I built an AI memory system inspired by one thing brains seem to do well: reinforce associations through use. Most AI memory is a notes file with search. It stores documents and retrieves them based on text similarity. I wanted something that behaved more like actual memory. I wanted paths that strengthen when you use them and fade when you do not. So mycelium stores memories as nodes with connections.
This is not just a graph database. It is an active system. When you recall a few things together enough times, the link between them gets stronger. This is a Hebbian approach to storage. If two concepts appear in the same context repeatedly, the system assumes they belong together. Ignore a memory long enough and it decays. This decay is deliberate. Forgetting is a feature, not a bug. It keeps the system from becoming a static archive of everything you have ever typed.
The core mechanism relies on SQLite with FTS5 for keyword matching. The connection graph lives on top of that. You might hear people talk about vectors for everything. Vectors exist as a secondary signal in mycelium. They are not the primary recall mechanism. The primary driver is this connection graph and the frequency of access.
