The Death of the LeetCode Ritual: Why Real Software Taste Beats 300 Memorised Solutions
Published: 2026-10-10 · 7 min read · Poorvith M P
The Death of the LeetCode Ritual: Why Real Software Taste Beats 300 Memorised Solutions
**Published:** October 10, 2026
**Author:** Poorvith M P
**Platform Link:** [Read on LinkedIn](https://www.linkedin.com/pulse/death-leetcode-ritual-why-real-software-taste-beats-300-poorvith-m-p-7tjdc)
**Companion Post:** [LinkedIn Post](https://www.linkedin.com/posts/poorvithmp_ai-solves-standard-coding-interview-puzzles-ugcPost-7514513205637910528-Ga8d)
In India's engineering colleges, thousands of students are still told that memorising code patterns is the only way to crack job interviews and start a software career after four years. Last week, while tackling a LeetCode problem, I asked Claude for the question number, and it returned the exact problem with a solution.
Frontier models now solve those algorithmic puzzles in four or five seconds. Is there an easier way? The era of landing a software role through memorisation is officially dead, but real software engineering has never been more alive.
As a 19‑year‑old student builder, the gap between classroom coaching and real software became obvious the moment I stopped running sandbox exercises and started building tools that ease my work and that of my peers. When I move to production, nobody asks me to invent a binary tree on a whiteboard. Real engineering hits us with problems that look completely different. They fall into three categories:
### 1. Diagnosing Failures vs. Generating Syntax
Anyone can prompt an LLM to dump 200 lines of boilerplate in seconds, or even build complete software with a single line of prompt. Syntax is a commodity. Knowing why a local server crashes silently at 3 am on Windows or macOS because a ghost process locked port 3000, or why page responses stall because a network payload was uncompressed, is an engineering test.
### 2. Dependency Discipline
Junior engineers often pull in thirty external packages to solve simple problems, bloating their dependency tree and introducing security vulnerabilities. Experienced builders know that deleting code and mastering the standard library is progress and a time‑saver. The standard library exists to make work easier. Just as we turn repeated prompts into a skill with tools like Codex, we can turn reusable code into library functions for Python or any language.
### 3. The Muscle of Code Review
Frontier models don’t teach us how to defend a diff against a senior maintainer. They don’t show the discipline of trimming eighty lines of unnecessary logic down to a clean five or six, or handling an edge case when an unexpected character breaks the parser.
### A Practical Framework for Builders
If you are a student, developer, or junior engineer anxious about AI replacing your skills, stop measuring your worth by the number of problems you solve on a coding platform. I felt the same at the start, so don’t worry. That anxiety comes from playing the wrong game. Here’s a simple framework I want to share:
Pick a real problem, open an issue in a repository you actually use, clone the codebase, run the tests, fix broken edge cases, address existing issues, open a pull request, and get the fix merged quickly so the maintainer can review and approve it. Build the judgment that frontier models can’t automate: system taste, curiosity, and engineering discipline. Developers are still needed to maintain the human‑judgment loop and problem‑solving skills.
Not every frontier model can replace a senior software engineer’s expertise. Don’t fear losing your job to AI. Focus on problem‑solving, contributing to open source, and using AI minimally and effectively so it enhances, not destroys, productivity.