NextHire

Overview

NextHire started as a response to a problem I saw around me all the time. People spend hours preparing for interviews, but most of that preparation is scattered across random notes, generic question banks, and one-size-fits-all advice. I wanted to build something that felt more like a practice partner than a static resource. The goal was to make interview prep feel active, guided, and personal instead of repetitive and stressful.

The problem it solves

What makes interview preparation difficult is not only the volume of material, but the uncertainty around whether you are practicing the right things. I built NextHire to reduce that uncertainty. Rather than leaving the user alone with a list of topics, the platform helps them simulate realistic sessions, get tailored prompts, and stay focused on the role they actually want. I wanted it to feel useful for someone who knows the basics but needs sharper repetition and feedback.

How it works technically

I built the product with Next.js and TypeScript so I could move quickly without giving up structure as the app grew. The AI layer handles dynamic prompt generation and conversational responses, which allowed the experience to feel adaptive instead of scripted. I spent a lot of time shaping the flow between user input, generated questions, and follow-up feedback so the interface stayed fast and readable. A big part of the implementation was making the AI feel intentional rather than flashy.

What I learned

This project taught me that AI products become credible only when the surrounding experience is clear. The model can generate useful output, but the product still fails if the user does not know what to do next or why a result matters. Building NextHire made me think more carefully about pacing, trust, and product framing. It also reinforced how important it is to design for confidence, because good tools do not just answer questions, they help people feel prepared.