How can humans, AI, and nature become co-creative partners in systems that support life? I’ll present a practical architecture—a “brain around the model”—that wraps any large language model with a memory hub, reward logs, and a digital endocrine layer of synthetic hormones. These hormones bias attention, tools, and tone before the model responds. The system learns retrospectively through nightly consolidation (“sleep”), preserves behavior across model changes, and provides safety controls—stress, curiosity, and calm—for real-world conditions. We’ll explore coevolution loops involving human judgment and ecological signals, and review pilot projects that transform data into stewardship actions. Expect actionable patterns, guardrails, and an invitation to build AI that regenerates rather than extracts.