Compare your résumé to any job description using AI
AI Résumé Match is a generative AI web application that helps candidates quickly evaluate how well their résumé aligns with a job description. Users upload a résumé and paste a job posting, and the system returns a clear breakdown of matched skills, missing qualifications, and explanatory context using large language models.
Beyond the end-user functionality, this project also served as a case study in AI-assisted software development, using Claude Code as an in-repo pair programmer to accelerate refactoring, debugging, and deployment.
As the application evolved, the codebase grew to include multiple routes, parsing paths (PDF/DOCX), UI states, and deployment configurations. Making cross-cutting changes—while preserving behavior and testability—became increasingly time-consuming and error-prone.
I used Claude Code from Anthropic because it operates directly inside the repository, understands cross-file dependencies, and can run and react to real command output—unlike chat-only coding assistants.
This allowed me to safely iterate on a real production codebase rather than isolated snippets.
Claude Code analyzed the full project structure and proposed multi-file refactors to consolidate duplicated logic across résumé parsing, request handling, and response formatting—while preserving existing interfaces.
I used Claude Code to run the application locally, inspect runtime and container logs, and iteratively fix issues based on actual execution output rather than static analysis.
All suggested updates were surfaced as diffs and manually reviewed before applying, ensuring full developer control over production code.
Claude Code assisted with Docker and AWS Lightsail configuration changes, validating container behavior during build and runtime.