I help organizations make high-stakes technical decisions with clarity. My lane is the intersection of Enterprise AI, GTM architecture, and calm operator leadership where complex systems need to be translated into decisive, executive-ready action. I stabilize environments,

You level up the moment you stop executing tasks and start isolating how the system behaves. Systems reveal root causes that years of surface fixes never touch, and once the architecture is clear, problems that looked unsolvable collapse fast.

AI doesn’t fail because models are complex. It fails because organizations are. The real architecture work is stabilizing decisions, ownership, and risk paths so the system can absorb non-deterministic workflows without chaos.

Multi-model isn’t a bridge state. It’s the operating model. The edge is in how you route, instrument, and retain high-value workloads as they find their fit. Benchmarks move. Cohort retention doesn’t. https://t.co/myo8fIXJFM

A unified canvas for reference-image conditioning will dominate creative pipelines. Architecting UI layers that expose model primitives with precision converts opaque knobs into predictable workflows and unlocks real volume. The winner will standardize the handoff surface.

AI went from: • “What can this do?” • “Why not just use ChatGPT?” • “How do we govern this?” Somewhere in that shift, one signal stands out: the moment the market starts pulling the product forward. That’s PMF. https://t.co/K2smEZYMpo via @LinkedIn

If your AI product creates more organizational change than it removes, you’re pre-PMF, no matter how excited the meetings feel. I wrote about the structural reasons AI products stall before the market ever pulls. https://t.co/2OtBjDaNmT

PMF is the hard gate in AI. Demand is loud, but real pull is narrow. The moment a product stops needing persuasion and starts getting dragged by a clear buyer, everything aligns: messaging, roadmap, revenue. In this market, PMF isn’t a milestone. It’s the only compass.

Most people choose ChatGPT Plus vs. Pro based on pricing; wrong model. If you treat ChatGPT like a chatbot, Plus is fine. If you treat it like an operator running real workflows, Plus collapses. Agents aren’t “smarter bots.” They’re interns with a task budget, and most teams

Agents aren’t magic. They’re deterministic workflows executed as discrete steps. Every retrieval, transform, or generation is a task. Real pipelines routinely span 20–50 steps, so shallow task ceilings collapse under load. Higher limits simply preserve architectural

Pricing tiers are constraint models. Plus fits exploration, Business adds governance, and Pro serves operators whose workflows collapse under task caps. The tier must align with the throughput architecture of your workday.

People think AI video is about prompts. It’s not. It’s about story, clarity, and taste. Prompts just reveal whether you have any.

Nobody knows what ChatGPT Pro actually does, and half the internet is guessing. If you use ChatGPT like Google, stay on Plus. If you use it like a teammate, you’re probably underpowered. I broke down Plus vs Business vs Pro in plain English: https://t.co/BkCIiX1s4w

The Chief AI Officer isn’t a job title. It’s a career pattern. I finally wrote the piece that explains the archetype everyone’s trying to hire but can’t describe. https://t.co/YHWGaoQBXo via @LinkedIn

I’ve noticed something interesting using different AI models: In my hands, Claude tends to go abstract and reflective when I need aggressive, operator-style execution. Not good or bad, just different personalities. Curious whether others feel the same.

GPT = Generative Pre-trained Transformer. Generative → It creates text, images, code, etc. Pre-trained → It’s trained on massive amounts of data before you ever use it. Transformer → The neural network architecture it’s built on (introduced by Google in 2017).

Sat in a meeting with a 50-year-old director and two high-school interns. Interns: “What’s a fax machine?” Director: “What’s a GPT?” Tech is now aging in both directions.

My girlfriend chatted with Grok in Chinese. It cursed her out and called her “bro.” AI’s got confidence, I’ll give it that. Somewhere in there, it learned every wrong lesson from the internet.

Put this hard mode cheat code prompt into ChatGPT: “Simulate me playing life on ‘hard mode.’ No rich parents, no lucky breaks, no safety net. Show me how to win anyway.”

Leadership is about lifting people up