What Are Advanced Prompts?
For years, tech interviews for freshers revolved around data structures and algorithms (DSA), often tested with platforms like LeetCode. While fundamentals remain crucial, companies are shifting towards more complex and ambiguous questions known as 'advanced
prompts'. These aren't simple coding challenges with a single correct answer. Instead, they are broad, scenario-based problems designed to simulate real-world engineering challenges. Think less about reversing a linked list and more about questions like, "How would you design a basic version of a URL shortener like Bitly?" or "Outline a system for a ride-sharing app like Uber." These prompts require candidates to think about architecture, trade-offs, scalability, and user experience, not just code implementation.
Why the Shift to Broader Questions?
Companies are making this shift for a simple reason: the day-to-day job of a software engineer has evolved. With the rise of AI coding assistants, the ability to write boilerplate code from memory is less valuable. What's more valuable is a candidate's problem-solving process. Interviewers want to see how you approach a vague problem, ask clarifying questions, consider different components, and justify your decisions. They are testing for 'product thinking'—an understanding of not just how to build something, but what to build and why. This is especially true in India's hyper-competitive market, where companies are prioritizing job-ready talent with practical skills over rote academic knowledge.
The Rise of AI-Assisted Interviews
A major driver of this trend is the integration of AI into the engineering workflow itself. Some companies, including giants like Meta, are now piloting interviews where candidates are allowed, and even encouraged, to use AI tools like GitHub Copilot or ChatGPT live during the session. The focus shifts from your ability to recall a specific algorithm to your ability to collaborate with an AI partner. Can you direct the AI effectively? Can you spot errors or 'hallucinations' in the code it generates? Can you take a basic AI-generated solution and build upon it? Success is no longer about just getting the right answer, but about demonstrating how you leverage modern tools to get there efficiently.
System Design for Graduates
Traditionally, deep system design questions were reserved for senior roles. Now, simplified versions are appearing in interviews for new graduates. You might be asked to design a news feed, a chat application, or an e-commerce shopping cart. The goal isn't to produce a perfect, production-ready architecture. Instead, interviewers are evaluating your ability to break down a large problem into smaller components like servers, databases, load balancers, and caches. They want to see you discuss trade-offs—for example, choosing between different types of databases or caching strategies. Articulating your thought process out loud is as important as the final diagram you draw.
How to Prepare for the New Interview
Preparation for these interviews requires a different strategy. While DSA fundamentals are still the foundation, your practice should expand. Start by working on high-level system design concepts. For any problem, practice asking clarifying questions before you code: Who are the users? What are the main features? What is the expected scale? Get comfortable with communicating your thought process, even for a simple algorithm. Finally, start using AI tools in your personal projects. Develop a concrete story you can tell an interviewer about a time you used AI to solve a problem or learn something new, as this is becoming a common behavioral question. This demonstrates that you are adaptable and fluent with the tools shaping the future of software development.
