Research programme
Seven papers, five manifestos
A systematic research programme on governed intelligence for regulated industries. Co-authored with Arnaud Gelas. Five published on SSRN, one on Zenodo, a seventh in preparation.
The causal spine
Enterprise AI fails because of dynamics blindness (A) → the resolution is architectural (B) → ten independent traditions converge on the same requirements (C) → the practitioner methodology includes epistemic immunity (D) → at sufficient depth, governed initiative emerges (E).
A · Diagnosis
Dynamics Blindness
Locally correct, globally non-compliant.
B · Architecture
Predictive Organization
Map, Physics, Player on claims.
C · Theory
Build the Medium
Ten traditions, one requirement set.
D · Methodology
Governed Intelligence
Epistemic immunity against decay.
E · Endgame
Autonomy to Initiative
Governed initiative emerges at depth.
SSRN working papers
Paper A · Published on SSRN
Dynamics Blindness: When AI Is Locally Correct and Globally Non-Compliant
Diagnoses the architectural failure mechanism in enterprise AI. LLMs process tokens without tracing causal chains through organisational dependencies. Chain-of-thought, RAG, tool use, and multi-agent systems do not add the missing causal infrastructure. The problem is structural, not parametric.
Paper B · Published on SSRN
The Predictive Organization: Architecture for Enterprise Intelligence
Specifies the architectural resolution to dynamics blindness. A tripartite structure - Map, Physics, Player - coupling neural perception with symbolic reasoning, operating on claims-based knowledge with prevalence weighting.
Paper C · Published on SSRN
Build the Medium: Why Organizational Intelligence Is Mechanism, Not Metaphor
Theoretical foundations. Ten independent traditions - from cell biology to social systems theory - converge on the same architectural requirements for organisational intelligence. Introduces the capability/fertility distinction and the autonomy-to-initiative transition.
Paper D · Published on SSRN
Governed Intelligence Architecture for Institutional AI
Practitioner methodology. The Governed Intelligence Lifecycle - Ingest, Consolidate, Curate, Expand, Apply - with an epistemic immunity framework protecting against six systemic knowledge failures. Introduces epistemic operational risk as a distinct risk category.
Paper E · Published on SSRN
From Autonomy to Initiative: Enterprise AI's Real Endgame
Capstone. The AI industry optimises for autonomy when the real prize is initiative - agents that perceive what matters through immersion, not instruction. Three conditions for governed initiative, the consulting pyramid as proof mechanism, governance relocation, and the domain graph as the missing middle layer.
Paper G · Published on Zenodo
The Knowledge Layer: A Reference Architecture for Delegated AI Action in Regulated Institutions
The reference architecture. What an institution has to build so a delegated AI action is defensible at the moment it commits: the claim as the atomic unit, standing computed across evidential warrant and authority, a gate that scales with consequence, and a signed replayable record bound to the basis rather than the output.
Read on Zenodo → · DOI 10.5281/zenodo.20784662 · The architecture, as a deck →
Paper F · In preparation
Ontology Governance in Claim-Level Architectures: The Bootstrap Problem, Versioning, and Cross-Domain Transfer
The ontology beneath the claim graph. How an institution starts one without a finished ontology, how it versions the ontology without invalidating what was already relied upon, and what transfers when the same architecture moves to another domain.
The Agentic Governance Stack
Five public manifestos
A five-layer governance framework spanning engineering practice through enterprise transformation. Each layer has a published manifesto with principles, values, and implementation guidance. Layers 1-3 authored by Arnaud Gelas. Layers 4-5 co-authored.
Agentic Engineering Manifesto
Principles for building systems where humans steer intent, agents execute within governed boundaries, and verified outcomes are the only measure.
Agent Software Development Lifecycle
The ASDLC - development lifecycle for agent-based systems in regulated environments.
Agent Product Lifecycle
The APLC - product governance from qualification through deployment, monitoring, and revalidation.
Intelligence Governance Manifesto
Governed intelligence as an operational discipline. Six values: governed claims over documents, traceable provenance over trusted sources, preserved contradictions over forced consensus.
Agentic Enterprise Manifesto
Enterprise-level transformation principles for organisations deploying AI agents at scale across regulated operations.
Vocabulary
Named contributions
Original concepts introduced across the research programme.
Machine-Readable Intelligence (MRI)
Dynamics Blindness
Governed Intelligence Lifecycle
Map / Physics / Player
Epistemic Immunity
Capability / Fertility
Epistemic Operational Risk
Autonomy-to-Initiative
Governance Relocation
Living Medium
Domain Graph
Circuit Breaker Principle