Gem

This week, we're at Home Delivery World 2026 in Nashville. The BackOps AI team and I will be at booth #1151 and were looking forward to being on the ground with the leaders pushing retail, delivery, and supply chain forward. If you're attending, come and find us, we'd love to chat! Final chance to register, get a free ticket on us 👉 https://lnkd.in/g7h2iM25 #HDW2026

Your company's best retention model is your recruiting team. There's a recruiter at your company who placed someone 18 months ago and still texts them. Not officially. They just sent congrats when the hire got promoted. Followed up after a rough all-hands. That recruiter knows when the employee updated their LinkedIn headline last Tuesday. They know the employee's been quietly asking about internal transfer options. They know the employee's manager has been “fine, just busy” for three months, which in recruiter-speak means this person is about to start taking calls. Meanwhile, your analytics tools are reading trailing indicators. Engagement surveys from last quarter. Tenure milestones. Comp ratio changes. Those are rearview mirrors. They tell you what already happened. Fewer than one in four HR teams are actually highly effective at using people analytics. Only 37% frequently use it to forecast attrition. The models are getting better, but adoption is still lagging behind. The next time your people analytics team presents a flight risk model, try something. Walk over to the recruiter who placed your five most recent critical hires. Ask them: "How are those people doing?" You might be surprised at what they already know. 🙂

A candidate ghosted his start date. No call, no email. Two years later, the company almost hired him again. The recruiter who flagged him had been laid off. Her notes lived in a personal spreadsheet on her desktop and a few Slack DMs she sent to herself at 11pm. When she was walked out, all of it went with her. This is the part of the recruiter layoff conversation we keep missing. We frame it as a headcount problem. Fewer open reqs, fewer recruiters. The math seems obvious. But it’s a knowledge problem. Research found that 42% of the expertise a person uses in their role is known only to them. It can't be filled by a replacement. And recruiting is almost entirely relational and contextual. Which hiring managers go dark for two weeks. Which agencies actually fill roles versus which ones just run up hours. None of this lives in the ATS. None of it lives in the CRM. And when you lose six recruiters out of twenty in a single quarter, you don't just lose people. You lose the system. The senior recruiter who trained the mid-level. The mid-level who onboarded the coordinator. The knowledge transfer that was supposed to happen never did, because they were walked out on a Friday. What do your recruiters know that you can't afford to lose?

Really thankful for the time with such a great group of people this past week!

🚀 Today, we're launching Gem's AI Fraud Detection Agent. It’s the newest agent in Gem’s AI recruiting suite, designed to catch fraudulent applications and help recruiters focus on the real candidates. The AI Fraud Detection Agent automatically scans applications when they're submitted and provides recruiters with clear risk assessments so they can make the right call. Candidate fraud is exploding. One customer saw 88% of applications for a single engineering role were fake. An enterprise customer flagged 60% of applicants as fraudulent across their roles. And we've heard from multiple customers who've had fraudulent candidates reach the final round of interviews. The workarounds teams are using today are time-consuming and inconsistent. Some train recruiters to manually spot suspicious markers. Others send applications to security teams for review, but that's not integrated with their ATS. A few sophisticated customers have tried building custom solutions in-house, but most teams don't have the bandwidth to do so. Here's how Gem's AI Fraud Detection Agent works: → Automatically scans every application when it's submitted → Evaluates multiple signals together (resume metadata, email verification, phone verification, LinkedIn profile age and activity, person verification, IP, and device data) and assigns a clear risk level: high, medium, or low → Gives recruiters a detailed explanation of why an application was flagged, so they can make the final call on whether to advance or reject → Runs in the background with zero friction for recruiters or candidates; no new tools to learn, no extra verification steps that slow down your process → Works for any customer using Gem's Application Review, whether you're on Gem ATS or integrating Gem with another ATS 💎 The key difference: most solutions just flag individual signals and leave you to interpret them yourself. We evaluate signals together and give you an actual risk assessment. The results from customers already using it speak for themselves: "For anybody who's already a Gem customer, it's a no-brainer. One less vendor to deal with, one less approval process — and you're getting more than you had before." — Beth Wolfe , Senior Director of Recruiting at Daxko. After switching to Gem, Daxko cut its fraud check costs by 89% and saved 8-10 hours per role. "I could not talk to another fake candidate. It's draining. Now I'm actually spending my time on people who are real." — Julia Graham , Senior Technical Recruiter at OneSignal. OneSignal reclaimed 14+ hours per role after getting off manual review. If candidate fraud has been a challenge for your team, we'd love to show you how it works. → [Read the full story on the blog — link in comments 👇]

Every week, I get together with a group of guys, and honestly, it’s super grounding. I really can't overstate how much we need this and for guys to not do life alone. I totally get why we try to, though. Life is just FULL (I try not to use the word "busy" anymore because a mentor told me it's just an excuse). Between work and being a parent to a toddler, I get it. You're trying to lead your house, provide, stay healthy, and somehow manage a tiny human who essentially runs the show. It’s exhausting. Last night, things got real. No "I'm fine" or "Work's good" talk. We’re talking guys opening up about everything: drinking too much, porn, marriage rifts, and the slow hum of financial anxiety. There were only nine of us in that room, but the weight of what we were all carrying was intense. It made me wonder -- if nine random guys have all this going on under the surface, how many other people are out there struggle silently or in secret. If you're reading this, don't do life alone. Find your people. It makes all the difference.

It's time to say goodbye to shady candidates. When I first heard about applicant fraud, I thought it was a joke. But following story after story of smart people getting fooled, the next move became obvious: for us to integrate a fraud detection solution into Gem. We hope this saves you time and helps protect your company, while giving real candidates the opportunities they deserve.

Your points resonate and basically... you have piqued my curiosity, Evan Liang !

So in like 2017 I remember all of a sudden everyone in the office is wearing Allbirds sneakers. I bought a pair. Today they're like "no, screw shoes dude - we are all in on AI!" https://lnkd.in/gh5hA_cG