Grinding Leetcodes isn't really my cup of tea. I've done my fair share, but there's surely more productive projects to spend your time on
So I did what any reasonable developer would do: I procrastinated on interview prep by building a better way to interview prep.
The Problem: One-Size-Fits-Nobody Learning
Here's the thing about traditional coding interview platforms: they're designed for the mythical "average developer." But I'm not average—I'm specific in how my brain works.
The Generic Platform Experience:
- Sterile coding environment with zero context
- Too much rote memorization and little care for how we got to a solution
- Progress tracking that assumes linear improvement
- Discussion forums full of people humble-bragging about O(1) solutions
My Actual Learning Style:
- Need to understand the "why" before the "how"
- Learn better with visual representations
- Require immediate feedback loops
- Work best with spaced repetition
- Need to see patterns across similar problems
- Perform better with contextual, real-world scenarios
The Epiphany: Build for Yourself First
I'm an engineer, why not build for myself.
The idea was simple: create a personalized interview prep app that adapts to how I actually learn, not how someone thinks I should learn.
Designing for My Chaos: The Learning Style Analysis
Before writing a single line of code, I had to honestly assess how I learn best. This required some uncomfortable self-reflection:
Visual Learning Dominance I need to see the data structures, not just imagine them. Tree problems make sense when I can watch nodes being traversed. Graph algorithms click when I can visualize the connections.
Pattern Recognition Over Memorization I'm terrible at memorizing solutions but excellent at recognizing patterns. Show me five similar problems, and I'll spot the underlying approach. Give me one problem in isolation, and I'll stare at it like it's written in ancient Sumerian.
Context-Driven Understanding "Reverse a linked list" is abstract. "Undo functionality in a text editor" makes perfect sense. I need the real-world context to engage the problem-solving part of my brain.
Confidence-Based Progression Traditional platforms move linearly: easy → medium → hard. My brain works better with confidence-based progression: "I kind of get this" → "I totally get this" → "I can teach this" → "Now I'm ready for the next concept."
Immediate Feedback Loops I need to know if I'm on the right track while I'm solving, not after I've already gone down the wrong path for 20 minutes.
The Technical Architecture: Building My Learning Brain
Armed with this self-knowledge, I started building. The tech stack was React, Node.js, and PostgreSQL—nothing fancy, because the magic was in the UX, not the underlying technology.
Adaptive Problem Selection Instead of random problems, the app tracks my performance patterns and serves problems based on my current confidence levels and knowledge gaps. Struggling with dynamic programming? It won't throw hard DP problems at me; it'll serve up easier ones until I build the foundational confidence.
Visual Algorithm Playground Every data structure has an interactive visualization. Linked lists aren't just nodes and pointers—they're animated elements I can manipulate. Trees grow and shrink as I traverse them. Arrays highlight elements as algorithms process them.
Contextual Problem Framing Every abstract problem gets a real-world scenario. "Find the shortest path" becomes "Navigate through a video game map." "Detect cycles in a graph" becomes "Find infinite loops in a dependency system."
Confidence Tracking Over Binary Scoring Instead of "Correct/Incorrect," I rate my confidence: "Totally lost," "Had the right idea," "Solved with hints," "Solved independently," "Could teach this." The app uses this to guide future problem selection.
Spaced Repetition for Coding Patterns Problems I struggled with resurface at calculated intervals. But instead of identical problems, the app serves variations that test the same underlying pattern. This builds pattern recognition without creating false confidence from memorization.
The Learning Features That Actually Work
Smart Hint System Instead of binary hints (show solution or don't), the app provides graduated assistance:
- "Think about the problem type" (is this a graph problem?)
- "Consider the approach" (maybe breadth-first search?)
- "Think about the implementation" (what data structure would help?)
- "Here's the pseudocode"
- "Here's the full solution"
Interview Simulation Mode The app simulates real interview pressure with:
- Timer pressure (but not punitive)
- Follow-up questions ("How would you handle edge cases?")
- Optimization challenges ("Can you improve the time complexity?")
- Communication prompts ("Explain your approach out loud")
Progress Visualization Instead of leetcode-style problem counts, I get visual progress maps showing my journey through different topics. Weak areas appear as unexplored territories, strong areas as conquered lands. It gamifies learning without making it feel childish.
Reflection Prompts After each session, the app asks:
- "What pattern did you recognize?"
- "What would you do differently?"
- "How confident do you feel about similar problems?"
This reflection solidifies learning and helps the app understand my actual comprehension level.
The Results: From Panic to Patterns
After three months of using my personalized system:
Confidence Breakthrough I stopped seeing problems as random puzzles and started recognizing them as variations on familiar themes. "Oh, this is just a graph traversal with extra steps."
Interview Performance My next technical interview felt... normal. Not easy, but normal. I could think through problems methodically instead of panicking. I got the offer.
Learning Efficiency Instead of grinding through random problems for hours, I spent 30-45 minutes daily on targeted practice. The spaced repetition meant concepts actually stuck.
Pattern Recognition The visual approach worked. I could literally see when a problem was asking for DFS vs BFS. Tree problems stopped being abstract and became spatial reasoning challenges.
The Meta-Learning: What I Discovered
Building this app taught me more than just how to pass interviews—it taught me how I learn.
Personalization > Optimization A mediocre system designed for your specific brain beats an excellent system designed for everyone's brain.
Context Is King Abstract problems are hard. Real-world scenarios with technical solutions are engaging puzzles.
Confidence Is a Skill Interview performance isn't just about knowing algorithms; it's about maintaining confidence under pressure. You can practice confidence just like you practice coding.
Learning Is Personal Your optimal learning style might be completely different from mine, and that's perfectly fine. The goal isn't to copy my system—it's to understand your own brain well enough to build something that works for you.
The Open Source Pivot
The app worked so well for me that I open-sourced it. Turns out, lots of developers are frustrated with one-size-fits-all interview prep. The project now has contributors adding features for different learning styles:
- Audio learners get problem explanations as podcasts
- Kinesthetic learners get physical coding challenges
- Social learners get pair programming simulation
Building Your Own Learning System
You don't need to build a full app (though it was fun). Here's how to personalize any learning system:
Audit Your Learning Style
- How do you naturally approach problems?
- When do you feel most confident learning?
- What kinds of feedback motivate you?
- How do you best retain information?
Modify Existing Tools
- Use visualization tools alongside LeetCode
- Create your own contextual problem descriptions
- Build personal spaced repetition schedules
- Track confidence levels instead of just correctness
Iterate Based on Results
- What's working? Double down.
- What's frustrating? Eliminate or modify.
- What's missing? Add it.
The Honest Conclusion
Did building a personalized interview prep app make me a better developer? Absolutely.
Did it make me better at interviews? Definitely.
Was it elaborate procrastination disguised as productivity? Probably.
But here's the thing: it worked. And more importantly, it taught me that the best learning tools are the ones that work with your brain, not against it.
Your mileage may vary, but your learning definitely shouldn't have to fit someone else's template.
P.S. - The app is open source and available on GitHub. It's called "InterviewCraft" and honestly, it could use some design love if any UI/UX folks want to contribute. The code works great; the aesthetics are... functional.
P.P.S. - I still occasionally panic during interviews, but now it's productive panic instead of paralyzed panic. Progress.