How do you make an AI that actually \*remembers\*? Not just RAG over chunks. Real memory — the kind humans have.



  I went deep on the hippocampus, Ebbinghaus forgetting curves, complementary learning systems, and slow-wave sleep replay. Then I built it.



  \## The Architecture



  ┌──────────────────────────────────────────────────────────────┐

  │                  5-TIER MEMORY ARCHITECTURE                    │

  ├──────────────────────────────────────────────────────────────┤

  │  TIER 1+2  EPISODIC BUFFER        Brain: Hippocampus         │

  │  64 working + 256 episodic items                              │

  │  Ebbinghaus decay: n\^0.3 · e\^(-λt) · importance              │

  │                          ↓                                    │

  │  TIER 3    SEMANTIC STORE          Brain: Neocortex           │

  │  ChromaDB v2 · Hybrid dense+BM25 search                       │

  │                          ↓                                    │

  │  TIER 4    KNOWLEDGE GRAPH         Brain: Association Cortex  │

  │  spaCy NER · NetworkX+SQLite · Multi-hop reasoning            │

  │                          ↓                                    │

  │  TIER 5    COLD ARCHIVE            Brain: Distributed Cortex  │

  │  Filesystem JSON · Search · Thaw · Compact                     │

  ├──────────────────────────────────────────────────────────────┤

  │  STANDBY NEURON AGENTS                                        │

  │  ┌──────────┐  ┌──────────┐  ┌──────────┐                    │

  │  │ Personal │  │   Tech   │  │ Projects │  ...N agents       │

  │  │  Agent   │  │  Agent   │  │  Agent   │                    │

  │  │ DEEP 💤  │  │ LIGHT 🟡 │  │ DEEP 💤  │                    │

  │  │ 0 RAM    │  │ \~3KB RAM │  │ 0 RAM    │                    │

  │  │ 0 tokens │  │  ready   │  │ 0 tokens │                    │

  │  └──────────┘  └──────────┘  └──────────┘                    │

  │  Wake → Vote → Act → Sleep → Spawn → Prune                   │

  └──────────────────────────────────────────────────────────────┘



  \## The Two Novel Things



  \*\*1. Standby Neuron Agents\*\* — Agents sleep on disk (JSON = 0 RAM, 0 tokens). Wake on trigger pattern matching. Vote in consensus panels. Return to sleep. Like biological neurons — sparse activation, only fire when relevant.



  \*\*2. Neurogenesis\*\* — When a memory cluster grows distinct enough, the system automatically spawns a new specialized agent. Inactive agents auto-prune after 30 days. Nobody else does this.



  \## Sleep as a Feature



  7-stage consolidation pipeline runs automatically: Decay → Cluster → Merge(LLM) → Rescore → Promote → FindRelations(LLM) → Archive → Neurogenesis. Quick mode: 60ms. Full mode: \~3s.



  \## Test Coverage



  324/324 tests. All passing. Production-ready Python. AGPL-3.0.



  \## Why



  I'm 18, from Slovakia. Started as a vibecoding project. The memory problem grabbed me and wouldn't let go. Long-term: I believe better memory for AI could lead toward computational memory prosthesis — helping people with Alzheimer's remember.

[P] I'm 18 and built a neuron-like memory system for AI — Standby Neuron Agents [P]