New editionSeptember 18, 2026
When capability keeps accelerating, the real constraints move to everything around it. Why the AI race is shifting from raw model capability to efficiency, economics, infrastructure and governance — and why that is not the same as slowing down.
Read the articleI thought I was moving a website. I ended up reconsidering how knowledge should survive the next generation of the internet — why Markdown, Git, and deliberately boring architecture became a technical-debt strategy, and what twenty years of WordPress taught me about enterprise modernization.
Sep 2026The next test of intelligence is knowing when not to use more of it. My LinkedIn feed is full of the same three words: “AGI has arrived.” Whether we have actually crossed that threshold will be debated for years. We do not need to settle it today. Because if…
Sep 2026Most organizations today have an AI strategy. They have copilots, AI councils, experimentation programs, model evaluations, agents and growing portfolios of AI use cases. Leadership teams are approving investments and asking every function to explore how AI…
Sep 2026Building a powerful AI model is one thing. Deploying that intelligence reliably inside enterprise business functions is something entirely different. The AI industry has made extraordinary progress in model capability. Models can reason across longer…
Aug 2026What if the most valuable output of AI is not an answer, but executable intelligence? Enterprises are rapidly putting AI into workflows, applications, agents, service desks, operations, customer journeys and decision processes. The assumption is usually…
Aug 2026AI does not remove scarcity. It relocates it, from the people who produce work to the people who must absorb it. For decades, knowledge work was rationed by the cost of producing it. A market analysis took days. A prototype took weeks. A presentation required…
Aug 2026What happens when organizations outsource not just work, but understanding AI can make an organization more capable while making it less knowledgeable. That sounds contradictory, but it is becoming possible. An analyst can produce a financial model without…
Aug 2026Producing intelligence and owning intelligence are not the same thing. The AI industry has spent three years teaching people how to produce it. It has spent almost no time teaching them how to own it. That gap is about to become the most important skill…
Aug 2026Why AI Will Move from Tokens to Skills to Business Value --- The Token Economy Has a Natural Expiration Date Every major computing platform eventually reaches the same inflection point. The underlying technology becomes abundant, inexpensive, and increasingly…
Aug 2026Episode 100 marks an important milestone for Agentic AI: The Future of Intelligent Systems . But rather than look back, this episode looks ahead. AI is moving beyond models, copilots and individual agents. As enterprises deploy hundreds or eventually…
Agentic AI is becoming more capable, but the way we design it may be fundamentally inefficient. Today, the default assumption is simple: if AI can reason about a task, let it reason about that task every time. But what happens when the enterprise already…
The AI industry has become obsessed with tokens. How many tokens did we consume? Which model is cheaper? How much does a million tokens cost? But tokens measure what AI consumes . They don't measure what AI accomplishes , and they certainly don't measure the…
Every AI feature ships an invisible bill. Cost. Energy. Water. Carbon. Hardware. Most teams see one. Almost none see the full picture. Welcome to Green, Efficient AI — a newsletter about building AI that is intelligent in output and efficient by design. ---…
Day 8 made the loop the unit of work and showed why each extra turn costs more than the one before it. Day 9 cut turns at the front by planning the route. This issue cuts turns at every step by changing what the agent calls when it gets there. Here is the…
Day 8 made the loop the unit of work. Day 9 cut turns by planning the route. Day 10 cut turns by shaping the tool. Days 8–10 all worked on the same lever — fewer turns per task. This issue works on a different one. When the turns you do run carry more weight…
Days 8–11 worked the loop itself — its turn count, its route, its tool shape, its context weight. That closes the loop chapter. This issue opens a new one. The next three days work on the platform underneath the loop, so the same work costs less every time it…
Speaking at Google I/O on Lean Agentic AI: as organizations scale from a handful of agents to thousands, systems must be efficient by design — across cost, energy, and carbon. Slides and demo available on GitHub.
A session at the Green Software Development Karlsruhe meetup on connecting Software Carbon Intensity (SCI) to agentic systems — why cost, energy, and carbon are deeply connected but not the same thing, and how to start measuring.
Keynote at CleanEnviro Summit Singapore Catalyst 2026, hosted by the National Environment Agency: why sustainability and business value are the same path, the shift to outcome-based metrics in Environmental Services, and the two dimensions of Green AI.
Presenting the Green Software Foundation's expanded vision: green software now spans carbon, energy, water, and waste, across every layer of the technology stack — from silicon to screen. What the new definition means for practitioners and decision-makers.
