You’re Sending Self-Driving Cars Down Unmarked Roads
AI doesn’t fail because it’s bad — it fails because your data lacks the infrastructure it needs to navigate. Language models don’t just search — they interpret. Most orgs haven’t built for that.
Nino Chavez
The MVP Mirage
Most MVPs aren’t minimum or viable — they’re just premature.
Leadership Reflection
One of the easiest traps to fall into as a leader or expert is assuming we already understand. That assumption — even when subtle — shuts down curiosity, slows progress, and can quietly place the burden of clarity on everyone but ourselves.
ChatGPT Doesn’t Eat—So Why Do I Keep Asking It to Cook?
LLMs can draft the menu, but you still have to taste the sauce. Here’s my field-note recipe for closing the fidelity gap between what ChatGPT writes and what actually works.
Experience Is Loud—Turn It Down So You Can Learn
Hard‑won patterns sound like wisdom—until they echo so loudly you miss new ideas. This month I learned: AI model tuning isn’t just prompting, shutter‑speed instincts fail at 60 fps video, and Figma spacing ≠ CSS. Beginner reps, reverse mentorship, and stranger audits keep the channel clear.
The Cake Is a Lie: Why AI Isn’t Ready
Everyone says AI can build for you — that you just describe the thing, and it ships itself. But I actually tried. I took it seriously. And what I found was brittle, inconsistent, and full of guesswork. If it took this much effort to build a landing page, what happens when the stakes are higher?
Signal or Spectacle?
Even when I’m not trying to posture, sometimes it feels like the platform does it for me. This is about the moment when sharing something honest starts to feel like a performance — and how I’m trying to stay grounded in signal, not spectacle.