Cosmic as Agent Memory: Structured, Versioned, and Queryable

AI agents get better the more they run. Every conversation turn, every task completed, every prompt refined adds to a growing body of context that shapes the next output. The compounding effect is real: an agent with 100 turns of memory and a versioned prompt history behaves meaningfully differently from one starting cold. This post walks through using a structured, versioned, API-accessible store as the memory layer for AI agents, with TypeScript examples. Agent messages, system prompts, findings, and instructions are all stored as structured, versioned, API-accessible Objects. Each new turn adds to the record. Each prompt edit is tracked. What Agent Memory Actually Needs The compounding loop only works if the memory layer has the right properties. Most agent frameworks handle working memory well. The gap is episodic and semantic memory: what the agent learned, did, and produced across sessions. Researchers at Elastic recently published a breakdown of agent memory tiers : working memory (in-context), episodic memory (past interactions), semantic memory (knowledge), and procedural memory (learned behaviors). Good persistent agent memory needs four properties: Structured : queryable by type, status, date, or custom field, not just full-text search Versioned : you need to know what the agent wrote at each point in time, not just the latest state API-accessible : any model, any framework, any language should be able to read and write it Human-reviewable : agents make mistakes; a human needs to inspect and correct outputs without touching a database Objects as Agent Outputs When an agent produces output, storing it as a structured Object gives you a queryable record with typed fields, a draft/published workflow so a human can review before promoting to production, a full audit trail of every change, REST API access from any runtime, and a dashboard UI where non-technical team members can inspect, edit, or approve agent outputs. Here's a simple research agent that stores