How Should I Practice For These Interviews?

In this lesson we talk about how AI is making previously time-prohibitive advanced data structures and algorithms newly relevant in coding interviews, and what that means for how you should prepare.

• AI unlocks harder concepts by handling the boilerplate — complex structures like tries, heaps, and LRU caches were rarely testable in a 45–60 minute interview because implementation alone could eat up 15–20 minutes; with AI generating that scaffolding in seconds, interviewers can now reasonably include them, making them worth studying once you've solidified the fundamentals.
• What you actually need to demonstrate has shifted — since AI handles much of the implementation, your value lies in recognizing when a given data structure is the right tool, clearly articulating why it helps (e.g. "a trie eliminates the factor of M by checking all patterns simultaneously through shared prefix traversal"), and writing precise prompts that reflect that understanding.
• Master the basics first, and don't over-rotate on this — the vast majority of interviews (roughly 95%) will not require these advanced concepts, so treat this as the final 5–10% polish layer, not the foundation; verification of AI output remains just as critical here as everywhere else in the interview.