A GitHub repository with 63,000 stars and counting. The repository's name is straightforward: ai-job-search. It's a tool that uses AI to assist with job searching.
The creator of the repository is Dr. Maas Lorentzen, a Danish geophysicist. In mid-December 2025, while on parental leave, he received a layoff notice. At the time, he was experimenting with Claude Code, which he used to automate his job search process. This included finding job postings, checking if they were a good fit, writing resumes and cover letters, and preparing for interviews. He applied to 69 jobs, had 20 first-round interviews, and received one job offer. He started working as an AI engineer in June 2026. The repository rose to the top of GitHub's weekly rankings for two consecutive weeks, and the number of stars doubled in just two and a half months.
Most people interpret this story as "AI automates job searching." However, I see it differently. The
The automation projects I've seen over my 30 years in corporate IT were similar. More often than not, they fizzled out not because the technology was lacking, but because we didn't define who would verify and where the hand‑off to a human would occur. So, when someone is evaluating the adoption of an agent, I recommend they first ask three questions: Who—or which agent—will review this deliverable? Is there a documented list of tasks that AI must never perform? And where exactly does the AI stop?
If you have answers to those three questions, any tool will work. Without them, whatever tool you use will ultimately produce a result as inflated and meaningless as a padded résumé.
He delegated the work to AI.
He didn't delegate the decisions.
And he became an AI engineer.
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