10 Build an AI Interview assistant: Project walkthrough
This chapter covers
- Building an AI Interview Assistant application, end to end exploring both user experience and technical implementation
- Configuring core features, including interview type, parameters, chat-based interface, text-to-speech capabilities, and feedback generation
- Technical architecture decisions on Next.js, Vercel AI SDK, and Upstash Redis
- Implementing key components, including conversation management, data persistence, and AI response generation
- Implementing security measures to protect user data and prevent system abuse
In this chapter, we'll take a comprehensive tour through our AI Interview Assistant application, examining both its user-facing features and the technical decisions to make during development. We'll explore the architecture, built on all the fundamental tools and technologies that we’ve been working with: Next.js, Vercel AI SDK, and Upstash Redis for data management. The full code of this project is in the project repo.
10.1 Overview of the application
Our AI Interview Assistant is designed to help job seekers prepare for interviews by simulating realistic interview scenarios with an LLM-powered interviewer. The application provides personalized practice, immediate feedback, and the ability to review past performances. We’ll start by looking at the core features that define the user experience.