GLIA — A holographic memory for AI agents that isn't a graph and isn't RAG

Every AI coding agent I've used (Cline, Claude, Cursor, etc) has the same problem: it forgets everything between sessions. You fix a complex race condition on Monday, and on Tuesday the agent suggests the same broken pattern again.

RAG (Retrieval-Augmented Generation) is the standard fix. You chunk files, embed them, and search by similarity. It works for direct questions. But it fails at associative reasoning. It can't connect "rate limiting fails open" with "shared Redis connection pool" if those concepts never appear in the same text chunk. The relationship exists in the architecture, but RAG is blind to it.

Graphs are the other option. Nodes and edges. Better at relationships, but rigid. If you delete 30% of your edges, you lose entire paths. And let's be honest: maintaining a massive knowledge graph for a changing codebase is a schema nightmare.

I wanted something different. Something that behaves more like a brain than a database. So I built GLIA.

What GLIA actually does