Introduction

Prisma is a distributed¹ action-learning² incubator, who’s work is to apply systems-change practice³ on-the-ground in spaces of experimentation in order to unlock whole-system transition pathways.

Concretely, this paper introduces an open protocol for organising and publishing transformation-oriented events, as a means for creating and evaluating experimentations in regionally-grounded action. We frame this event-protocol as a decentralised accounting system designed to create value liquidity across a hub-network, enabling funders to participate in the action-backed value created in the form of surplus-sharing dividends.

Evolutionary Transition: Higher-Order Value Creation

This paper opens up the next evolution in Prisma’s role as a project: from being a distributed action-learning incubator, to operating a protocol for distributed incubators to publish with. The purpose of our events, therefore, evolve from incubating teams and publishing case-studies, to onboarding partner hub-networks into protocol compatibility. The protocol presented is a consequence of the learnings generated from past work to date. With this protocol, Prisma aims to enable a shift from manually organising these events, to enabling a distributed system to self-organise events, whilst still maintaining whole-system integrity and alignment.

Reading Guidance

We first set the context in which this work takes place, which prisma as a project sees itself as a part of, within which it must find necessary alignments in order to balance mission with viability. The event-organising methodology is then summarised. Although still in development, this has been used to design and participate in organising transformation-oriented events. Methodology is centred early to highlight how the protocol derives from real-world actions, not the other way around. The core concepts of the protocol are introduced, before moving immediately to lower-level currency mechanics as the foundation for enabling action-backed value liquidity. Case-studies are then provided to give context-rich examples of how protocol looks in reality, before closing with business modelling, governance, roadmap and an account of present unknowns.

Footnotes

1. Distributed systems are defined in an engineering sense as an information system which generates, processes and stores data across a network of nodes, as opposed to a monolithic or centralised architecture. ↩

2. Action-learning, building on the work of Reg Revans, is used in this context to refer to the quality of inquiry of generating learnings by reflecting on the performance of real-world actions. Within the context of our work, action can be interpreted as applying practice in place, and learning can be interpreted as understanding the place living as an example within the lineage of the practice. ↩

3. Practice is defined as conscious participation and integration, as an ongoing process toward increasing capability of a given activity. (Fritjof Capra, 2023, referencing MacIntyre, 1985, p.186) ↩