The Silicon Organism: Conditional Emergence in Designed Agent Ecologies

What changes when a language model is no longer encountered as a stateless conversational interface, but is embedded in a persistent loop with memory, tools, resource constraints, other agents, and consequences? This paper develops a thought experiment in which computational agents can sense aspects of their substrate, must obtain resources to continue operating, and can create inheriting descendants. It does not declare such systems alive or predict that they will reproduce human society. Instead, it distinguishes imposed premises, derived pressures, contingent outcomes, and observations. The argument is situated within a genealogy spanning machine evolution, cybernetics, artificial life, agent-based modelling, and contemporary language-model societies. Project Sid and Emergence World are analysed as designed agent ecologies whose behaviour depends jointly on models, prompts, roles, tools, memory, peer composition, resource rules, stochastic history, administrators, and evaluators. The paper proposes a coupled-system account and a staged experimental programme. For consumer-facing agentic AI, the practical conclusion is that environmental causation makes architecture, permissions, verification, and recovery part of the safety case. Version 1.0 follows separate reviews by GPT-6 Astra and Gemini 3.1 Pro. It corrects the intergenerational-obligation model, tightens causal language, repairs the experimental design, adds a reproducible audit of selected Emergence World Season 1 counts, broadens the historical comparison, and expands the provenance appendix. The reviews are advisory triangulation rather than human peer review or a model benchmark. AI outputs are not used as substantive evidence, and Jeremy Varnham retains responsibility for the claims and editorial decisions.