A Step-by-Step Guide to Solving Technical Interview Questions

Technical interviews really suck, don't they? They can feel like you're trying to solve a Rubik's Cube blindfolded while riding a roller coaster. But fear not - armed with a solid and structured game plan, you can navigate that wild jungle with some style and swagger. That's the goal with this post - to give you a problem solving framework that can be applied to a broad set of technical interview questions so you can show off your knowledge and skills even when you get stuck.

Mar 6, 20255 min read

FEATURED POST

Never Miss a New Post.

TRAIN OF THOUGHT

Maximum Depth of a Binary Tree: A Step-by-Step Interview Walkthrough

Maximum Depth of a Binary Tree is another short problem that interviewers use as a fundamentals check. Like Invert Binary Tree, the appeal isn't the difficulty — it's that there's nowhere to hide. Can you state the recursive definition cleanly? Can you handle the null case without overcomplicating it? Can you explain why the algorithm is O(n) without hand-waving?

4 hours ago8 min read

Invert Binary Tree: A Step-by-Step Interview Walkthrough

The Invert Binary Tree problem is famously one of the simplest problems in the interview rotation, and interviewers like it for exactly that reason. When a problem is short, there's nowhere to hide. Can you state the base case correctly? Can you write clean recursive code without overthinking it? Can you talk through your reasoning without rambling? This may be a warm-up, but warm-ups still matter.

5 hours ago9 min read

Wildcard Matching: A Dynamic Programming Interview Walkthrough

Wildcard Matching is a problem interviewers reach for when they want to see whether you can interpret pattern semantics carefully and resist the urge to write greedy code. The actual skill being tested is the discipline to model the operator's semantics precisely before reaching for a familiar template.

2 days ago13 min read

Regular Expression Matching: A Dynamic Programming Walkthrough

Regular Expression Matching is one of the hardest "easy-to-explain" dynamic programming problems in the standard interview rotation. The problem statement fits in three sentences, but the implementation rewards a very specific kind of thinking: can you take a vague, recursive-feeling specification and turn it into a precise DP table with rigorously-defined transitions?

3 days ago12 min read

Minimum Path Sum: A Dynamic Programming Walkthrough

Minimum Path Sum is a dynamic programming problem interviewers use early in a loop because it's a clean test of fundamentals. Can you define a DP state that's actually self-contained? Can you identify the transitions without overthinking? Candidates who haven't internalized how to walk through a 2D DP table will fumble the indexing, miss the base cases, or jump straight to in-place optimization without justifying it. The interviewer is watching for clean reasoning, not clever

4 days ago10 min read

I hate interviewing. Technical interviews are especially annoying. So I created this blog to practice for technical interviews. Hopefully it's helpful to you, too!