You open a cab app. Destination: 2 km away. Expected fare? Maybe ₹70. Actual fare? ₹487 At that point… Walking starts looking premium. 😅 So I turned this into a coding challenge. And yes… This is a real system problem. 🚨 The Problem Basic fare logic sounds easy: Calculate distance fare Add surge pricing Add weather charges Done. Right? Not really. ⚠️ What Goes Wrong? In real ride apps: • Demand spikes suddenly • Driver supply drops • Surge multipliers stack badly • Weather fees pile up And suddenly: 👉 A short ride costs like airport travel. Users feel pricing is random. Sometimes… it almost is. 🧠 What I Observed When exploring this: Basic solutions handled formula math Many ignored pricing caps Some missed fairness logic Very few thought about trust in pricing The code works. But users feel robbed 😭 🔍 The Real Issue This is not just fare calculation. It’s about: • Dynamic pricing • Fairness • Supply-demand modeling • User trust Because: 👉 Correct math can still produce terrible pricing.…