Coding interviews are hard. I’m a software engineer and I know this well, having gone through dozens of them across companies like Stripe, Atlassian, and several Series B startups. I’ve also been on the other side as an interviewer, which made me realize just how badly most candidates prepare, not because they can’t code, but because they’re training for the wrong thing.
The gap between being a strong engineer and passing a coding interview is real. The Stack Overflow 2024 Developer Survey found that a large majority of developers feel underprepared for technical interviews despite having years of professional experience. That’s not a skills problem. It’s a preparation problem.
What most people actually do wrong
The default approach is to open LeetCode, sort by “Easy,” and grind. You do 40 problems, feel confident, walk into an interview, get a problem you haven’t seen before, and freeze. Then you wonder what went wrong.
What went wrong is pattern isolation. You memorized solutions, not patterns. When the interviewer modifies a classic two-sum problem slightly, say by changing it to a three-sum with a specific constraint, your memorized solution breaks and you have nothing to fall back on.
The second mistake is silent solving. Real technical interviews require you to narrate your thinking, walk through your approach before you write a line, and communicate trade-offs out loud. If you’ve been practicing alone in silence, you’ve been training for a completely different activity.
Pattern recognition first
Before you touch a problem, you should be asking: which pattern does this belong to? There are roughly 14 core patterns that cover the vast majority of interview problems at companies from Google to mid-size startups: sliding window, two pointers, fast and slow pointers, BFS and DFS, backtracking, dynamic programming, binary search, and a few others.
The NeetCode roadmap (free, well-organized) groups problems by pattern rather than difficulty, and that’s a much better way to build the mental index you need. Spend the first week or two doing 3 to 4 problems per pattern until you can recognize what kind of problem you’re looking at within 30 seconds of reading the prompt.
I’d also say the Blind 75 list is overrated for senior interviews specifically, though I know that’s not a popular opinion. By the time you’re interviewing for L5 or L6 positions, the companies expect more depth on system design and behavioral than on classic algorithms. For those roles, the patterns still matter, but the problems skew toward design decisions rather than raw implementation.
The talk-through phase
After two weeks of pattern work, shift to verbalized practice. Pick a problem, read it, and spend five minutes talking through your approach before writing anything. Explain what pattern you’re seeing, what the edge cases might be, what the time and space complexity will be.
This sounds awkward when you first do it alone. Do it anyway. Record yourself if that helps. The goal is to make narrating feel natural so it doesn’t cost you cognitive load during the actual interview.
Pramp runs free peer-to-peer mock interviews where you both play interviewer and interviewee. I don’t have data on how much it improves pass rates, but the format forces the real feedback loop: someone else watches you think, which surfaces habits you wouldn’t catch on your own.
Timed pressure in the final stretch
Two weeks out from an interview, start adding time constraints. Not the full 45-minute interview timer yet, but 25-minute sprints on medium-difficulty problems. The constraint changes how you behave. You’ll stop over-optimizing early solutions and learn to ship a working answer before chasing the perfect one.
That shift matters because many candidates fail not by writing wrong code, but by getting stuck optimizing and never finishing. A working O(n²) solution with a note about how you’d improve it scores much better than a half-finished O(n log n) one.
In the week before an interview, stop adding new problems entirely. Review patterns, do one or two warm-up problems per day, and make sure your development environment and editor are set up so you’re not debugging keyboard shortcuts under pressure.
The behavioral side that companies actually care about
At FAANG-adjacent companies, behavioral interviews contribute at least as much to the hiring decision as the coding rounds. I’ve seen candidates write clean, optimal code and still get rejected because they couldn’t articulate a trade-off decision they’d made in a past role.
The STAR format (Situation, Task, Action, Result) is fine as a structure, but the thing that actually lands is specificity. “We had a disagreement about the database schema” is worse than “we had a disagreement about whether to denormalize the user-activity table to hit a 50ms read target.” Interviewers remember specific details. They forget summaries.
Prepare six to eight real stories from your work history that can flex across different question types: a conflict, a failure, a time you pushed back on a direction, a time you had to deliver under pressure. You’ll use a version of the same story for multiple different questions, and that’s completely fine.
One tool worth knowing about
If you want AI-powered mock interview practice with real-time feedback on your answers, Craqly runs simulated technical and behavioral interviews and gives structured feedback on where your answers fall short. It’s not a replacement for peer practice, but it’s useful for late-night prep sessions when you don’t have a partner available.
The coding interview is a learnable skill. Most of the people who pass it aren’t smarter than the people who don’t. They just practiced the right things in the right order.