Notes from operators who have spent decades shipping products and AI capabilities — on building AI for the global ten thousand enterprises and the mission-critical workloads that run their businesses.
Spend tripled. Usage is near-universal. Value is rare. Parsing the hype from reality — including the famous "95% of pilots fail" stat everyone misquotes — and the seven things the successful few do differently.
The cost crunch is real, the seat is dying slowly, and the meter is becoming the contract. How product, technology, and finance leaders should price the machine's work — across cloud APIs, open-source models, and the racks in between. With current pricing data for the full AI stack.
A quieter essay than the others. On what AI does to our voice, our taste, and the slow craft of becoming ourselves — the sycophantic mirror, the frictionless self, the borrowed voice, the optimised life — and five anchors that keep you yourself.
An honest definition, a four-stage maturity ladder, the landscape of who's actually playing (six layers, by vendor), the five things wrong with the discourse, the seven structural problems nobody's solved, the five places it already works, and the seven questions to ask before you sign the contract.
A practitioner's manual for product managers using AI. Ten concrete plays — from customer feedback synthesis to A/B test design to executive briefings — each with a copy-paste prompt skeleton, anti-pattern, and verification step. Plus a week-in-the-life worked example and the minimum viable PM-AI stack.
Eight phrases that mean less than they sound like, seven questions that cut through them, and the case for operational language — the kind that survives the meeting it's spoken in. Includes a real bingo card and a worked example on the word "agentic."
A clear, opinionated tour of the nine debates that define AI ethics in 2026 — bias, privacy, autonomy, accountability, labor, concentration of power, misinformation, children, and the environmental cost we keep refusing to look at. Includes infographics on AI's energy, water, and carbon math.
A working taxonomy of 28 PM skills with honest verdicts on each: how much AI changes the work, and whether the loop can be run by an agent. Plus a sample architecture for the highest-leverage agent a PM can build — the Competitive Intelligence Agent.
The six-minute version of our State of AI Monetization paper: the seat's slow demotion, the margin crunch, the 180x token spread, the rent-vs-own math, and why metering just became platform infrastructure — plus the 90-day plan.
Sovereign AI went from niche to procurement default in 18 months. The data architecture and the AI stack are becoming the same architecture. The six-layer stack, the hardware reality of the world outside hyperscale, and a competitive scan of the on-prem AI landscape.
Treat it like compliance and you will ship the next decade's worst scandals. The five categories of AI harm, the maturity ladder, ethics-washing vs operational ethics, and the three frameworks worth knowing.
The lone forward deployed engineer is the wrong model. Six years ago, I learned why — the hard way. What it takes to build a forward deployed AI team, and why design thinking is the connective tissue.
Market understanding is the only PM skill I would protect at all costs. AI changes the speed of the work — not the judgment. A live walkthrough of how to read a market in a day, with AI as your research assistant.
AI just changed shape — from something you talk to into something that does the work. What agents actually are, what they're already doing in production, why now, what's still hard, and how the world is reorganizing around them.
It's not one gap. It's five — access, language, productive use, domain integration, and the ability to build & govern — and the world doesn't get an even shot at any of them. A map of the gap and what actually closes it.
This isn't a course about using AI — learn what AI actually is, how it works, what trust means in the age of AI, and why ethics matter. A reminder that books, history, philosophy, and time outside still matter.
AI capability is racing ahead. AI education isn't keeping up. Here are the five gaps holding it back — operator-led teaching, domain-specificity, real shipping, time-to-value, and access — and how the AI Impact Foundation closes each one.
The gap between AI capability and professional readiness is growing exponentially. Most professionals aren't falling behind because they're lazy — they're falling behind because the education system hasn't caught up. Interactive charts and data inside.
Every professional course enrollment directly funds a full scholarship for an underserved student — not a percentage, not "a portion of proceeds." The full thing. A laptop, mentorship, meals, and a course that changes trajectories.