My recommendation to anyone who is preparing for interviews is to spend less time learning pre-determined solutions and focus instead on showing the way you analyse a question, what kinds of questions you ask for clarification, and how you adjust your thinking based on new information. In recent interviews the majority of hiring managers have placed more importance on how well you break down a question rather than if you can recall a specific "perfect" solution from your memory. For me as senior software engineer, this is how I prepare for my interviewees, along with the many candidates I have been coaching. I use AI-testing tools to practice mock interviews as if it were a real interview, and then we discuss and evaluate their reasoning. And not just if they got the answer correct. In each interview we go through the problem aloud, evaluate where their reasoning was unclear and work on refining that line of reasoning. The purpose of this process is not to appear polished in their response, but rather to be able to clearly demonstrate how they think through problems in uncertain situations. If the interviewees can explain their methods and trade-offs, and articulate their assumptions, they will rise to the top of the candidate pile — even when they do not propose the "perfect" solution.
Be the "go-to person," not a passive participant. When you walk into that interview, your goal is simple: create the impression that if the company decided to build this system tomorrow, you could lead the effort. What does that mean in practice? Own the conversation. Drive it forward. Have a clear plan and articulate it confidently. The moment you go silent and the interviewer starts asking questions to fill the void - the section is already lost. This doesn't mean talking non-stop or pretending to know everything. It means thinking out loud, explaining your reasoning, proactively identifying trade-offs, and showing that you can navigate uncertainty without freezing. Confidence matters more than perfection. A slightly imperfect design presented by someone who clearly knows what they're doing beats a "correct" answer from someone who needed to be guided to every decision. Practice this with a friend before the real thing. You'll quickly discover where you hesitate, where your explanations fall apart, where you lose momentum. Fix those gaps. It takes a bit of preparation - and honestly, some acting - but the impression you create is half the battle.
Treat the interview like a systems design problem about you, not just about code. Most candidates over-optimize for algorithms and under-explain how they think, so I always advise engineers to narrate their trade-offs out loud. Why do you choose one approach over the other? What would you change under different constraints? How might it fail in production? That context signals seniority far more clearly than a perfect solution. This is because what usually stands out for the interviewing panel is not speed or cleverness, but judgment. Interviewers want to see whether you can reason about maintainability, edge cases and real-world impact under pressure. If you practice anything, practice explaining your thinking calmly and clearly because that's exactly what strong soft engineers do on the job.
Instead of treating the coding challenge as a solitary test, treat it more like a pair programming session instead of as an exam. From my experience reviewing coding challenges, the primary cause of failure is not a programming error in the code itself. Instead, it is the candidate who has not spoken for 15 minutes while thinking through the solution. In an actual engineering team, silence is considered a bottleneck. By expressing your thought process and talking through your logic and considerations (such as what algorithm you are considering for time complexity, etc.), you provide the interviewer with insight into how you will be able to contribute to a sprint in the real world. This gives you an opportunity to express that you have a critical long-term view about the 'why' of your code. The approach to coding challenges is in keeping with current trends of the industry, which state that being technically proficient does not represent a full indication of a person's capability. Consistent with the trends we've seen in creating large global engineering teams, recent studies on applicant talent suggest that being able to communicate clearly is one of the top indicators of future success as a developer. By expressing your thoughts verbally, you enable the interviewer to gain a better appreciation for your decision-making processes, which ultimately instills a sense of confidence that you will take good care of their code. Everyone knows that technical interviews are somewhat fabricated environments; therefore, when attempting to impress the interviewer, it is best to emphasise both your ability to demonstrate how you think and your ability to work collaboratively with others. These are the two attributes that last beyond your interview.
Focus on demonstrating how you think, not just getting to a correct answer. Before the interview, refresh your understanding of core data structures, algorithms and the language you'll use. Practice solving problems in a time-boxed setting, ideally by talking through your approach aloud or writing on a whiteboard, because many interviewers are listening for your reasoning and communication skills. When presented with a question, ask clarifying questions to confirm requirements, outline your solution before coding and discuss trade-offs. Finally, show curiosity about the company's products and culture by preparing a few thoughtful questions. Interviewers look for someone who can collaborate and communicate effectively, so treat the session as a conversation rather than a test.
Focus on the fundamentals--data structures, algorithms, and the basics of system design. Those questions show up even at senior levels. When you're getting ready, it helps to work through common problems in your main programming language without relying on IDE hints. It trains you to think cleanly under pressure instead of leaning on muscle memory. And say your thought process out loud as you work. Interviewers are usually more interested in how you break a problem apart than whether your solution is flawless. On my teams, we've always preferred someone who can walk through trade-offs clearly over someone who can recite every tree traversal by heart.
My main advice to candidates who prepare for software engineering interviews is to prepare seriously for the interview with the technical recruiter. Often people think that this is just a formality, but at this stage more rejections happen than you think. A recruiter is the first gatekeeper of the process, who reviews not only your relevant experience (and many recruiters are technical enough to ask some difficult questions), but also how you formulate your thoughts, understand the context of the role, explain motivation, and manage expectations. Everything that you say during this stage becomes an important part of the future team's decision. A strong technical profile does not always compensate for unclear motivation or weak communication that's why you should be very conscious about this step.
Practice out loud, not just in your head. Pick a handful of common problem types, set a timer, and get used to talking through your approach while you code, including tradeoffs and edge cases. Most people can solve problems quietly, but interviews reward clear thinking under pressure. If you can explain what you are doing and why, catch your own mistakes, and stay calm when you get stuck, you will beat the person with slightly better LeetCode skills who freezes or goes silent.
One of the best pieces of advice that can be offered here is that of explaining how you think out loud, i.e., in terms of the solutions, rather than the answers. It has been observed time and again that the interviewers specifically focus on the explanation of the reasoning that you put into practice, and the answers that you have arrived at.
The best advice I can give is to prepare to explain your thought process, not just demonstrate that you know the right answer. After interviewing software engineers for over twenty years, the candidates who stand out are the ones who can articulate why they chose a particular approach, what tradeoffs they considered, and how they'd adjust if requirements changed. Most interviewers care less about whether you solve the problem perfectly on the first try and more about whether you can reason through technical decisions clearly. If you get stuck, explaining what you've tried and why it didn't work tells me more about how you'll perform on the job than memorizing algorithm patterns. Real software development is messy and collaborative, and we're trying to assess whether you can think through problems the way you'll need to when the solution isn't obvious. The other piece that matters is being honest about what you don't know instead of trying to bluff your way through. When I ask about a technology or concept you're unfamiliar with, saying "I haven't worked with that directly, but here's how I'd approach learning it" is much better than pretending expertise you don't have. We're hiring for long-term potential, not just current knowledge, and engineers who can admit gaps and demonstrate how they'd fill them are the ones who grow into stronger team members. The worst interviews are with candidates who claim to know everything but can't explain their reasoning when pressed for details. Technical skills can be taught, but intellectual honesty and clear thinking can't.
If I could give one piece of advice to someone prepping for a software engineering interview, it would be to focus on problem-solving over memorizing solutions. A lot of people get caught up in trying to memorize algorithms or coding patterns, but what you really need to demonstrate is your ability to think critically and break down problems step by step. Interviewers want to see how you approach a problem, how you tackle challenges, and how you reason through your solution—not just whether you can recall the right algorithm from memory. Start by practicing with real interview questions on platforms like LeetCode, HackerRank, or CodeSignal. But, here's the catch: when you're solving problems, don't just go for the solution. Talk through your thought process out loud. Think about edge cases, ask clarifying questions, and discuss the trade-offs of different approaches. Even if you're unsure about the final solution, showing how you approach the problem is often more important than getting it 100% right. Another thing to remember is communication. It's not just about solving the problem; it's about explaining how you arrived at the solution. Many candidates struggle with explaining their thought process, and that's something interviewers look for. Practice explaining your solutions as if you're teaching someone else. This helps you clarify your thoughts and shows that you're able to break down complex concepts clearly. Also, don't forget to review the basics. Sometimes candidates dive straight into complex problems and forget about foundational topics like data structures, big-O analysis, or basic algorithms. Make sure you're comfortable with things like arrays, trees, sorting algorithms, and hashmaps. These are often the building blocks for solving more complex problems. Finally, ask for feedback if you're stuck. It's totally fine to hit a wall during an interview. If you're unsure, explain where you're getting stuck, and ask the interviewer if they can give you a hint. A good interviewer will appreciate your willingness to collaborate and learn. At the end of the day, the key is confidence and preparation. Be ready to think on your feet, but also remember that interviews are a two-way street. Take a moment to understand the problem, talk through your ideas, and keep calm. You've got this!
As the founder and CEO of an AI healthcare SaaS company, one piece of advice I give candidates is to develop the ability to rigorously reason about and prove the correctness of your algorithms. While most computer science students are exposed to this in school, relatively few can apply it in day-to-day programming or interviews. Thinking in terms of loop invariants, induction, and clear preconditions and postconditions helps you catch subtle bugs early and explain your solution with confidence. In interviews, this approach lets you clearly articulate why your code works (not just that it seems to), making you more confident and far less likely to make mistakes under pressure.
My top piece of advice is to practice explaining your thought process loudly while you code. In a software engineering interview, the interviewer isn't just looking for the right answer; they want to see how you think and how you'll collaborate with a team. If you code in silence, the interviewer has no idea if you are stuck or if you are just deep in thought. A communicative approach turns your coding into a story. You should ask about constraints, state your approach before typing, and narrate your edge cases. Every time you solve a problem, just follow this flow: Clarify the requirements. Plan the logic and discuss time or space complexity. Code while narrating your steps. Test with sample inputs. Optimise the solution if needed.
President & CEO at Performance One Data Solutions (Division of Ross Group Inc)
Answered 20 days ago
Stop just memorizing coding patterns. My time interviewing in SaaS has shown me that they care more about how you reason through a problem than what you've memorized. Try working through something new out loud. That shows you can think on your feet at a real job, which is worth more than any textbook answer.
Learn to be able to explain out loud your reasoning process, not just get the correct answer. Interviewers assume that you will be using AI tools like ChatGPT and Copilot on the job. They want to see how you think things through and make trades. When I interview candidates at our company, it's not important if they remember the best algorithm for sorting things, what's important to me if they can explain why they'd do one thing or another. Anyone can paste a coding problem in ChatGPT now. The question is whether you have a good understanding of the output so that you can adapt it to our specific constraints. Practice discussing the thought process for your decision-making activities when interviewing for a position. Say things like "I'm choosing this data structure because, or "The tradeoff here is performance vs memory and based on what you told me about traffic patterns I'd prioritize" Most candidates remain silent when trying to think and then offer a solution. That doesn't show me how you work. The best signal I get in interviews is watching someone find a bug in their own code and to explain how they'd debug it. That's the actual job.
Build a couple of small things before your interview. A candidate once showed me a simple AI tool he made, and it sparked a great technical talk. It gives you something concrete to point to, which helps explain your thinking. That little bit of effort makes you stick in people's minds later.
I would suggest that software engineers avoid trying to misrepresent their skills and be prepared to discuss their previous projects in order to have a successful interview. Describe how you approach technical issues, making sure to arrive at a clear answer, and practice. Obviously, this isn't all you need to do to do well in an interview. However, if you're looking for a job in software engineering and are new to the field, it should help you identify certain key points of attention and give you some idea of what your interviewers are looking for. Your interviewers are people after all, and they frequently share a lot of qualities with you. Happy interviewing.
The most important thing I can tell you is this: focus on the system design and not on trivialities when doing your interview. When you solve the algorithm during your interview, make sure that you explain how your solution fits into the larger digital toolchain. Discuss how your code's technical agility impacts infrastructure latency and scalability in a decentralized setting. Interviewers are looking for more than just 'works on my machine' types of solutions; they're looking for proof that you understand technical debt and the overall stability of the product you would be building/maintaining long-term. If you can explain to the interviewer why a specific microservices architecture is a better fit for this type of problem than a monolithic architecture, then you will have shown him/her that you understand the 'engineering' portion of your job title.
As a product owner who has worked very closely with developer teams I can tell you that your interview should lean towards learning the business context of technical problems. A lot of candidates are fantastic at problem solving and CRUD operations, but when asked to explain how their solution would affect real users or align with a business goal they freeze. Show that you are capable to think beyond from just writing code into scalability, user experience and business value and you will distinguish yourself from other technically geeky people.
Make sure you're ready for those academic puzzle-type questions you don't see much of in your day-to-day life. Interviewers like these specifically because they get a good look at how you think on your feet and respond to novel situations. Some studying in advance will help you here, but the key is to simply review the fundamentals, especially of data structures.