From Phone Repair Founder to Head of AI
When Spanish entrepreneur Santiago Fernández de Valderrama Aparicio decided to pivot from running a retail phone repair company to a full‑time AI career, he discovered that job hunting was almost a second full‑time job. Instead of manually combing through hundreds of listings, he treated the challenge as an AI project. Using Anthropic’s Claude Code and what he calls “vibe coding”, he built a tool named Career‑Ops that could read and evaluate job ads against his skills and interests. Over six weeks, his tool analysed more than 740 openings and shortlisted 66 roles worth applying for. Those 66 targeted applications turned into 12 interviews, and eventually an offer as head of applied artificial intelligence at a software company in Seville. He later released the tool publicly, choosing not to monetise it because he saw job seeking as a basic need. His story shows what’s possible when you treat your job search like a data problem.
The Job-Hunting Workflow Behind His AI Tool
Under the hood, Santiago’s custom tool followed a simple workflow that anyone can copy without writing code. First, it collected job data: pulling listings from platforms and storing the text of each ad. Second, it filtered by hard criteria such as location, seniority, required skills and salary expectations. Third, it ranked roles by how well his experience matched the description, surfacing the top opportunities instead of a messy list of 700+ links. Finally, it kept track of notes: which CV version he sent, when he applied, and any feedback after interviews. This is the same logic behind an efficient AI job search: gather everything into one place, use clear rules to remove poor fits, then focus your energy on high‑probability applications. You do not need to build Career‑Ops to benefit; you only need tools that can read, compare and summarise text reliably.
Recreating the Same System with AI Chatbots and Spreadsheets
Malaysian job seekers can recreate Santiago’s workflow using everyday tools instead of custom code. Start by collecting listings from sites like JobStreet, LinkedIn, Hiredly and government portals. Paste each job description into a spreadsheet, with columns for role title, company, link, platform and pasted text. Then, use an AI chatbot to analyse batches of roles. For example: copy 5–10 job descriptions, paste them into an AI chat and prompt, “Compare these roles against my CV below. Score each from 1–10 for fit, list missing skills, and recommend which three I should prioritise.” Use the chatbot’s output to populate new columns in your sheet (fit score, must‑have skills, nice‑to‑have skills, red flags). Over time, your spreadsheet becomes a lightweight ATS: you can sort by score, track application status and update notes after interviews. This approach lets you effectively automate job applications prioritisation without any technical background.
AI Resume Tips, Cover Letters and Interview Prep That Don’t Sound Generic
AI can supercharge your CV and cover letters if you feed it the right inputs. For CV tailoring, try: “Here is my master CV and a job description. Rewrite my CV to highlight only relevant experience, using clear, measurable achievements. Keep it to two pages and Malaysian English.” For an AI cover letter, avoid one‑click templates. Instead, prompt: “Write a concise AI cover letter using my CV and this job ad. Use a human, specific tone. Include two short bullet points linking my experience to their requirements.” For interview preparation, paste the job ad and ask: “List 10 likely interview questions for this role in Malaysia, plus strong example answers based on my experience.” Always review the outputs for accuracy, correct jargon and local context. Adjust language for English, BM or bilingual applications so your job hunting workflow stays aligned with how roles are advertised here.
Staying Ethical: No Spam, No Blind Trust, Better Data Hygiene
Automating parts of your AI job search doesn’t mean spamming every vacancy. Santiago’s tool recommended only 66 applications out of more than 740 listings, and that focus is a lesson in ethics and effectiveness. Use AI to apply better, not just faster. Set rules: only apply when you meet a minimum skills match, can customise your CV, and genuinely want the role. Double‑check every AI‑generated CV line and AI cover letter for truthfulness and cultural fit; never claim skills you don’t have, and correct any exaggerated language. For data safety, avoid pasting full identity details (IC number, full address) into public tools. Share just enough professional information—roles, skills, achievements—for the model to help. If you use cloud documents or automation platforms, secure them with strong passwords and restrict sharing. When used thoughtfully, AI helps you stay organised, targeted and honest throughout your job hunting workflow.