Notes
Job Finder: Starting a New Project
A job-search platform with a professional profile, saved searches, AI that reads job listings, and a section for recruiters. It is being born at 42 Barcelona and is meant to be my Trascendence: a tool for my classmates, future students, and the staff.
2 min read
I have started a new project: Job Finder, a job-search platform designed to keep the process from becoming a race of blind applications. A professional profile on one side, saved searches, job listing searches across external sources, artificial intelligence that extracts the relevant information from each listing, help generating and reviewing your resume and cover letter — and a section for recruiters, with their own listings and direct interaction with candidates.
Why This Project
There are two reasons behind it.
The first is a need I see firsthand: a friend works with the school helping students find jobs — how to write a resume, how to introduce themselves to companies, how to define their path so they can focus on what they want. All of this happens every day at 42 Barcelona, the school where I study. I have seen how that support changes people’s job searches, and I thought much of that guidance could live in a tool.
The second is both academic and personal: at 42, the final degree project is called Trascendence. I wanted mine to be not just a piece of work for passing my exams and completing my studies, but a tool that would serve the classmates who studied with me and the students who will come in the future — while also making the school staff’s work easier. If the project is to last for years, it is better for it to be born with a purpose greater than a grade.
How It Begins
I am starting in the reverse of the usual way: first the specification and the tickets, then the code. The roadmap has thirteen tickets with dependencies between them — from account access and the professional profile to scheduled searches or the relationship between candidates and recruiters — and the project is organized modularly by feature.
The first investment of time has not been in code but in research: I have documented how Apify works, the data extraction platform that the job-listing search feature will use — what it promises, what it costs, what its limits are, and which risks need to be considered, especially with sensitive sources such as LinkedIn. Product decisions will emerge from these facts, not assumptions. It is the same method I follow in my other projects: vocabulary first, facts afterward, and code once I know what it should be.
Where It Goes Next
From now on, the development log will continue appearing on this website, entry after entry, as with my other projects. The first steps are clear: account access, the professional profile, and the first saved searches. The rest, ticket by ticket.