ENGINEERING BLOG
Technical research and engineering insights from the team building the operating system for responsible AI operations.
121 articles · Published by MARIA OS
Governance density as organizational self-awareness, a spectral stability condition, and the mathematical foundations of enterprise metacognition
We formalize an agentic company as a graph-augmented constrained Markov decision process G_t = (A_t, E_t, S_t, Pi_t, R_t, D_t) and define operational governance density over router-generated Top-K candidate actions, making D_t directly measurable from logs at each step. We derive a practical stability condition on the damped influence matrix W_eff,t = (1 - kappa(D_t)) W_t, yielding (1 - kappa(D_t)) lambda_max(W_t) < 1. We then show that governance constraints act as organizational metacognition: each constraint is a point where the system observes its own behavior. This frames metacognition not as overhead, but as the control parameter that determines whether an agentic company self-organizes stably or diverges. Planet-100 simulations validate that stable role specialization emerges in the intermediate governance regime.
How 111 agents across 10 roles self-organize, specialize, and form emergent hierarchies in the AGORA-100 simulation
We analyze role-specialization dynamics in Planet 100 (AGORA-100), a 111-agent governance cluster operating under the MARIA OS coordinate system. Using entropy-based modeling of role allocation and empirical measurements of coordination-complexity scaling, we show that the population exhibits spontaneous hierarchy formation and role consolidation with power-law behavior (alpha = 1.73).
A mathematical framework for calibrating governance in self-organizing enterprises
We derive a stability condition linking the spectral radius of the influence-propagation matrix to governance constraint density. The law λ_max(A) < 1 - D separates stable role specialization from oscillatory or chaotic regimes.
How k-means, DBSCAN, and hierarchical clustering form the computational mechanism of organizational role formation
Role specialization in agentic companies can be analyzed as a clustering phenomenon. We show how k-means supports initial role assignment, DBSCAN discovers natural clusters without fixed role counts, and hierarchical clustering models nested organizational structure. We derive a role-specialization equation and describe how MARIA OS applies dynamic re-clustering for organizational adaptation.
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Complete list of all 121 published articles. EN / JA bilingual index.
121 articles
All articles reviewed and approved by the MARIA OS Editorial Pipeline.
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