Code Interview AI
Practice Coding Interviews with AI. Get Scored. Get Hired.
# I Failed 6 Coding Interviews in a Row. So I Built an AI That Prepares You Better Than I Was
The embarrassing truth that made me build CodeInterview AI.
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## The Failure
Last year, I bombed 6 back-to-back technical interviews.
Not because I didn't know how to code. I'd been writing code for years. The problem was I had never actually practiced interviews. I thought knowing the concepts was enough.
It wasn't.
The first rejection stung. By the sixth, I was genuinely questioning whether I was cut out for this industry. The worst part? Every interviewer said something similar: "You clearly know the material, but you need more practice with problem-solving under pressure."
I kept thinking — there has to be a better way to prepare.
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## The "Aha" Moment
I tried LeetCode. I tried YouTube. I tried paying $200 for a mock interview with a human.
None of it felt right:
- LeetCode gives you problems but no real feedback on how you're performing
- YouTube is passive — you watch, not practice
- Human mock interviews are expensive and hard to schedule
What I wanted was something that could simulate the pressure of a real interview, score my performance honestly, and tell me exactly where I was weak — available at 2am when I actually had time to study.
So I built it.
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## Building It
I started with a simple question: What does a good technical interview actually test?
After going through dozens of real interview transcripts and talking to engineers who had passed FAANG interviews, I narrowed it down to 4 things:
1. Problem comprehension
2. Approach & communication
3. Code quality
4. Time efficiency
I built an AI scoring system around these 4 pillars. Then I curated 210+ real interview questions across algorithms, data structures, system design, and problem solving — organized by difficulty and company type.
The hardest part wasn't the code. It was making the AI feedback feel useful, not generic. It took me weeks of iteration before the scoring felt honest and actionable.
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## Where It Stands Today
CodeInterview AI is live. Here's what it does:
- Unlimited AI mock interviews — practice as much as you want, any time
- Instant scoring — get rated 0-100 with specific feedback after each session
- Progress tracking — see your weak areas improve over time
- CV & LinkedIn Analysis — on the premium plan, get AI feedback on your entire job search profile
- Salary Estimator — understand your market value before negotiating
Pricing is simple:
- Monthly: $12/mo
- 6 months: $49 (best value)
- Yearly: $89 (most popular)
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## What I Learned
Building this taught me that the best products solve a problem you've personally lived through. I wasn't building for a "market segment" — I was building for my past self who failed those 6 interviews.
If you're preparing for technical interviews right now, I'd genuinely love your feedback. What's missing? What would make this a no-brainer for you?
[Try it free → https://code-interview-ai--dapoet236.replit.app/
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Currently at: first paying users. Goal: 100 users by end of month.
Happy to answer any questions below — brutal honesty welcome.
2 Comments
Interview prep usually breaks down when practice doesn’t feel close to the real pressure, even if the problems themselves are familiar.
One thing that often changes outcomes is not the question quality, but how quickly someone can identify where their thinking slows down during solving.
Do users tend to improve more from repeated mock interviews, or from reviewing the scoring feedback in detail after each session?
Interesting build.
The thing I'd be careful with is assuming the reason you built CodeInterview AI is the same reason people ultimately pay for it.
Those sound similar, but they can lead to very different product and growth decisions.
The expensive mistake is usually not building the wrong feature. It's optimizing around the wrong reason users stay.
I wouldn't make that call casually in a thread.