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Yes, that number is real. Here’s the full story, and why I’d do it again.
Let’s start with the obvious: sending 11,450 job applications sounds insane.
But in a market where applying to 20 roles gets you ghosted by 19 recruiters, I was tired of playing fair. So I automated everything.
What followed was a wild ride through rejection, interviews, tech experiments, and a deeper understanding of how the modern job market really works.
This is a full breakdown of what happened, what worked, what failed, and what I’d recommend to anyone job hunting in 2025.
What roles did I apply?
This is an overview of the type of roles I did apply for this experiment, it was mainly finance and consulting jobs.
🧑💼 The Profile I Used
To make this experiment meaningful, I didn’t use a “perfect” profile. I used my real background, strengths, gaps, and all.
Here’s a quick overview:
- 🎓 Education: Business & Finance background, with a Master’s from a top European university
- 💼 Experience:
- 2+ years in Strategy & Value Creation at a Big 4
- 1 year of startup experience (founder/operator role)
- 📍 Location: Italy (open to relocation)
- 🧠 Target Roles: Strategy, M&A, Investment Banking, PE/VC, and Corporate Finance
- 🧰 Languages: Italian (native), English (fluent)
📄 Download the resume template I used
For your reference, this is the "Template 2", on the official LABORO app.
🧠 What I Learned
1. Most Job Boards Are a Mirage
- Over 70% of the most interesting roles I applied to were not on LinkedIn or Indeed.
- Many firms only post on their careers page or internal portals.
- Tools like LABORO that scrape those listings give you a real edge.
2. Tailoring Your Resume Still Matters
- I thought personalization was overhyped. Turns out, customization is what got me interviews.
- The AI-generated CVs adapted my experience to keywords in each job description, that helped me pass ATS filters.
3. The ATS Wall Is Real
- For most mid-to-large companies, if your resume isn’t optimized for ATS, it gets binned automatically.
- That’s why the AI scoring and keyword alignment were key to landing interviews.
4. Ghost Jobs Exist
- I discovered many listings were either expired or filled but never removed.
- After tracking results, ~15% of roles never responded at all, not even rejection. A healthy dose of skepticism is required.
5. Speed Wins
- Some interviews came from jobs I applied to within hours of posting.
- Automation helped me be first in line, a critical advantage when companies review early applicants first.
⚙️ The Stack I Used
- LABORO: To scrape jobs, match to my CV, auto-generate documents, and auto-apply
- Notion: To track which roles I was most excited about (and prep for interviews)
- ChatGPT: To help fine-tune my top 5 resumes and add context for niche roles
- Hunter.io: For occasional cold outreach when the AI couldn’t apply directly
- Calendly: For recruiters to book calls, this surprisingly improved conversion
📊 The Results
After 11,425 job applications sent using AI, the outcome wasn’t just a flood of rejections or silence. It was a detailed funnel, and it taught me more about the hiring market than any blog post or recruiter ever could.
Here's what happened:
- 🧠 132 AI Interviews
Screening bots, pre-recorded video platforms, or algorithmic Q&A systems. - 👤 71 Human Interviews
Actual conversations with hiring managers or recruiters. Some turned into multi-round processes. - 📝 268 Assessments
Case studies, take-home tasks, timed tests, mostly for consulting, finance, and analyst roles. - 🧊 6,773 Applications Ghosted
No feedback, no rejection, no update. Not even an auto-response. - ❌ 4,181 Rejected
Some within minutes, others after weeks. Often template emails, rarely personalized.
Despite the drop-off, every part of the funnel was automated. I didn’t burn out. I wasn’t checking job boards daily. I was testing a hypothesis, and building a resume funnel at scale.
✅ Final Thoughts
You don’t need to send 11,000 applications to get results. But you do need an edge.
I used LABORO to automate everything, job scraping, matching, tailored resumes, and submissions. It worked.
You can do the same.
Less guessing, more interviews.
