Hi all. I run people functions across borders, mostly in organizations where the stated problem turns out not to be the problem. One thing occupies most of my thinking right now. AI will write your change plan and your rollout note by lunchtime. It still cannot tell you who in the room stopped believing you. The starting half of our work got cheap. The finishing half never was. I write about that in a weekly newsletter called Margin. Five minutes on Tuesdays. Mostly here to read, though. AI in HR is the category that made me join. One question, if anyone wants to take it. Are you carrying a change right now that launched well and then quietly stopped being mentioned? Nobody calls those failures. They just stop appearing in the update. I think it is the most common unreported failure in our function and I would like to know if that matches your experience. Rui

It's a question most of us in the people space don't ask out loud. When something's broken, we get the call. And the instinct is almost always the same: build something. A program. A course. A curriculum. But sometimes the problem isn't a skill gap. And when we lead with training anyway, we're not just solving the wrong problem. We're building the wrong thing. On April 14th at 11am PT / 2pm ET, Ashely Aguirre and I are sitting down with Tina Schust Robinson , Founder and CEO of WorkJoy, to dig into exactly this. Tina is a leadership strategist, executive coach, and author of "Developing Your Business Leaders: A Guide to Investing at All Levels." She works with organizations to treat leadership development as a real business strategy, not just a program calendar. We're not a podcast, we're a conversation. Our goal is to be practical, honest, and useful, whether you're in L&D, HR, or anywhere else on the people side of the house. Register here: https://luma.com/i56eg5s6 As always, you can expect: ✅ A practical and engaging conversation ✅ Networking with fellow L&D pros ✅ No recordings—just real-time connection and insight The Learning Leaders Collective is a place for people in the L&D community to connect and learn from each other through our free, monthly sessions.

What does it mean or what does it look like for you to grow a culture of collective care within and beyond your organization?

How is everyone navigating the pullback on DEIA efforts (in the US, at least)? I’m seeing a mix of quiet deprioritization, reframing under different language, or doubling down more intentionally (though this one is rare).  At the same time, workplace culture and employee experience efforts seem to be getting folded into “nice to have” buckets again, which feels… familiar and not in a good way. What’s actually happening inside your organizations right now and how are you handling it with your employees?

Resumes tell you where someone has been. References tell you what their manager was willing to say out loud. Interviews tell you how well someone prepares for interviews. But none of those things reliably tell you whether the person can actually perform in the role on day one. We thought about this - especially for roles where the gap between "interview performance" and "job performance" tends to be widest: customer-facing roles, high-pressure environments, anything that requires quick judgment under uncertainty. A few things I'm curious about from this community: Do you use any form of practical assessment or simulation before making an offer? If so, what does that look like? Where do you draw the line between "thorough vetting" and "asking too much of candidates"? Has anyone found a reliable signal that actually predicts real-world performance, rather than just interview performance? Would love to hear what's actually working (and what's flopped) — especially in high-volume hiring where you can't run 5 rounds for every candidate.

We've assessed 105 candidates for AI skills — here are the insights Over the past few months, we've run 105 AI skills assessments through AISA. Not multiple-choice tests. Not self-assessments. Real conversations where candidates demonstrate how they actually work with AI. Here's what the data tells us: Most people overestimate their AI skills. The biggest gap we see isn't in whether people use AI — most do. It's in how they use it. Accepting the first output. Never iterating. Copy-pasting without verifying. Using one tool for everything when three better options exist. Knowing tools ≠ knowing how to use them. Candidates who can name every AI tool on the market often score lower than those who use two tools deeply. Vocabulary without practice consistently scores in the bottom half. Critical thinking is the rarest skill. Of our five assessment dimensions, Critical Thinking — the ability to evaluate AI output, catch errors, and understand where AI fails — has the lowest average scores. Most candidates trust AI output at face value. The top 15% do something different. They don't just use AI. They've built workflows around it. They iterate with intention. They know when not to use AI. And they can explain their reasoning — not just their results. "My team uses AI" ≠ personal proficiency. One of the most common patterns: candidates describe their organisation's AI strategy fluently but can't demonstrate personal, hands-on skill. Strategy awareness and personal capability are two different things. We built AISA because we believe AI skills are the new literacy — and like any literacy, they need to be measured properly. Not with checkboxes. With evidence. If you're hiring for roles where AI competency matters, the gap between what candidates claim and what they can demonstrate might surprise you. aisa.to

I'm a HR professional and a tech-savy person and when I started building AI agents for our People function, I made every mistake: Picked a flashy platform that forced my team to leave Gmail. Adoption: 0%. Framed it as "save HR 20% time" instead of "remove entire categories of work." Treated chatbots and real agents as the same category. They're not. Tried to convince skeptics with demos instead of letting one early win do the talking. What finally worked: Pick the ONE workflow eating your team's week Build the agent inside the tool they already use — never a new platform Set the bar at "good enough to ship with 30 min review," not "perfect" Measure removed work, not added work Let early users sell the rest of the team. Don't pitch internally. We now have agents handling onboarding plans, JDs, performance scoring, and L&D kit production. Senior team's strategic output is up, not because they have more hours, but because their hours aren't fragmented anymore. Want to go deeper? 🔗 See what we're building → aiydou.com 🎁 Test all 4 agents free (first 20 sign-ups, no credit card) → aiydou.gumroad.com/subscribe 📅 Live training session — "Deploying AI agents in HR, end to end" → https://www.linkedin.com/events/7459682079761543168/ What's the ONE workflow you'd kill first if you could?

Morning everyone, I am a founder building in the future of work space. We want to help companies operate with intelligence as they build out their workforce in the AI era. We are trying to get that ever-elusive first design partner who can write that ever-elusive trustpilot review so that we can get that ever-elusive first sale. Anyone want to help a brotha out? Our tool is live and functional. Happy to demo. Here's my LinkedIn so that you can get in touch: www.linkedin.com/in/zhengallan Thanks!

One of the things that pushed me to build Poli (AI People & Culture Assistant) was realizing how much time HR teams spend answering the same questions repeatedly: PTO policies, leave requests, compliance questions -across Slack, email, and hallway conversations. Curious how others in this community are handling it: Are you using any AI tools to deflect repetitive HR inquiries? Has anyone experimented with a repository-trained assistant, and what were the adoption challenges? What's the biggest barrier: trust, accuracy, employee skepticism? I built a proof-of-concept to tackle this and learned a ton in the process. Happy to share what worked and what didn't but mostly just curious what you're all seeing in your orgs.

Hi everyone—I'm new to the group and looking forward to learning from your experiences 😊 I’ve been thinking about how cascading goals show up in different organizations—especially in companies with 1,000+ employees—and would love to hear how it works where you are. A few things I’m curious about: How are cascading goals actually being implemented in your organization? Is this something driven more at the departmental level, or centrally? Are they mainly used for development conversations, or tied more directly to performance and business outcomes? More broadly, how does your organization use the goals feature overall? Do employees have clear visibility into how their individual goals connect to larger company priorities? Really interested in what’s working (and what’s not), particularly at scale. Appreciate any insights you’re willing to share!