Building PreepX: What We Learned Building an AI Interview Platform
Technical interviews are difficult to practice for.
You can read hundreds of interview questions, watch videos, or solve coding problems, but a real interview is different.
Someone asks you a question.
You have to think.
You explain your approach.
Then comes the follow-up question.
And after the interview, one of the biggest problems is knowing what you actually did well and what you need to improve.
That's the problem we're trying to solve with PreepX.
What is PreepX?
PreepX is an AI-powered platform for interview practice and hiring.
The candidate side focuses on helping people practice interviews in a more interactive way instead of simply going through static question lists.
The hiring side is focused on helping companies assess candidates, conduct interviews, and manage the hiring process.
Our goal is to make the interview process more practical for candidates and more structured for hiring teams.
Why we decided to build it
We noticed that interview preparation often becomes repetitive.
You prepare a list of questions.
You read the expected answers.
You practice a few times.
But that doesn't completely reproduce the pressure and unpredictability of an actual conversation.
An interviewer can ask:
"Why did you choose this approach?"
Then:
"What happens if the traffic increases 10x?"
Then:
"Can you think of another solution?"
That interaction is difficult to reproduce with a static question bank.
So we wanted to experiment with an AI-driven interview experience.
What we're trying to improve
The core idea is simple:
Instead of only showing candidates questions, the system should interact with them.
The experience should feel closer to an actual interview.
The AI can ask questions, understand the candidate's responses, continue the conversation, and provide feedback after the interview.
The feedback is important because practicing without knowing what to improve isn't particularly useful.
The hiring side
We're also building PreepX for companies.
The idea is to bring different parts of the hiring workflow into one platform:
- Candidate discovery
- Candidate assessment
- Interviews
- Evaluation
- Hiring
We're still developing and improving this part of the product, so we're particularly interested in feedback from engineering teams and recruiters.
What we learned
One of the biggest lessons so far is that building the AI part is only one piece of the problem.
The actual user experience matters just as much.
An AI interviewer can technically ask questions and generate responses, but if the experience feels unnatural, candidates won't enjoy using it.
This means we're paying attention to things like:
- Conversation flow
- Follow-up questions
- Feedback quality
- Interview structure
- Response time
- Overall user experience
We're still early
PreepX is still an early-stage product.
That means we're still figuring out:
- Which interview formats users prefer
- What feedback candidates actually find useful
- How AI should evaluate different types of answers
- How companies want to use AI during hiring
- Where AI should assist humans rather than replace them
We're intentionally building and learning from real users instead of assuming we already have everything figured out.
We'd love feedback
If you're a developer, engineering manager, recruiter, founder, or someone who has recently gone through technical interviews, I'd love to hear your thoughts.
Some questions we're currently thinking about:
- What makes an AI interview feel realistic?
- What kind of feedback would actually help you improve?
- What would make you trust an AI-generated interview evaluation?
- Where should AI stop and a human interviewer take over?
- What part of the current interview process do you think needs the most improvement?
You can try PreepX here:
We're still early, so feedback is especially valuable right now.
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