Waypoint.
A private career intelligence platform that evaluates job fit, recommends the right CV and simplifies applications.
- Platform
- Responsive web application · Career intelligence dashboard
- Role
- Product Owner · UX/UI Designer · Full-Stack Developer · AI Systems Designer
- Timeline
- Iterative personal project · 2026
01 / CONTEXT
Problem and response
Challenge
Career information is usually scattered across CV files, job descriptions, application forms and opaque AI conversations. That makes it difficult to know what is proven, what is missing and what should be improved.
Response
Waypoint creates a confirmed and editable career knowledge base, compares it with atomic job requirements, separates supported evidence from unknowns and conflicts, and recommends the most suitable stored CV with clear tailoring guidance.
04 / DECISIONS
How the system took shape
- 01
Separated a person’s career profile from any single CV so the underlying evidence can be reused across applications.
- 02
Modelled job descriptions as atomic requirements so recommendations can explain fit instead of returning one opaque score.
- 03
Built the full-stack application with Next.js, TypeScript, Supabase and PostgreSQL.
- 04
Used Zod and Vitest to validate boundaries and protect the reliability of analysis workflows.
05 / OUTCOME
Outcome and reflection
Waypoint demonstrates a complete AI product loop: structured personal data, evidence-based analysis, privacy-aware architecture and practical application support.
The central design challenge was making AI useful without making it mysterious. The product became clearer once every recommendation had to point back to evidence the user could inspect and correct.