AI in hiring is now table stakes. In mid-2025, leaders said it wasn’t urgent. In April 2026, the attitudes flipped – here’s what it means for both sides of the interview table.
The Attitudes Just Shifted: AI in Hiring Is Now Table Stakes Read Post »
Scattered organizational knowledge AI workflows depend on is the real bottleneck. Here’s why data readiness determines AI adoption success and what to do about it.
AI Isn’t Exposing a Technology Problem. It’s Exposing a Knowledge Problem. Read Post »
Studies show AI delivers only 10% productivity gains. But they’re measuring broken adoption, not AI’s ceiling. Here’s what 10x actually requires.
Your AI Pilots Aren’t Failing Because of AI Read Post »
Most AI pilots fail not because the technology doesn’t work, but because organizations won’t commit the budget, time, and leadership required to succeed.
Why Your AI Initiative Will Fail (And You Already Know It) Read Post »
If you’ve tried to use Claude Code primitives, you’ve probably felt the confusion. Should this be a Skill? A slash command? Wait, maybe a hook? Or is this what subagents are for? You’re not alone. Claude Code gives you seven different primitives for extending and customizing its behavior, and the boundaries between them aren’t immediately
7 Claude Code Primitives Explained: The Ultimate Decision Guide Read Post »
Let’s face it: the loudest voices in tech right now are shouting one of two things: “AI is going to replace all developers.” “Just drop a giant prompt in and let the AI do the work.” Here’s the thing: neither of those ideas reflect how real engineering actually works. Tools Change, Principles Don’t In mid-2024,
The Anti-Hype Guide to AI in Software Engineering Read Post »
