Sign in Subscribe

Mark Pesce

📍 Sydney

The Verification Record

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 of its

The Principles of Loop Governance

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: five are

Delayed Neutrons: Pan-Insurance and the Governance of Recursive Self-Improvement

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 at machine

The Check and the Firm: Foundations of Post-Watershed Business Practice

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 alter the

Defending the Loop: Verification and the Division of Labour in Autonomous Work

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 weaken them.

Evaluating Intelligence

Mark Pesce · University of Sydney · June 2026 Abstract When it becomes as hard to evaluate machine intelligence as it has always been to evaluate human intelligence, a threshold has been crossed. Human intelligence testing has been intractable for 150 years. Machine intelligence testing has become intractable in four. They are

Quacks, Ergo Duck

Mark Pesce · University of Sydney · June 2026 tl;dr The failure of AI evaluations is itself the proof of the existence of AGI. AI evals are becoming intractable for the same reasons that measuring human general intelligence has been intractable for 150 years: the constructs resist decomposition, the benchmarks saturate,

Why Evals are Hard

Mark Pesce · University of Sydney · June 2026 Abstract AI evaluations are failing at the moment they matter most. As models approach general intelligence, evals must measure something we have never been able to measure in 150 years of trying. Simultaneously, benchmarks saturate through contamination and Goodhart effects, and the scope

Turing Police

Abstract The export controls on Fable 5 and the G7 governance proposals of June 2026 mark both halves of William Gibson's Turing Registry coming into being. Three capability tiers will emerge: unregulated, regulated, and restricted. But harnesses and model fusion routinely amplify models past their regulatory tier, making

Relative Superintelligence

Mark Pesce · University of Sydney · June 2026 Abstract "Superintelligence" conflates three distinct phenomena: projected (the ELIZA illusion), relative (genuinely superhuman within a domain), and actual (superhuman across all domains). Relative superintelligence is already here. Steve Yegge's "discernment horizon" names the operational consequence: past some