How I Built an AI Interview Coaching Platform

The Problem

Interview preparation is often a collection of generic questions and disconnected notes.

Candidates need a way to practice in context, answer one question at a time, and understand exactly what to improve after each response.

InterviewIQ is built around that practice loop.

The Application Architecture

InterviewIQ is a Next.js App Router application.

The application uses:

• Next.js
• NextAuth
• MongoDB with Mongoose
• OpenRouter
• Paystack

How an Interview Works

The candidate chooses a role, seniority level, and interview format.

The server validates those inputs before creating an in-progress interview session with five questions.

When the candidate submits an answer, the AI returns structured feedback containing a score, one strength, one improvement, and one practical tip.

Each exchange is stored in the MongoDB interview session.

Paystack Integration

Paid access is handled through a separate subscription path.

The server initializes transactions, verifies payments, and stores subscription state in MongoDB.

Challenges

The hardest part of an AI interview flow is maintaining structure while still allowing natural conversation.

Model output is not automatically reliable JSON, so parsing and fallback reports are deliberate safeguards.

Lessons Learned

AI products benefit from a strong application contract around the model.

Clear prompt formats, validated inputs, persisted session state, defensive parsing, and explicit fallback behavior make the AI layer easier to reason about.