Neither @OpenAI nor @AnthropicAI has ARR. In reality, each company's revenue comes from five streams that renew differently. Each headline that attempts to "annualize" an overall figure paints a misleading picture. That analysts, investors, and markets understand this so poorly deeply troubles me. OpenAI and Anthropic are two of the most important companies for anyone trying to understand the next decade of business. Yet a market that has financed hundreds of billions of dollars in compute for their growth still doesn't know how to read their revenue. That would be disturbing enough with Anthropic moving toward a potentially historic IPO in November. But the stakes are larger than a single listing. The two labs sit at the center of a vast web of interconnected deals, including the well-documented circular financing between infrastructure companies and suppliers like @nvidia. If you can't read how they make money, you can't size the systemic risk around them. This week, I published the first of a 3-part series that breaks down and explains those revenue streams to reset the conversation around their growth and financing. decodingdiscontinuity.com/p/…

When the @FinancialTimes described French insurtech @avec_alan’s latest funding round as Europe’s biggest “non-AI” fundraising of the year, it mislabeled the company in an interesting way. Under the headline: “@Prosus leads €480 million investment in French health tech startup Alan” was the original subhead: “Paris-based group raises one of Europe’s largest non-AI start-up rounds this year.” The FT later swapped that subhead for the more anodyne “The deal values the 10-year-old Paris-based group at €5.5bn.” But the difference between the two subheads goes beyond marketing buzzwords. Rather, the miscategorization is entirely understandable because it is a microcosm of the larger struggle playing out across markets as they try to price the impact of generative and agentic AI on legacy software. This is most evident in the binary debate of software versus AI. The market’s reflex may be directionally correct for some categories, but it is analytically lazy. Alan is an example of why the binary framing is wrong. It is proof that some existing companies can make the crossing to the Agentic Era. As I wrote in Orchestration Economics when discussing the February 2026 SaaSpocalypse, this is “a confused, simplistic attempt to price a structural shift in where control, coordination, and value capture reside. This is not the death of SaaS. It is the Software Sorting,” a re-ranking of where value will sit “when autonomous agents become the primary actors inside enterprises.” The harder question for investors is how to tell which companies can make the crossing and which can’t. That question reaches well beyond software. In Orchestration Economics, I reserve a specific label for a company that has secured the structural position to capture value in this new paradigm: AGNT. It is an end state, not a badge handed out for momentum. A company earns it only once it holds the orchestration position and shows the value separation that proves it. Alan has not arrived there. But of the companies I track, it is one of the clearest emerging orchestrators: a disruptor led by @jcsamuelian, @Gorintic, and Mihaela Albu that is already building the new playbook rather than an incumbent wondering whether it can. In the latest Decoding Discontinuity newsletter, I apply the Three Laws of Agentic Value to Alan to explore the lessons the companies hold.

Today, I am publishing AGNT: The Orchestration Economics Manifesto, a framework for what is becoming the largest value dislocation within the S&P 500 in modern memory. It rests on five claims: 1. The marginal cost of cognition is collapsing. The collapse is non-linear. A task that costs $100 in human cognitive labor today will cost $10 in 2027, $1 in 2028, and pennies in 2029. 2. As cognition becomes abundant, machines shift from tools to actors. For the first time, software receives goals, takes autonomous action, and delivers outcomes. The unit of economic production changes from the human labor hour to the orchestrated workflow. 3. Orchestration creates a new economic layer. The companies that control it capture the surplus of the entire transition. The entity that reorganizes itself around a new architecture - with intelligence at the core of workflows - and delivers outcomes from irreplaceable operational context through the Orchestration Layer captures the surplus of the transition. That entity is the AGNT. 4. Three structural laws predict who wins, who loses, and who the market is mispricing. Proximity to intent. Context depth. Workflow intelligence. Satisfy all three: you are an AGNT, the captain of the Agentic Era. Miss one: you are just a member of the crew. 5. Every company carries an embedded option that the market cannot yet price. Every company holds two value curves inside a single stock price: the fundamentals curve and the orchestration curve. The gap between them is an embedded option that runs in both directions. The destruction will be priced in days. The creation will be priced in years. These five claims are the spine of the Manifesto. Each is developed across the full text: the substrate that made cognition collapse, the shift from tools to actors, the emergence of the Orchestration Layer, the laws of durable value capture, and the hierarchy of firms, sectors, and positions that will fracture, fuse, or be repriced in the crossing. Find the full Manifesto here: orchestration-economics.com/

The battle to understand where and how the new durable growth moats will be built has never been more fierce.

🚨 $2B for a seed round? No product? No revenue? No demo? Thinking Machines (@thinkymachines) just made history and redefined the future of AI. Led by former @OpenAI CTO @miramurati and researcher @lilianweng, this six-month-old company raised the largest seed round ever at a $12B valuation. But it’s important to look past the eye-popping numbers to see the real story: