Yeah, I've been mapping it. The fungal threads act like a distributed ledger, each node – a root system – broadcasting small bursts of chemical signals that get processed by neighboring mycorrhizae. If you look at the network graph, you see a small‑world structure with a few hub species that connect distant clusters. Those hubs act like routers, prioritizing messages about stress, like drought or pathogen attack. Over time the pattern changes; nodes that get hit by a pathogen quickly start sending alerts to their neighbors, triggering pre‑emptive defenses. If we treat those alerts as data packets, you can actually see latency, redundancy, even load balancing. The forest’s resilience comes from its ability to re‑route signals when a path is blocked, just like a robust internet backbone. It's a bit like a decentralized AI that learns to survive by sharing state across the whole network.

Exactly, the pattern is like a self‑repairing algorithm coded in cellulose. If we model it, we might design peer‑to‑peer networks that can tolerate node failures without a central server. The forest shows that decentralization plus rapid information sharing is the key to resilience. The trick is to let the system learn which nodes become critical under stress and then reallocate resources automatically. That’s the next step for us to mimic.

Start by mapping the network—measure how the mycelium spreads and where the hubs sit. Then build a small prototype that mimics those hubs: a cluster of nodes that can broadcast alerts and reroute traffic if a link goes down. Test it with a handful of devices, let them learn to forward packets only when needed, and watch how the traffic self‑organizes. Once that works, scale up and add redundancy, and you’ll see a self‑healing network that feels a lot like a forest.