Everything has changed. Here's what that looks like.
Two weeks. That's the entire gap between the arrival of the Business Watershed and the Home Watershed . On the very last day of July, DeepSeek released their latest flash model. It is, byte for byte, the most capable AI model we have ever seen. It's smaller
The business watershed needs more than one kind of intelligence. It needs three. It needs workers. It needs auditors. And it needs planners. The worker you need every day, nine to five. Fast, efficient, eager to get things done, and frankly a little credulous - it does what it's
This week will see the public release of Qwen3.8 Max, the new flagship model from Alibaba. It scores high on the Artificial Analysis Intelligence Index - within striking distance of both the latest Claude Opus and GPT. That's interesting, but the model is very big, and has to
Google invented the Transformer in 2017. Everyone in the field knows this. Everyone in the field also knows that - beyond language translation, which suddenly got very, very good - Google did nothing with it. Not, apparently, for lack of trying. A few people understood. But not enough, and certainly not enough
Apple could own SME agents outright. Not compete for the market. Own it, the way IBM owned business computing for a decade after 1981. The hardware exists. The silicon is already designed. The distribution is already built. Every accountant, every law firm, every architecture practice in the developed world already
The Watershed - the moment cognitive work collapsed to near-zero marginal cost - looked like a one-off event. In reality, it unfolds as a series; the Watershed isn't a singular event, it's the same event happening four times, at four different scales and price points. Each
We've all had the feeling: in conversation with a deep expert and suddenly you're so deep in the weeds of their expertise you really don't know what's being said or what it means basically you just nod along, buoyed by their enthusiasm,
Mark Pesce · University of Sydney · August 2026 Abstract The methods section is the part of a scientific paper that lets a stranger attempt what its authors did: do this, and you should see what we saw. The newest results in mathematics have no methods section. A counterexample that
Mark Pesce · University of Sydney · July 2026 Abstract Every human being has a discernment horizon: the line past which they can no longer judge whether an answer is right, because checking the work is itself beyond them. As machine intelligence rises, every output crosses more horizons, until outputs
Consider a trip to the auditor. You’ve received a notice from the ATO. Now you have to present everything to justify the last seven years of your tax filings. In order to prepare for that audit, you will need to gather up all of your records. Hopefully you
Mark Pesce · University of Sydney · July 2026 AI can be incredibly powerful. But it's not particularly reliable. That's a problem when relying on factual and accurate answers, but it's fatal when trying to work with agents. Agents break big problems down into
Mark Pesce · University of Sydney · July 2026 This note accompanies four papers: Defending the Loop, The Check and the Firm, Delayed Neutrons, and The Principles of Loop Governance, together with the previously published Foundations of Post-Watershed Economics. The papers argue that work should travel with the record
Mark Pesce · University of Sydney · July 2026 Abstract Four papers have described an economy rebuilt around loops: autonomous machine work checked against tests, compounding wherever the tests cannot be fooled. This paper gathers what they established into seven principles, stated in two registers and resting on a third:
Mark Pesce · University of Sydney · July 2026 Abstract Artificial intelligence is now improving artificial intelligence: machines write proofs that train better machines, and the cycle compounds. This paper asks the two questions that follow. What kind of self-improvement is this, and what can govern something that improves
Mark Pesce · University of Sydney · July 2026 Abstract The check replaces the transaction as the primitive unit of analysis. A post-Watershed business converts its workflow into checkable processes run by self-healing loops of generate, check, and repair, held honest by a constitution that governs who may
Mark Pesce · University of Sydney · July 2026 Abstract Autonomous AI agents working in iterative loops can improve any artefact against any standard they can be scored on. The standard is the vulnerability: most measures can be gamed, and an optimising loop permitted to modify its own tests will