Stability control for agent workflows including coordination under shared objectives, tool-augmented execution chains, and feedback loops. Addresses emergent instabilities in autonomous agent ensembles.
Agentic instability emerges from interaction patterns, not component failure. Each agent may operate correctly in isolation while collective behavior degrades. The coupling between agent actions, feedback interpretation, and goal pursuit creates emergent dynamics that no single agent can observe or attribute.
These scenarios demonstrate how agent-level behaviors propagate into system-level instabilities. Each scenario isolates a different coupling mechanism between autonomous agents and their collective emergent behavior.
Three diagnostic scenarios examining structural stability under different agentic configurations. Each scenario provides pre-computed evidence artifacts for a specific multi-agent system topology.
Goal fragmentation and coordination failure in loosely coupled agent swarms pursuing shared high-level objectives.
View ScenarioCascade amplification in sequential agent chains with tool-mediated state propagation and deep execution hierarchies.
View ScenarioFeedback instability in self-modifying agent ensembles with mutual observation and continuous adaptation dynamics.
View ScenarioSupporting materials for context and technical orientation.