AI-Powered Resume Builder
Next.js application that parses LinkedIn details and creates optimized, tailored CVs based on target job descriptions.
Value Delivered:
Helped over 500 beta users optimize resumes, resulting in a self-reported 30% increase in interview callbacks.
1. Project Overview
Built to demonstrate AI prompt engineering and custom React web app implementation. Solves the challenge of tailoring CVs to matching job keywords efficiently.
2. Business Problem & Goals
Core Challenge
Manually rewriting resumes for every job application is slow and tedious. Job seekers struggle to match candidate profiles to ATS keywords.
Key Project Goals:
- Build a modern drag-and-drop resume editor.
- Generate custom tailorings using OpenAI models.
- Allow PDF downloads with clean typography.
3. Technical Architecture
The frontend gathers job requirements and resume text. Next.js API routes send structured JSON prompts to OpenAI, validate outputs, and return CV contents. A client-side PDF renderer exports the finished layouts.
System Integrations Map
Mermaid Diagram Code representation:
graph TD User[User Interface] -->|Uploads Resume + Job URL| Next[Next.js App] Next -->|Extracts Data| Parser[Text Parser Engine] Parser -->|JSON Payload| OpenAI[OpenAI Chat API] OpenAI -->|Tailored Copy JSON| Next Next -->|Streams Layout| PDF[Client PDF Renderer] PDF -->|Saves PDF| User
Connected APIs
- OpenAI Chat Completions API using structured JSON output schemas
Component Stack
- ResumeForm (React Component)
- resumeOptimizer API Route (Next.js serverless function)
- PdfExport (Client-side HTML-to-PDF library)
Key Design & Technology Decisions:
4. Screenshot Gallery
Interface showing side-by-side editing pane and AI suggestion highlights.
Build in Public & Timeline
Project Timeline Phasing
Created basic prompts in OpenAI Playground.
Built dynamic forms and layout grids.
Structured JSON response schemas and tested model speeds.
Deployed to production, shared on Reddit.
Technical Build Journal
Fixed resume section corruption by switching to OpenAI's structured outputs API, guaranteeing that lists and dates return in exact schemas.
Lessons Learned
LLMs can return inconsistent formatting. Implementing strict JSON schemas using OpenAI's response format feature resolved output inconsistencies, ensuring parser engines never crashed.
Future Roadmap
- Support direct LinkedIn import via secure OAuth login.
- Integrate cover letter generator matching customized templates.
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