💰 Greedy Algorithm Mindset

📖 Core Idea: Greedy makes the locally best choice at every step, hoping these choices lead to a global optimum. It works well when the problem has optimal substructure and a greedy choice property that you can prove or justify.

🗯 Real Interview Scenario: “Jump Game”, “Minimum Number of Arrows to Burst Balloons”, or interval scheduling.

✅ How to shine: Share your greedy intuition first, then briefly prove why it works (e.g., “Sorting by end time guarantees we fit maximum activities”). Compare with DP when asked. This shows deeper problem-solving maturity.