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Welcome to our Software Engineering Interview Prep Course!

Software engineering interviews still test the core skills they always have: writing correct, efficient code under pressure, designing systems that hold up at scale, and showing how you've actually shipped work with other engineers. Those fundamentals are non-negotiable, and a strong candidate still has to clear a high coding bar, reason through tradeoffs in system design, and tell project stories that stand up to follow-up questions.

In the last few years, the loop has also started to shift in some specific ways. AI-assisted coding rounds are now a standard part of the onsite at several big tech companies. System design prompts are increasingly pulled from AI infrastructure problems. And behavioral rounds, even short ones, are getting more technical and more values-driven.

This course is designed to prepare you for both: the foundations that decide every SWE loop, and the newer expectations showing up in today's hiring market.

After coaching hundreds of candidates, we've found that nothing replaces deliberate practice. That's why your Aced membership includes:

  • Practice questions for every type of SWE interview round, including data structures and algorithms, coding, system design, and behavioral.
  • A dynamic, interactive coding platform for self-guided prep, with a built-in code editor.
  • Refresher lessons on the most common data structures and algorithms.
  • Mock interview videos with software engineers and engineering managers at top tech companies including Google, Amazon, Microsoft, and more.
  • A peer-to-peer mock interview platform with live practice twice daily.
  • Access to our Discord community for support throughout your prep.

Reports from 100+ SWE candidates interviewing at companies including Anthropic, Meta, OpenAI, xAI, and others show a few consistent shifts in what interviewers care about:

  • AI-assisted coding rounds are now standard at several big tech companies. Candidates at Meta and Netflix describe a dedicated AI-enabled coding round in the onsite, often a maze traversal or similar problem solved using whatever AI tools they would normally use. Companies are giving practice environments for this round in advance.
  • Coding is getting more practical, not just pattern-based. Candidates report more class-design problems like LRU cache, rate limiters, iterators with state, and small transactional databases, alongside refactoring tasks and live debugging in real codebases. Pattern-based coding prep still gates the loop, but it's no longer the whole bar.
  • The coding bar at AI-native companies is higher than candidates expect. Senior candidates describe the coding rounds at OpenAI and Anthropic as well past textbook level, with layered follow-ups and real expectations around language internals like iterators, generators, async, and concurrency.
  • System design prompts are pulling from AI infrastructure. Alongside classic prompts, candidates report being asked to design batch inference APIs over GPU clusters, file upload for an AI chat product, agent backends, and LLM sampling systems with batching and request orchestration.
  • Behavioral rounds are getting more technical and more values-driven. Even short behavioral rounds are often run by technical interviewers who drill into specific project decisions. At AI-native companies, the values round expects real opinions on safety, ethics, conflict, and tough feedback, not polished STAR answers.

These shifts don't replace the fundamentals of SWE interviewing. They make the fundamentals more important. Strong pattern-based coding makes practical and AI-assisted coding rounds easier. A solid grasp of distributed systems makes AI infrastructure prompts approachable. And a real story bank with specific tradeoffs is what holds up when a technical interviewer pushes on your projects.

This course covers the fundamentals across coding, system design, and behavioral, with context on the newer rounds where it matters most.

What you'll learn

The Aced SWE track will help you master the most common SWE interview rounds, including system design, data structures, algorithms, and behavioral. You'll review critical SWE concepts, apply proven frameworks to technical rounds, and practice answering real questions from real loops.

Specifically, you will:

  • Discuss the necessary tradeoffs between reliability, scalability, and maintainability in real-world systems.
  • Describe what strong systems look like and outline one in an interview setting, including AI-adjacent prompts where relevant.
  • Practice working with common data structures and algorithms on recently asked coding questions.
  • Build a strong SWE story bank to handle behavioral rounds where interviewers push for specifics.

How to use this course

The SWE interview generally falls into a few categories:

  • Coding. These rounds test your ability to solve problems with code, increasingly inside a real codebase or AI-assisted environment, not just on a blank doc. The best prep is a thorough review of common data structures and algorithms followed by lots of practice.
  • System design. "Design Reddit," "design a batch inference API," and similar prompts test your technical knowledge alongside your communication, critical thinking, and judgment under ambiguity.
  • Behavioral. Either experiential ("tell me about a time when you...") or hypothetical ("what would you do if..."), these rounds assess how you work with others, how you make tradeoffs, how you recover from mistakes, and at some companies, how you think about values and impact.

Coding interview prep

To start prepping for coding, read through the data structures and algorithms lessons for a quick refresher. Then try a few of the practice questions linked at the bottom of each lesson to test your skills. If graph search is rusty, work through several of those before moving on.

After that, watch a few mocks so you get a feel for how strong candidates talk through problems in real time. Once the cadence feels comfortable, run more practice questions until you're confident solving cleanly under pressure. If you're targeting AI-native companies, build in extra reps on practical class-design problems and on reading unfamiliar code, since those increasingly carry as much weight as classic pattern-based questions.

Not sure where to start with coding interviews? Check out this article on Byte-by-Byte for some additional tips.

System design prep

Prep for system design in small chunks because it's a lot to digest. Once you've read the intro lessons on frameworks and the system design rubric, watch a few mock videos. Get a feel for the round, then browse the fundamentals course to refresh your technical basics, and design a few systems on your own. When you feel ready, sign up for a system design mock interview or three.

It helps to see how systems work at real companies, so check out the case studies linked at the bottom of each fundamentals lesson and read the engineering blogs of any companies you're interviewing at.

When designing a system, remember there's no single correct answer. By working through your design and explaining your choices, you'll improve the structure and content of your response. This is a trainable skill, so keep at it.

Behavioral interview prep

Finally, leave real time for behavioral. The best approach is to build a story bank with specific tradeoffs, metrics, and decisions, then practice using it under realistic conditions. Sign up for as many behavioral mock interviews as you can until your stories are sharp.

Behavioral rounds at many companies are now run by technical interviewers, and the bar at AI-native companies often includes real opinions on values, safety, and conflict. Stories that hold up are the ones where you can explain why you made the call you did, what tradeoffs you weighed, and what you'd do differently.

If you have questions or thoughts as you go, visit the Aced Discord community and participate actively. You'll find others working through the same prep, and you'll often pick up sharper approaches to specific question types.

If you reach the end of the course and want more practice, head to our interview question database. We select the top answers and provide detailed feedback and analysis.

More information

If you have any questions, please don't hesitate to reach out to others in our Discord community.

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