What capability means at work when anyone can produce with AI.
Why the old hiring signals broke, what to screen for instead, and how a career changes when output is cheap and judgment is scarce.
- The 7 Types of AI Users: Those Who Grow vs Those Who Plateau — The 7 distinct ways humans interact with AI—revealing who keeps control and who surrenders it. Each profile predicts radically different outcomes.
- The Collapse of Talent Signals — Why the Global Economy Loses $1 Trillion Annually to Broken Measurement—and What Replaces It
- Hiring Signals Are Obsolete: AI Just Made It Worse — AI hiring tools are optimizing the wrong layer. They make hiring faster, not better. The missing piece: measuring growth velocity—who will 10x with AI versus plateau.
- Hiring Is Broken — Not Because of AI — Resumes, degrees, skill tests — all rest on one assumption: if you've done it before, you'll do fine again. AI didn't break hiring. It exposed the broken assumption.
- Every Wrong AI Hire Is a Competitor's Advantage You Paid For — The cost of a wrong AI hire is not a weaker team member. It is a transfer. You fund the gap your competitor is closing, and often you hand them the Operator you passed over.
- What You're Actually Screening For When You Screen for 'AI Skills' — 'AI skills' is gesturing at two different things and treating them as one. Fluency is what a candidate can make AI do, and everyone has it now. Direction is whether they can steer it, and it is the whole hire.
- What to Put in Your Job Description Instead of 'AI Skills' — AI skills' sorts nobody, because everyone has it. Here are the exact lines to write instead — language that describes the judgment the role needs when the model is confidently wrong.
- What I Look For Now That the Portfolio Stopped Meaning Anything — The portfolio, the polished sample, the confident demo — I used to hire on all three. They stopped meaning anything. Here is what I watch for now, and why the tell is always a catch.
- The Uncomfortable Conversation Every CHRO Needs to Have About AI Hiring — Your ATS, your take-homes, your competency screens are now measuring the tool, not the person. Everyone in the function half-knows it. This is the conversation you have been avoiding with your team and your CEO.
- The Two Questions That Tell You If a Candidate Can Operate AI — The whole AI assessment collapses to two questions. Can they build with it? Almost everyone passes. Can they direct it, catch it when it is confidently wrong, and override it? That one sorts the room.
- There Are Two Kinds of AI Hire, and They Look Identical — Two candidates list the same tools, run the same fluent demo, say the same confident yes. Every artifact you collect reports them as one person. They split in exactly one place.
- The Take-Home Assignment Is Dead. Here's What Killed It. — The take-home was the one filter HR trusted, because it looked like real work. AI severed the one thing that made it a signal: effort. A polished submission now proves nothing about the person who sent it.
- The Most Dangerous Person You'll Hire Is Fluent With AI — The hire who worries you should be the confident one, not the slow one. Fluency with AI is common now. Judgment about when the machine is wrong is not, and that gap is what you're actually paying for.
- Stop Hiring AI Users. Start Hiring AI Operators. — The most dangerous hire on your shortlist is fluent with AI and wrong about what it tells them. Fluency is not the signal. Direction is.
- One AI Operator Is Worth a Team. That's the Hire You're Missing. — An AI Operator doesn't add to a team. They replace the need for most of one — directing the machine to do the work of several, and catching the errors a room of confident users would ship. The scarce hire is the one your process filters out.
- 'Must Have AI Skills' Is on Every Job Description. It Means Nothing. — The line is on a growing share of job posts and it screens for nothing, because it names a thing every candidate already has. A requirement everyone meets is not a requirement. It's a wish, badly worded.
- Hiring Is the First Place You'll Feel the AI Capability Gap. It Won't Be the Last. — Hiring is where the AI capability gap becomes visible first and most expensively, because you have to bet money on one person. But the same fault line runs through promotion, team design, training, and the whole economy of who counts as capable.
- How to Actually Hire for AI Capability — Without a Quiz — A quiz tests knowledge, and knowledge is the one thing AI hands every candidate for free. So a quiz measures nothing. Here is a process that measures the thing left over: judgment, watched live, when the model is confidently wrong.
- Fifteen Years of Hiring Instincts, Undone in a Year — The seasoned gut read of a strong candidate was built on a world where the artifact tracked the capability. AI undid that world in about a year, and now the instinct rewards the most fluent, most polished candidate, who may be the most surrendered.
- A Hiring Manager's Field Guide to Spotting an AI Operator — You cannot see an AI Operator on a CV. You see one in how they talk about the work. Here are the observable tells that separate the person who directs the machine from the person the machine directs.
- Every Signal You Trusted in Hiring, AI Can Now Fake — The résumé, the portfolio, the take-home, the writing sample. Every artifact you used to sort candidates was a proxy that only worked because faking it cost as much as having the real thing. AI removed the cost. The proxy is now noise.
- You Can't Train What You Can't Measure. And Nobody's Measuring This. — Your AI upskilling budget is buying more of the thing every candidate already has. It is training Fluency and never measuring Direction, and you cannot train what you refuse to measure.
- How Are You Actually Checking AI Skill? Asking Isn't Checking. — When you ask a candidate whether they use AI, you measure their confidence and their vocabulary. Neither is capability. Checking means building a moment where the model is wrong and watching what they do.
- The AI Operator: The Job Title That Doesn't Exist Yet, But Should — Your org chart has no box for the person who directs AI toward the right outcome and catches it when it's wrong. That absence is why you can't hire for it. You cannot screen for a role you can't name.
- What a Company Looks Like 12 Months After Hiring for Usage Instead of Building — Hire confident AI users for a year and the charts say you won. Output up, velocity up, everyone faster. Underneath, the share of decisions that are AI-shaped and unchecked is climbing, and the company's ability to catch a wrong answer is quietly gone.