Ai Resume Builder
Next.js
AI
Tailwind
ShadCN
MongoDB
Google API
Auth
Tech Stack & Features
- Next.js / React
- MongoDB Atlas
- ShadCN / TailwindCSS
Integrations:
Next.js
AI
Tailwind
ShadCN
MongoDB
Google API
Auth
About this Project
This AI-powered résumé builder streamlines the process of creating polished, professional résumés by combining modern UI development with intelligent content generation. Built with Next.js, TypeScript, Tailwind CSS, and ShadCN, the platform provides a clean, intuitive interface for crafting customized résumé sections, managing structured data, and exporting final documents. It integrates OpenAI-powered text generation to help users enhance bullet points, summaries, and job descriptions, all while maintaining full control over layout and formatting. The project emphasizes thoughtful UX design, component reusability, and fast, server-rendered performance—resulting in a tool that feels both modern and genuinely helpful for job seekers.
Challenges
Integrating AI text generation reliably
This required careful prompt engineering, rate-limiting, and handling inconsistent responses from the OpenAI API to ensure résumé content stayed professional and relevant.
Managing complex user state
This would be nearly impossible with React state alone, leading to the use of Next.js server actions and context to synchronize data seamlessly between UI components and server logic.
Balancing AI suggestions with user control
It would be important to ensure that generated text enhanced rather than replaced user input meant designing a thoughtful UX that made edits and overrides effortless.
Ensuring clean, consistent formatting
The return would sometimes comeback in different formats (markdown, html, etc.), this content required additional sanitization, trimming, and restructuring to prevent unpredictable line breaks or styling issues.
Building a scalable UI system
Tailwind and ShadCN demanded attention to component composition, semantic structure, and accessibility—especially when dynamically inserting AI-generated text into form fields.
What I Learned
Through this project, I gained valuable experience working with Next.js context and server actions to manage complex, multi-step user state in a far more organized and reliable way. I also deepened my understanding of prompt design and AI integration, learning how to shape and refine AI-generated content so it feels polished, personal, and easy for users to edit. Building a flow that mixed user input with dynamic AI suggestions pushed me to think more carefully about UX, validation, and component patterns, ultimately improving how I structure forms and interactive UI in React. Overall, the project strengthened my ability to blend modern Next.js architecture with thoughtful AI-driven features.