process out loud, and practice whiteboarding.
**Specific scripts for interview practice:**
When you’re stuck on a problem, say: "I’m going to start with the brute-force approach to understand the constraints, then optimize." This shows interviewers you have a structured thought process. Also, always ask clarifying questions: "Can I assume the input is sorted?" or "What’s the expected time complexity?" This mirrors how real engineers solve problems.
Real Parent Reality
Let’s be honest—theory and practice don’t always align. You might follow this roadmap perfectly and still hit a wall. Maybe you’re a working professional with only an hour a day to study. Maybe you’re a student juggling college exams. Or maybe you’re a parent yourself, trying to upskill while raising kids. The reality is that consistency matters more than intensity.
Anmol himself admits he didn’t follow the roadmap linearly. He got stuck on dynamic programming for weeks. He failed mock interviews. He felt like giving up. But he adapted: he broke DP into sub-patterns (knapsack, LCS, matrix chain) and practiced each separately. He also used the "Pomodoro technique"—25 minutes of focused problem-solving, then a 5-minute break—to maintain focus.
If you’re struggling, don’t compare your journey to someone else’s highlight reel. The 70 LPA packages you see on LinkedIn are the result of months of disciplined practice, not genius. And remember: even top performers have bad days. The key is to keep showing up.
Different Ages, Different Approaches
Just as parenting strategies change as a child grows, your DSA preparation should adapt to your experience level.
**For students and freshers (campus placements 2025-2026):**
You have the advantage of time. Start early—ideally 6-9 months before placement season. Focus on building a strong foundation in all core topics. Don’t skip the basics. Also, leverage campus resources: coding clubs, seniors’ notes, and mock placement drives. Your goal isn’t just to crack interviews but to build skills that will serve you throughout your career.
**For working professionals (job switch 2026):**
You have less time but more context. Focus on the topics most relevant to your target company. For example, Amazon emphasizes leadership principles and system design, while Google focuses on algorithmic problem-solving. Use your work experience to your advantage—mention real-world projects in your resume and interviews. Your goal is to show you can apply DSA to solve business problems, not just theoretical puzzles.
**For developers stuck at easy problems:**
You’re likely missing the "why" behind solutions. Instead of memorizing code, understand the underlying patterns. For example, many medium problems are just easy problems with a twist. If you can’t solve a medium problem, go back to the easy version and analyze what makes it harder. This metacognitive approach—thinking about your thinking—is what separates advanced learners from beginners.
The Takeaway
The core principle to remember is this: a structured roadmap beats random practice every time. You don’t need an IIT degree. You don’t need to be a competitive programming champion. You just need a clear plan, consistent effort, and the willingness to adapt when you get stuck.
One thing you can try today: pick one DSA topic you’re weak on (say, dynamic programming) and solve 3 easy problems from that topic. Write down the pattern you notice. Then, tomorrow, solve 3 medium problems. Do this for a week. You’ll be surprised how quickly your confidence grows.
And remember—every expert was once a beginner. The 70 LPA software engineer you admire started exactly where you are now. The only difference is they had a roadmap. Now you do too. Go build your future.
