🏆 Community Challenge: What's working in hiring right now?

Hello everyone,

I can share, what I consider a basic tip, that usually saves some time from the initial search work.
Before jumping into any type of search and loosing valuable time, I suggest using an LLM like Claude, ChatGPT or Gemini. Get the job description for the role you will be sourcing for, attach it and ask the LLM to analyze it. 

Ask it to provide 10 different names for the same role, similar industries/sectors and a few boolean search strings ready to be copy pasted into Linkedin Recruiter keyword search. 

Personally, I’ve created an AI Agent for the company. Consultants/Recruiters/Sourcers just need to pick the document with the job description or the meeting notes that the client provided for the role and ask to create the boolean search strings. 
What usually took them between 30minutes to 1hour, they take just a few minutes to try different variations of the role and start searching right away.

Hope it helps and best regards,

Eduardo Alves - Sourcing & Talent Attraction Manager

Hello community!

On Building Trust - A brief, real conversation early in the process creates a human connection that automated emails simply can’t replicate, helping candidates feel seen and understood from the start. That initial trust carries through the rest of the process, so even when assessments, scheduling, and structured interviews are automated, the experience still feels thoughtful and personal.

Best,

Sandra Lief

FairchildHR

Hi ​@Eduardo Alves - Smart move starting here before ever opening a sourcer tool!

Decoding the JD first, pulling alternative titles, adjacent industries, and ready-to-paste Boolean strings, is exactly the kind of upstream thinking that compounds over time. And building it into an Agent so your team doesn't even have to prompt it manually? That's the real unlock.

Thanks for kicking us off with something immediately actionable. This is what peer learning is all about. 🙌

👉 Quick starting prompt for anyone wanting to try it today: "Analyze this JD. Give me 10 alternative titles, 3 adjacent industries, and 5 Boolean strings optimized for LinkedIn Recruiter."

Spot on ​@Sandra Rebecca Lief - This is such an important counterbalance to the automation conversation.

Everyone is talking about efficiency, but you're pointing at something that actually drives outcomes: candidates who feel seen early are more likely to stay engaged, show up authentically, and ultimately say yes. That early human moment acts as an anchor for everything that follows.

The sequencing insight here is key. Lead with a real conversation, then let automation handle the logistics. The process feels personal because it started personal.

Thanks for bringing the human element into this thread. Easy to overlook, hard to replace. 🙌

We’ve been experimenting with using AI for something similar. We’ve been taking traditional job descriptions and using AI to turn them into a “Day in the Life” narrative. It shifts the focus from a list of requirements to a more human, relatable view of the role.

Candidates get a clearer picture of:

• what their mornings look like
• who they’re working with
• what success actually feels like in the role

It’s been especially helpful for surfacing overlooked talent. When people can see themselves in the work, they’re more likely to raise their hand, even if they don’t feel like they check every box on paper.

Yay another great challenge! What works for me is a Success Criteria Reset at intake.
Before sourcing, I align with the HM on 3-4 non‑negotiable success criteria (observable outcomes, not skills or years), plus explicit “acceptable gaps’: what the hire can realistically learn in 3–6 months.

Each criteron is mapped to a sourcing clue and an interview question, so we assess consistently end‑to‑end.
As a result, I get faster screening, fewer late‑stage vetoes, and more “non‑obvious” candidates who actually perform.

Today’s candidates are tomorrow’s talent.
Every interaction is an opportunity to build our future workforce.
Ensure thoughtful documentation—each conversation counts.

I’m all about building trust with candidates. I like to use AI for scheduling, reminders, and administrative tasks so I can spend more time where it matters most—building real relationships.

In a world of AI, automation, and speed, trust has become the true competitive advantage in recruiting. Candidates don’t expect perfection—they expect honesty, communication, and respect. That’s what makes this work so rewarding—knowing my candidates trust me throughout the process.

I’ve also recently started using AI to create screening questions aligned to each job description, then refining them as needed. It’s helping me focus on true must-haves while also recognizing trainable skills and potential that might otherwise be overlooked.
 

​@StevenAmrhein I am going to use your strategy on future job postings. Thanks for sharing! 

🌟 What a thread this is becoming!

So many great perspectives coming in and some real patterns emerging across all of them.

​@StevenAmrhein Reframing the JD as a "Day in the Life" narrative is a brilliant way to widen the top of the funnel by making the role feel real and relatable rather than a checklist to qualify against. Paired with ​@Najat Andreozzi Success Criteria Reset, which anchors the whole process to observable outcomes rather than proxies like titles or years, and you have a sourcing and screening foundation that's genuinely built for finding potential over pedigree.

And threading through all of it is what ​@Tracie_Bouye Tracie and others keep coming back to: trust is the competitive advantage. Whether it's saving automation for scheduling so you can show up fully in conversations, or making sure every candidate interaction is documented thoughtfully as a long-term talent investment, the message is consistent. Speed and efficiency matter, but the human moments are what candidates remember.

Thanks for sharing also ​@Talent Architect_Cybersecurity!

Keep it coming, this thread is turning into a real playbook. 👏

Most recruiters are drowning in applications and still missing the right person. The problem isn’t volume, it’s signal.

What’s working for me right now is flipping the funnel:

Instead of filtering in, I’m deliberately filtering out early and then going deeper on a smaller group.

Practical example:

• I ignore 80% of CV noise and focus on evidence of outcomes (revenue generated, problems solved, improvements made)
• I headhunt adjacent industries where the skill transfers, not just identical job titles
• I use AI to summarise and compare candidates quickly, but the decision still comes from a human conversation

The real edge though is this:
I call people others won’t.

Candidates who are:

• Slightly off brief
• Not actively looking
• Overlooked because they don’t tick every box

That’s where the “hidden gem” actually lives. Not in the 200 applicants, but in the 20 people no one else bothered to speak to.

Hiring hasn’t gotten harder. It’s just louder.