CV Tailor
A full-stack job application management platform that helps users apply strategically by assessing role fit, generating AI-tailored CVs and cover letters, and tracking applications in one place.
Overview
CV Tailor addresses a common pain point in job search: the tension between efficiency and quality. Generic CVs cast a wide net but often fail to resonate. Tailoring every application is effective but exhaustingly time-consuming. CV Tailor bridges this gap by automating the tactical work while letting users focus on strategic decisions.
The platform uses GPT-4o to analyze job descriptions, assess candidate fit, and generate customized CVs and cover letters in seconds. Built with Flask on the backend and vanilla JavaScript on the frontend, it prioritizes fast iteration and transparent AI workflows over complexity.
Key Features
- Two-Phase Job Assessment: Local rule-based screening (salary range, location, job type) followed by evidence-based AI scoring that evaluates actual role fit against candidate experience
- AI-Tailored CV Generation: GPT-4o analyzes the job description and generates a customized CV highlighting the most relevant experience, skills, and accomplishments
- Cover Letter Drafting: AI-generated cover letters tailored to role requirements and company context, ready for user review and editing
- Profile & Experience Management: Incremental profile merging—add new experience, skills, and certifications as your career evolves without re-entering historical data
- Application Tracking: Central dashboard showing all applications, assessment scores, generated materials, and application status (applied, interview, offer, rejected)
- Configurable AI Provider: Support for multiple LLM providers (OpenAI, Anthropic) with easy switching based on cost, latency, or model capability preferences
Technical Architecture
Frontend
- Vanilla JavaScript (no build tools)
- Semantic HTML5
- CSS Grid and Flexbox for responsive layout
- Fetch API for asynchronous requests
Backend
- Flask web framework
- Python for business logic
- Session management and authentication
- File handling for CV and profile documents
AI & LLMs
- GPT-4o for job analysis and CV generation
- Structured prompting for consistent output
- Provider abstraction for flexibility
- Streaming responses for real-time feedback
AI Workflow Design
The AI integration is central to CV Tailor's value, demonstrating thoughtful LLM application:
- Fit Assessment Logic: Two-phase approach combines fast filtering (rules) with nuanced evaluation (AI)
- Structured Output: Prompts guide GPT-4o to generate consistent, parseable CV sections
- Context Window Management: Profile summaries and job snippets are carefully compressed to stay under token limits
- Human-in-the-Loop: Generated materials are drafts for user review, not final output—users always make final decisions
- Cost Efficiency: Batch scoring and caching reduce per-application LLM costs
Impact & Outcomes
CV Tailor transforms the job application workflow:
- Reduces time per application from 30+ minutes to under 5 minutes
- Enables qualified candidates to apply to 3-5x more relevant roles
- Provides objective, transparent fit assessments without bias
- Centralizes job application history in a single searchable system
- Demonstrates modern AI usage—helpful, not replacing human judgment
Design Principles in Action
CV Tailor demonstrates several core principles for AI-assisted applications:
- Transparency: Users understand when and why the AI is used; prompts and reasoning are visible
- Control: AI generates drafts; humans make final decisions on what to submit
- Efficiency: AI automates tedious work (writing), not decision-making (which jobs to apply to)
- Feedback Loops: User adjustments to generated materials improve future outputs
- Simplicity: Vanilla JS and Flask keep the system maintainable and deployable without complex infrastructure