How to Prepare for Technical Interviews in 2026 - Complete Guide

How to Prepare for Technical Interviews in 2026 - Complete Guide

I bombed my first technical interview at a mid-sized Bangalore startup because I couldn't solve a medium-difficulty tree problem. Binary tree level-order traversal -- that's it. Not even hard. I'd spent three weeks watching YouTube tutorials, bookmarking LeetCode problems I "planned to do later," and zero time actually writing code with my own hands. When the interviewer shared the screen and said "go ahead," my mind went blank. I sat there staring at the blinking cursor for what felt like two minutes. He waited. Then he gently said, "Would you like to start with the base case?" and I realized I couldn't even identify what the base case was. I think I mumbled something about queues and then just kind of trailed off.

That was the lesson. Watching someone solve problems isn't preparation. It feels like it -- same way watching cooking shows feels like learning to cook. You're not. You're learning to recognise the dish.

I've been through this process multiple times since. Some went well. Some were humiliating in ways I still think about at 2 AM sometimes. This is what I wish I'd known.

The Process (Briefly)

Most companies: online coding test first, phone screen second, then on-site rounds. Google and Amazon drag it to 4-6 rounds. Indian startups usually keep it to 3-4. The big service companies test fundamentals more than algorithmic depth. The stages aren't the hard part. The hard part is the preparation, so I'm going to spend most of this article there.

DSA -- Where Interviews Are Won and Lost

Everything else in this article is secondary to this section. You can fumble the behavioural round. You can have a shaky system design answer. But if you can't solve the coding problems, nothing saves you. I've seen this play out too many times.

Data structures. Arrays, strings, linked lists, stacks, queues, hash maps, trees, graphs. You need to reach for the right one instinctively. If someone says "find duplicates," your brain should go to hash map before they finish the sentence. If someone says "nearest," you should be thinking BFS or heap.

I'll tell you what surprised me: I thought I knew arrays. I'd used arrays at work for years. But interview array problems are a different thing entirely. Rotating a matrix in place, trapping rainwater, finding the longest substring without repeating characters -- these aren't things you encounter in a normal codebase. You have to specifically train for them, and the training feels artificial, and that's just how it is.

Algorithmic patterns. Two-pointer and sliding window show up constantly and are the easiest to learn -- maybe a week of focused practice. These gave me quick wins early on when I was still in the "I am terrible at everything" phase and they kept me from quitting.

Binary search seems simple but the off-by-one errors will make you question your sanity. I've watched experienced engineers get the boundaries wrong. Practice the variations: rotated sorted array, first/last occurrence, search in a 2D matrix. Then practice them again.

BFS and DFS took me longer than I expected to internalise. I kept confusing when to use which -- there was this one problem, something about finding the shortest transformation sequence between two words, and I spent an hour trying to DFS it before realizing it was textbook BFS. The rough rule that finally stuck: BFS for shortest path in unweighted graphs, DFS for exploring all possibilities. But honestly, this only clicked after maybe 25 graph problems. Before that it was just words.

Dynamic programming. I need to be honest about this. DP scared me for months. Months. I'd look at a DP problem, stare at it, not see the recurrence relation, feel stupid, and skip it. This was a mistake because DP appears a lot at top companies and you can't just hope you get lucky and avoid it.

What finally made it click -- and I mean genuinely click, not "I sort of understand the textbook explanation" -- was this: every DP problem is just recursion where you store results you've already computed. That's literally it. Write the recursive solution first. Then add memoisation. Don't try to jump straight to bottom-up tabulation like the YouTube tutorials show. Start with recursion plus memo. The bottom-up version can come later once you actually understand what you're optimising.

A friend of mine, sharp developer, four years at a decent product company, failed three Google interviews in a row on DP. Specifically DP. He could solve mediums in every other category. On his fourth attempt he'd spent two months doing nothing but DP. Literally nothing else. He got in. I'm not saying you need two months on DP specifically. I'm saying: figure out your weak pattern early and hit it disproportionately hard. Don't just keep solving problems in categories you're already good at because it feels productive. That's what I did for my first month of prep and it was basically wasted time disguised as progress.

One more thing. Keep a practice journal. Write down your approach, why it works, time/space complexity, and mistakes for every problem. I used a Google Doc. Nothing fancy. This sounds tedious and it is tedious. But when I reviewed my notes the night before interviews, they were more useful than any course or video I'd consumed. Something about writing things in your own words forces the understanding in a way that reading someone else's explanation doesn't.

Complexity Analysis

Every solution you present will be followed by "what's the time complexity?" Stumble here and the interviewer notices. Classic example: two numbers in an array that add to a target. Brute force is O(n squared). Hash map is O(n) time, O(n) space. If you can't get from one to the other when prompted, that's usually a fail at most companies.

Space complexity is the one people under-prepare. "Can you do it in-place?" is a follow-up that catches a lot of candidates off guard. Know the standard ones cold -- quicksort averages O(n log n), merge sort is always O(n log n) but uses O(n) extra space, binary search is O(log n). If you have to pause and think about these during an interview, you haven't practiced enough.

Where to Practice

LeetCode. I'm going to be blunt: nothing has come close to replacing it. The Blind 75 and NeetCode 150 lists are the best curated problem sets available. They cover the common patterns without drowning you in 3,000+ problems. Premium costs around Rs. 1,500 per month and gives you company-tagged problems -- I paid for it when preparing for Amazon and it was worth it for seeing what they actually ask. Whether it's worth it for everyone, I don't know. If you're targeting a specific company, probably yes. If you're doing general prep, the free tier is honestly fine.

Do 20-30 problems on HackerRank and HackerEarth too, purely because many Indian companies use those for online assessments and the interface is different enough to throw you off. I lost 15 minutes on a real HackerEarth test once -- couldn't figure out the input parsing format and kept getting runtime errors that had nothing to do with my actual logic. Embarrassing and entirely avoidable.

Abdul Bari on YouTube is excellent for building algorithm intuition. Striver's SDE Sheet is well-structured if you want a free roadmap. "Cracking the Coding Interview" is showing its age but the fundamentals chapters are still solid. Scaler and Coding Ninjas charge Rs. 1-3 lakh and I genuinely don't know if they're worth it -- I've seen people succeed with them and people succeed without them, and I can't tell if the course was the variable that mattered.

System Design

If you've got 3+ years of experience, expect at least one system design round. If you spent those years at a services company coding specific modules without seeing the architecture, this round will feel like being asked to take an exam for a course you never attended.

Learn the building blocks: load balancers, SQL vs NoSQL, caches (Redis), message queues (Kafka), CDNs, API gateways. You don't need to have used all of these at work. You need to understand when to reach for each one. The concepts underneath: horizontal vs vertical scaling, sharding, replication, CAP theorem, caching strategies.

Common questions that keep appearing: URL shortener, social media feed, chat system, ride-sharing app. The skeleton is always: clarify requirements, estimate scale, define the API, data model, high-level architecture, then deep-dive on one or two components. The deep-dive is where you show you can reason about trade-offs rather than just drawing boxes on a whiteboard.

"System Design Interview" by Alex Xu (both volumes, the second one is better) is the best single resource I've found. Gaurav Sen on YouTube is good for specific topics. And here's something that actually helped me in a real interview: I'd read a Swiggy engineering blog post about their notification system -- I think it was about how they handle delivery partner notifications at scale, or something along those lines -- and I referenced it during a system design round. The interviewer was visibly impressed. Reading engineering blogs from companies you're targeting is underrated.

Companies

Amazon is the company I know best because I went through their process twice. The coding problems are medium difficulty -- not as hard as Google -- but every single round also tests their Leadership Principles. All sixteen of them. You need STAR stories prepared for each one. The Bar Raiser round is unique: an experienced Amazonian from a different team whose only job is to make sure the hiring bar stays high. My first time through, I under-prepared the LP stories and it cost me. Second time, I had a document with 12 stories mapped to different principles and it went much better. Some people find the LP stuff performative and annoying. Having talked to friends who work there, it genuinely is how they make internal decisions. It's not just interview theatre.

Google is the hardest. LeetCode medium to hard, leaning hard. But I also think the process is the fairest -- they genuinely evaluate your thinking, not just the final answer. Communication matters as much as the code. I've heard from people who got offers despite not fully solving one problem because their approach was clear and their reasoning was sound. I never got past the final round myself, so take my advice here with that context. System design leans toward distributed systems.

Flipkart and Indian startups. Flipkart is LeetCode medium range with e-commerce flavoured system design. If you're interviewing there, practice designing product catalogues and order systems specifically. Startups like Razorpay, PhonePe, Meesho, CRED, Swiggy -- generally 3-4 rounds, less emphasis on hard algorithms, more machine coding rounds and practical problem-solving. I actually prefer the machine coding format. It feels closer to real work than whiteboard problems. Pay at funded startups has gotten surprisingly competitive: Rs. 40-70 lakh for senior engineers at the well-known ones.

I've never interviewed at Microsoft, so I won't pretend to have insider knowledge. From what friends have told me: slightly less algorithmic intensity than Google, more collaborative interviewers who give hints, and strong emphasis on code quality over speed. Primarily Hyderabad and Bangalore. That's about the limit of what I can honestly say.

Live Coding

Don't start coding the second you hear the problem. Ask clarifying questions first: constraints, edge cases, input format. Talk through your approach before writing anything. The interviewer might catch an issue early and save you from a full rewrite at the 30-minute mark.

If you get stuck, say so out loud. "I'm stuck on this edge case, let me think" is fine. Silence isn't. Interviewers can't tell if you're thinking deeply or completely lost, and they tend to assume the latter.

Machine coding rounds -- 60-90 minutes to build a working solution for something like a parking lot system or expense splitter. These test production-quality code. I practiced by timing myself with a 90-minute timer maybe eight or nine times before my first real one. First two attempts were disasters. Genuinely awful. By attempt seven I had a rhythm for how to structure code under time pressure. The reps matter more than reading about it.

Mock Interviews

I thought I was ready because I'd solved 180+ LeetCode problems. Then I did my first mock interview on Pramp and couldn't articulate my approach while simultaneously writing code. Knowing how to solve a problem and being able to explain it under pressure while someone watches you -- those are two completely different skills. Do mocks. Even just 3-4 before your first real interview. Find a friend who's also preparing and take turns -- it's free and surprisingly effective.

Prep Timeline

Part-time at 2-3 hours per day, give yourself 3-4 months. Full-time, 6-8 weeks is doable but intense.

First few weeks: fundamentals. Refresh data structures, get sharp in your language of choice, solve easy problems. Don't jump into hards on day one. I tried that and it destroyed my confidence for a week.

The bulk -- maybe 7-8 weeks part-time -- is intensive problem-solving. 2-4 problems a day, covering all patterns. Follow NeetCode 150 or Striver's sheet so you're not picking problems randomly. Add system design prep if that applies to you.

Last couple weeks: mocks, company research, review your journal. Look up interview experiences on Glassdoor and LeetCode Discuss for your target companies.

Your preparation won't be linear. There will be weeks where you feel like you're getting worse. A pattern you thought you had down will suddenly confuse you again. I panicked about this mid-prep and almost scrapped my study plan to start over with a different one. Don't do that. The understanding consolidates over time in ways that aren't obvious day to day. You just have to keep going, even when it feels like you're spinning your wheels.

That's really all I have. The gap between my first interview -- staring at that blinking cursor, unable to write a single line of code, mumbling about queues -- and the interviews that eventually went well wasn't some kind of talent thing. It was just reps.