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Binary search problems look easy… until they’re not 😅 In this video, I walk through **LeetCode Question 34 – Find First and Last Position of Element in Sorted Array**, showing **my real thought process**, including mistakes, edge cases, and why some “clean” textbook solutions don’t always feel intuitive at first. Instead of jumping straight to the classic double binary search approach, I explored a **two-pointer strategy**, carefully handling duplicates, boundaries, and early exits. This is an **uncut, real-world coding session**, exactly how you’d think during an interview or practice session. 🔍 What you’ll learn: How to reason about *sorted arrays* beyond textbook binary search How to handle *duplicates and boundaries safely* Why early exits can simplify logic Common mistakes engineers make with indices Trade-offs between readability and optimal complexity If you’re preparing for **FAANG interviews**, grinding **LeetCode**, or just want to think like a real engineer, this one’s for you. --- 🧠 *Approach Explanation* Start with two pointers: one from the *start**, one from the **end* Shrink the search window while checking both sides As soon as the target is found: Expand inward to capture *all duplicates* Return immediately to avoid unnecessary scans Handle edge cases early: Empty array Single element array This approach trades strict optimality for **clarity and practical reasoning**, which is often valuable in real interviews and debugging scenarios. --- ⏱ *Complexity* *Time Complexity:* Worst case → *O(n)* Best case → *O(1)* (early match at boundaries) *Space Complexity:* *O(1)* — no extra memory used If this helped you, *don’t forget to like, subscribe, and share* 🚀 📌 *GitHub:* [https://github.com/NganeEmmanue](https://github.com/NganeEmmanue) 💼 *LinkedIn:* [ / ngane-emmanuel-b25242150 ]( / ngane-emmanuel-b25242150 ) 📸 *Instagram:* @nganeemmanuel I post **real-world LeetCode walkthroughs**, and engineering lessons learned the hard way.