In this guide, you’ll learn why mock interviews are a great tool, how to structure and run them effectively, and which tools and platforms are available. By following this guide, you’ll walk into your next interview with confidence.

Table of Contents

• Why Mock Interviews Matter
• How to Structure and Run a Mock Interview
• Common Challenges and How to Overcome Them
• Tools, Platforms, and Resources for FAANG Mock Interviews
• FAQ
• Conclusion

Why Mock Interviews Matter

When preparing for FAANG-level roles, many engineers find themselves practicing algorithms, reading system design blogs, and rehearsing behavioral stories. That’s important, but often not enough. What matters is being able to perform under pressure, which you can train by simulating real interview conditions. That’s where mock interviews come in.

You might be able to solve a problem at your own pace, but in the heat of an interview, time pressure, an interviewer asking clarifying questions, and trade-offs can throw you off. Mock interviews help bridge that gap by training you to think out loud and maintain composure under pressure. 

Key Benefits of Mock Interviews

• Immediate feedback loops: you learn what you missed, why you missed it, and how to improve.
• Stress rehearsal: you get used to the environment of an interview, with details such as whiteboards, screen sharing, live coding, and follow-up questions.
• Pattern recognition: while no interview is the same, over multiple mocks you begin to internalize patterns in interviewer behavior.
• Confidence building: The more mock interviews you do, the less fear of the unknown you’ll experience.

How to Structure and Run a Mock Interview

A mock interview has to feel close to the real thing to benefit you the most. It’s important to plan your environment. Use the same tools you’d expect in a real interview, such as CoderPad. Timebox your segments and ensure you have no distractions. Use a video recording or screen capture if possible, so you can review your own performance later.

Divide your mock interview into segments covering coding and algorithms, system design, and behavioral questions, and choose the question types strategically. You can always adjust these depending on the company you’re planning to interview with. To simulate a real interview environment, the ‘interviewer’ should ask clarifying questions, present small changes to requirements, push on trade-offs, or request optimization. It’s also important to not work in silence. The interviewer has to mimic follow-up questions, interrupt with hints, or ask questions about edge cases.

Afterwards, your ‘interviewer’ should provide you structured feedback across different segments such as problem understanding and clarifying questions, algorithm design approach and trade-offs, code correctness, edge cases and performance, and communication clarity, pacing, and structure. You could even score across these categories to track your progress over time.

Thus, it’s wise to use multiple mock interviews, each time focusing on one or two weak points. This way, your performance should improve over time. Some coaching platforms claim that candidates undergo around 3-5 mock interviews before their real interview, increasing their odds of passing technical rounds by 70 percent. But take this with a grain of salt, since companies also want to sell their pretty picture.

Types of Mock Interviews

Peer-to-peer mocks: Great for early and ongoing reps: low cost, low friction, and frequent practice. Platforms like Pramp/Exponent Practice match peers and provide real-time feedback.

Expert / ex-FAANG mocks: Best for late-stage polish or when you need company-calibrated feedback and realistic pressure. Interviewing.io and Hello Interview pair you with senior engineers who’ve run loops at Amazon, Google, and Meta.

AI / bot-based mocks: Useful for volume reps, quick drills, and off-hours practice. AI can generate varied prompts, basic critique, and timing discipline, though nuanced coaching remains limited. Tools range from Exponent’s AI feedback to specialized AI mock apps.

Hybrid models (AI + human): Combine AI breadth (lots of reps, instant prompts) with human depth (trade-off probing, communication coaching) to get the best of both.

How to Design a Mock Interview

Question mix (coding, system design, behavioral)

A realistic session touches all three pillars:

• Coding/DSA
• System Design
• Behavioral

Timeboxing & session segmentation

A strong template (≈75–90 mins):

• 45 min coding
• 20-30 min system design
• 10 - 15 min behavioral
• 15 min feedback

Several platforms align to the ~45 min problem + feedback formats, making it familiar.

Simulating interviewer behavior and follow-ups

Have your interviewer:

• Ask clarifying questions and add constraints midway
• Push on complexity, memory, or failure modes
• Request optimization or extension

This is where your adaptability is built, something practice sites and coaching platforms stress.

Record and self-review setup

Always record (screen and audio). Afterwards, reflect on the following:

• Where you hesitated or skipped edge cases
• Whether you stated a plan before coding
• If tests were incremental and meaningful

General career resources recommend recording mock interviews for self-critique; it’s widely adopted in both university career centers and professional prep.

Feedback and Improvement Cycle

Feedback rubric

Score each dimension 1–5:

1. Problem understanding and clarifying questions
2. Solution design and trade-offs
3. Code correctness and edge-case coverage
4. Performance and optimization
5. Communication clarity and structure
6. Confidence and pacing

A rubric turns subjective comments into trackable metrics, mirroring how many interviewers internally calibrate.

Tracking progress and building an error pattern log

Maintain a simple table (date, type, scores, notes, next focus). Add an error pattern log listing recurring misses (e.g., off-by-one, null handling, test strategy). Review this for 60 seconds before each mock interview.

Turning feedback into action plans

Pick one or two improvements per session. This micro-retrospective approach compounds quickly. Career guides emphasize the value of iterative feedback; engineering-specific platforms echo the same principle: feedback + repetition = faster gains.

Common Challenges and How to Overcome Them

Even with the best intentions, you could stumble upon some challenges in your mock interviews. It's best to tackle those before the real deal, so here’s how to navigate those hurdles. 

Performance anxiety

During mock interviews you may freeze, stumble, or go blank. Overcome this by starting with easier warm-up problems before moving to full mock interviews. Using mindfulness techniques to stay calm and reminding yourself that mistakes are human and that you can get great feedback out of them. 

Poor or vague feedback

A simple ‘good job’ is unhelpful. Instead, insist on asking your mock interviewer to be explicit about what to improve and how, with feedback like: 

• Which edge cases you missed 
• How you could optimize your code from O(n²) to O(n log n)
• How you could improve your communication with your interviewer

Mock interviews that feel too easy or unrealistic

If the mock questions are too easy, they won’t help with stress-testing your limits. Ask for harder questions or questions with a twist. On the other hand, don’t start with mock interviews that are too hard too early. 

Limited access to quality mock interviewers

It might be a struggle to find ex-FAANG interviewers or expert coaches (within a reasonable price range). If this is limiting you, you could also try peer interviews with ambitious engineers, use platforms that are within your price range that offer skilled mock interviewers, or use AI-based mock interview tools - though we recommend being cautious about their feedback sometimes and seeing these as purely supplemental. They’re definitely not a replacement for the depth and nuance that humans bring.

Generally speaking, free mock platforms offer great services, but paid platforms offer more depth.

Tools, Platforms, and Resources for FAANG Mock Interviews

The following list covers some FAANG mock interview platforms that will help you simulate FAANG interviews at home. 

Popular paid/Expert platforms 

• IGotAnOffer: widely used coaching and mock interview service for FAANG roles.
• Interviewing.io: offers real-time mock interviews with ex-engineers.
• Pramp:  also offers real-time mock interviews with ex-engineers.
• Private coaches/freelancers: you can find experienced mock interviewers via tech communities or referrals.

Free and DIY Resources

• Peer mock groups: pair up with other interview candidates to alternate as interviewer/candidate.
• Open-source mock interview bots/platforms: there are bots out there built for coding practice.
• LeetCode/HackerRank timed sessions: simulate time-constrained coding rounds on your own.
• YouTube mock interviews: watch sample FAANG mock interviews

It can be a challenge to pick the right tool. Think about matching your level and budget. Free tools work early on in your prep, expert mock interviews are more valuable closer to your real interview. Also keep an eye on how the platform you’re using gives feedback and if the feedback is of quality. 

If you’re interviewing with a specific company like Google, Meta, or Amazon, look for coaches that are familiar with loops within those companies. And always record your sessions for self-review.

Example schedule for planning your mock interviews

Frequently Asked Questions

How many mock interviews should I do for FAANG?

Aim for 5–10 mock interviews, mixing peer, expert, and AI platforms. This pace balances coding interview mock sessions with time to work on feedback you’ve been given.

Are free peer mocks enough?

They’re excellent for volume and building some confidence. For late-stage polishing, add ex-FAANG mock interview coach sessions for more depth.

Can AI replace human interviewers?

AI mock interview tools are great for repetition and timing, but human interviewers provide more quality and context when it comes to trade-off probing and interpersonal feedback. Use AI as supplemental practice.

What’s a good mock interview schedule template?

Weekly: 1 peer + 1 expert + 1 review day. Monthly: at least one multi-round mock interview to build endurance.

How do I reduce mock interview anxiety?

Start with a warm-up, narrate your plan before coding, and treat misses as input to your mock interview improvement plan. 

Conclusion

A mock interview is more than just a rehearsal. You practice clarity, composure, and your ability to adapt in the exact conditions that define FAANG interviews. We’ve explained why mocks matter, how to structure and run a mock interview, and how to manage challenges such as anxiety, vague feedback, and unrealistic questions.

The baseline is simple: practice performance over just practicing problems. Do that by tackling every mock interview as if it’s a real interview and see them as taking steps toward your onsite. Start your prep early, with intent, and utilize company-calibrated mock interviews in the final stretch of your prep. And always keep track of your progress and where you could improve.

With that, you’ll walk into your next interview prepared and with confidence. Don’t forget that while mock interviews are an important step in your preparation, practicing leetcode is also key. Luckily, we’ve got just the tool for that. Go out there, practice those mocks, and use Leetcode Wizard where necessary.