chapter ten

10 Building an AI interview assistant: Project walk-through

 

This chapter covers

  • Building an AI interview assistant covering UX and technical implementation
  • Configuring chat, text-to-speech, and feedback features
  • Architecting the app with Next.js, the Vercel AI SDK, and Redis
  • Managing conversations, data persistence, and AI responses
  • Securing user data and preventing 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, which is built on all the fundamental tools and technologies that we’ve been working with: Next.js, the Vercel AI SDK, and Upstash Redis for data management. The full code for this project is in the project repository.

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 a large language model (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.

10.1.1 Key features

10.1.2 Technical implementation

10.1.3 Technology stack overview

10.2 Security measures implemented

10.3 Challenges during development

10.3.1 State management considerations

10.3.2 Text-to-speech integration

10.3.3 Generating feedback

10.4 Additional considerations and improvements

Summary