Roadmap
Our path from understanding coordination failures to building self-sustaining infrastructure.
This roadmap shows our path from understanding coordination failures to building self-sustaining infrastructure for testing and designing better coordination mechanisms. Detailed specifications decrease as we move away from the current phase, because we learn as we go. The work is iterative - as we test and deploy, we might discover insights that require revisiting earlier frameworks. We start with foundations to establish the right cybernetic frame of mind. The construction phase uses those foundations to generate novel coordination mechanisms. The generation phase tests these mechanisms from an incentive perspective in RL and LLM simulation environments. The validation phase then bridges the theory-practice gap by testing across real-world domains to build confidence in what works. Each phase provides immediate practical value while building capabilities for the next.
Scottish Enlightenment philosopher who pioneered empirical approaches to understanding human nature, causation, and the foundations of knowledge.
Phase 1: Hume
Foundation: Understand Multi-Scale Coordination
The first phase focuses on exploration: What exactly are these multi-scale collective intelligence problems? How should we even think about them? What frameworks from different fields (economics, political science, complexity science) might help? We focus on exploratory research to find the right frames and map the problem space.
This foundational phase explores three interconnected research areas. Mathematical Language develops the formal framework for reasoning about coordination systems—treating markets, networks, and democracies as operations on the same underlying structure. Taxonomy of Agents classifies what types of agents exist and how agency emerges at different scales. Problem Prioritization maps the landscape of coordination failures and identifies which problems are most urgent as AI systems become more capable. Together, these areas provide the conceptual foundation needed to rigorously study collective intelligence.
Click a phase to explore the research areas