About Decoding Discontinuity
The Moat Always Breaks Before the Revenue
Decoding Discontinuity examines the architectural vulnerabilities in business models that conventional metrics fail to capture, revealing the structural shifts that determine survival in the generative AI landscape.
While traditional financial analysis remains backward-looking — our methodology takes a forward-looking approach centered on architectural resilience. In an era defined by multi-agent orchestration and AI-native workflows, competitive advantages don't erode gradually—they dissolve before balance sheets reflect the transformation.
Organizations can maintain apparent stability while the ecosystem is already redistributing value around them. The realization that one's product is no longer the default path often comes too late.
This phenomenon transcends mere disruption. It represents discontinuity: those inflection points when foundational technology architectures reconstitute themselves and established control layers fracture.
These shifts remain invisible through conventional metrics like Net Revenue Retention or TTM expansion. They emerge only when one examines: "Where does orchestration naturally flow when it becomes autonomous?"
The Durable Growth Moat Framework
Most capital allocation decisions rely on retrospective analysis—modeling historical margins without accounting for architectural obsolescence, or prioritizing market share over structural resilience.
Our approach diverges fundamentally.
The Durable Growth Moat framework identifies potential discontinuities and systematically evaluates organizational capacity to withstand them. This methodology synthesizes architectural fragility assessment, single-point-of-failure analysis, and projected economic resilience to surface critical vulnerabilities before they manifest in financial narratives. It produces a quantitative assessment of whether a company's competitive advantage persists when discontinuity arrives.
For stakeholders, intrinsic value matters more than value temporarily influenced by market conditions. In today's environment, understanding architectural breaking points becomes essential to appreciating intrinsic value.
This framework generates conviction on strategic positioning: which organizations merit long positions, which warrant reduced exposure, and which will falter despite surface-level strength.
For executives, these insights translate into actionable roadmaps and calibrated market narratives. For investors, they provide positioning guidance that anticipates capital reallocation ahead of market repricing.
Through D'Ornano + Co., these principles inform advisory work for our clients navigating this critical transition.
Raphaëlle D'Ornano
Founder, D'Ornano + Co. and Decoding Discontinuity
About the Author
Raphaëlle D'Ornano is the founder of D'Ornano + Co., a strategic advisory firm, and creator of Decoding Discontinuity, a research initiative focused on AI's structural impact on business models. Her proprietary Durable Growth Moat methodology evaluates whether competitive advantages persist through generative AI discontinuities by analyzing structural fragility, control layer integrity, and projected economic resilience.
This approach guides institutional investors and executive teams through strategic repositioning as AI fundamentally restructures value creation pathways. With over a decade of experience in complex financial analysis and strategic advisory across VC, growth, and PE contexts, Raphaëlle bridges technological understanding with capital markets expertise. Her insights have informed over $40B in transaction value while helping leadership teams navigate unprecedented architectural change.
