Semantic Memory Architecture
Overview
Memory is what separates an agent from a stateless function call. A language model without memory treats every interaction as isolated — it cannot learn from yesterday’s mistakes, recall why a design decision was made, or build a cumulative understanding of a codebase.
The Semantic Memory Architecture provides the persistent, queryable, and evolving knowledge substrate that makes true agent-native programming possible.
What Agents Need to Remember
| Category | Examples |
|---|---|
| Factual knowledge | Project structure, module boundaries, API contracts, config conventions |
| Procedural knowledge | Build processes, review conventions, deployment procedures |
| Episodic knowledge | Design decisions, rejected approaches, fragile code areas |
| Meta-knowledge | Self-calibration, effective tools, learned heuristics |
Three-Layer Memory Model
Drawing from cognitive science (Atkinson-Shiffrin, Tulving, Baddeley):
Working Memory
- Scope: Current session context, active task state
- Capacity: Limited (analogous to human working memory)
- Lifetime: Session-scoped
- Purpose: Holds the agent’s current focus, recent observations, and in-progress reasoning
Semantic Memory
- Scope: Facts, patterns, relationships, learned skills
- Capacity: Large
- Lifetime: Long-term, persists across sessions
- Purpose: The agent’s accumulated knowledge about the codebase, tools, and domain
Episodic Memory
- Scope: Events, interactions, decisions, outcomes
- Capacity: Large
- Lifetime: Long-term, with decay for irrelevant episodes
- Purpose: Historical record enabling learning from experience
Memory Properties
| Property | Description |
|---|---|
| Persistence | Survives session boundaries and system restarts |
| Queryability | Retrieval by semantic similarity, not just exact key match |
| Evolvability | Knowledge updates as codebase changes; stale memories retire |
| Contextuality | Retrieval is sensitive to current task and context |
| Efficiency | Memory operations don’t dominate response latency |
| Transparency | Humans can inspect what the agent remembers and why |
Memory Lifecycle
The document details the full memory lifecycle:
- Acquisition — How new memories are formed from agent observations and actions
- Consolidation — How working memory items are promoted to long-term storage
- Retrieval — How relevant memories are recalled based on current context
- Decay — How outdated or irrelevant memories are gradually retired
Cross-Agent Memory
When multiple agents collaborate, memory sharing becomes critical:
- Shared semantic memory — Common knowledge about the project
- Private episodic memory — Each agent’s unique interaction history
- Memory governance — Who can read/write what, privacy boundaries
- Conflict resolution — When agents have contradictory memories
Key Contribution
Memory is not just storage — it is an active, evolving system that requires curation, consolidation, and governance. A well-designed memory architecture makes an agent more valuable in its hundredth session than its first.