New Manifesto by AI investor and researcher Raphaëlle d'Ornano introduces an investment framework for the Agentic Era and argues that the next wave of value creation will accrue to the "Orchestration Layer" within tech and non-tech companies.
NEW YORK, May 5, 2026 /PRNewswire-ÌÇÐÄVlog/ -- Decoding Discontinuity today announced the release of AGNT: The Orchestration Economics Manifesto, a groundbreaking work by founder Raphaëlle d'Ornano that sets out an investment framework for understanding value capture in the Agentic Era.
Positioned at the intersection of AI, market structure, and capital allocation, the Manifesto argues that generative and agentic AI should not be understood as another technology disruption, but as a structural discontinuity that collapses the marginal cost of cognition, shifts machines from tools to actors, and reorganizes competitive advantage around orchestration.
In AGNT, Raphaëlle d'Ornano introduces her central thesis that is intended to help navigate the Agentic Era's unprecedented valuation shift: Orchestration Economics.
Among its key principles, Orchestration Economics establishes that as intelligence becomes abundant and autonomous systems move into production, the companies that coordinate workflows, context, and decision-making across machine actors will be positioned to capture disproportionate value. The Manifesto contends that the decisive layer in this transition is not intelligence alone, but the orchestration layer built above it.
"The Manifesto is intended to give investors and operators a way to see the agentic transition as an economic and architectural shift, not just a product or model story," said Raphaëlle d'Ornano. "It offers a framework for understanding where durable value may form as AI systems move from assistance to autonomous execution."
Before founding Decoding Discontinuity, Raphaëlle d'Ornano spent more than a decade building an international financial analysis and strategic advisory firm, advising institutional investors and executive teams across venture capital, growth, and private equity on technology-driven transitions. She began publishing her thesis on generative AI in 2023, before orchestration and agentic systems became central terms in mainstream investment discourse.
Decoding Discontinuity has since grown into a leading technology publication on Substack, and the AGNT podcast has extended that research into long-form conversations. These frameworks serve as the analytical engine for a market-neutral fund she is incubating, going long on companies navigating the discontinuity and shorting those that land on the wrong side of it.
With the release of AGNT, Decoding Discontinuity is formalizing the structural argument beneath its research: that the Agentic Era will not be defined simply by model performance, but by which entities command proximity to intent, depth of context, and workflow intelligence at scale.
The publication lays out five core claims. It argues that the marginal cost of cognition is collapsing on a non-linear curve; that software is shifting from passive tool to autonomous actor; that orchestration is emerging as a new economic layer; that three structural laws help determine which companies will hold durable positions in that layer; and that many companies now carry an embedded orchestration option the market cannot yet fully price.
The Manifesto also introduces Raphaëlle d'Ornano's broader analytical architecture for the transition, including the Architectural Resilience Assessment Framework, or ARAF, and the Durable Growth Moat framework. Together, these frameworks are designed to help investors, operators, and strategic decision-makers distinguish between companies likely to control coordination in the next regime and those vulnerable to displacement or repricing.
The manifesto is now available at:
About Decoding Discontinuity
Decoding Discontinuity is a research and investment platform founded by Raphaëlle d'Ornano focused on AI as a structural break in market logic, value capture, and competitive architecture. Its work examines how generative and agentic AI reset economic assumptions across technology and non-technology sectors and develops frameworks to identify the companies most likely to control the coordination layer in the next regime.
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