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I love a good AI hack. Especially when it saves me hours of mind-numbing copy-pasting.
That’s what this is really about. I had a job to do…build a list of prospects who looked like our best clients (staffing companies and others that care about job description management). I knew what kind of company I was looking for. I knew the job titles I wanted. I just needed names. And LinkedIn URLs.

How I Started (and Where ChatGPT Helped)
I kicked things off in ChatGPT. I asked it to help me find companies that matched our ideal customer profile. I gave it clues — like the size of the company, the types of roles they hire for, and what makes them care about managing job descriptions.
To be fair, it did a solid job. It spit out a spreadsheet with companies, why they matched, and even suggested job titles. This saved me a ton of time. But here’s where it fell short: I needed real people. Names. Links. Contact points. And ChatGPT just isn’t the best at that (yet).
Why Gemini Didn’t Get Me There Either
I gave Gemini a shot too, hoping for better results. But it was the same story. It helped me think about strategy and ICPs, but when I needed actual LinkedIn profiles tied to the job titles I cared about? Crickets.
Then I Tried Grok
This is where Grok changed the game. I took the list I had (those companies and job titles) and fed them into Grok. And in seconds, it started returning the actual people who worked there. With their real LinkedIn URLs.
Also, my Grok account is free. That matters because I already pay for ChatGPT and Gemini — and they get me 80% of the way. I didn’t want to stack another subscription just to get the last 20%.
Here’s What That Looked Like:
- Company A → Director of Talent Acquisition → LinkedIn Profile
- Company B → VP of Recruitment Marketing Operations → LinkedIn Profile
- Company C → Head of Recruiting → LinkedIn Profile
- Company D → Director of Recruitment Technology → LinkedIn Profile
I took all that info and turned it into a ready-to-go outbound list. It was clean, fast, and way more accurate than anything I could’ve built manually or with ChatGPT/Gemini alone.
Why This Matters to Recruiters
If you’re a recruiter reading this, think about your hardest-to-fill role right now. You know the kind of company your dream candidate probably works at. You might even know the job title they hold. But finding them?
That’s the part where hours disappear. That’s what Grok might be able to cut out for you too.
You could use the same process I did:
- Use ChatGPT or Gemini to brainstorm your target companies and titles.
- Use Grok to find real people who match — with their LinkedIn links.
- Reach out with something personal, fast.
My Stack for Prospecting (and Sourcing)
- ChatGPT: Great for ideation and organizing your thoughts
- Gemini: Nice second opinion, especially if you want Google-rich data
- Grok: Best for actually finding people. Period.
Why I Wrote This
At Ongig, we help teams clean up their job descriptions and make their hiring process better. But that only works if you’re talking to the right people. The process I just shared helped us find them, fast.
If job description chaos is on your plate, we can help there too. Request a demo to see how Ongig can simplify your JD management (and a whole lot more).
FAQs
What is Grok and how is it different from ChatGPT or Gemini?
Grok is an AI tool optimized for real-time web data and people search. It finds actual people and their profiles, not just ideas or summaries.
Can recruiters use Grok to source candidates?
Yes — especially when you know the job titles and companies you want to target. Grok gives you the people behind the roles.
Is this process compliant with data privacy?
Always double-check your outreach for compliance, but Grok pulls public data (like LinkedIn URLs), which is typically okay for sourcing.
How do I get started with Grok?
It’s part of the xAI toolset. If you have access to Grok, just prompt it with your target titles and companies — and it’ll do the rest.
Why not just use LinkedIn directly?
You could — but doing that manually is slow. Grok helps automate that step so you can scale faster.
