Durable organizational memory—services, owners, policies, dependencies, and incident history—that agents and operators share
Exemplar
How this harness capability fits the Exemplar platform—governed agent operations, not a standalone prompt playground.
Agents without memory re-discover the same org chart, on-call rotation, and blast radius on every session—burning tokens and risking wrong targets.
Exemplar treats memory as platform infrastructure: the same entities the console uses are what MCP clients and background agents query.
A live knowledge graph of services, teams, dependencies, risk posture, and work items—fed from Git, cloud, security, and ticketing signals.
Session-spanning recall so assistants in Cursor, Claude, and the console reason over one consistent picture of production.
Model services and relationships in the catalog; Context Lake keeps memory fresh as integrations sync.
Agents retrieve only what the turn needs—progressive disclosure—instead of stuffing entire estates into every prompt.
Official documentation on docs.exemplar.dev for this capability.
Open developer guide (opens in a new tab)Contact sales
Harness Platform is scoped per deployment. Talk to us about this feature.
Related posts on exemplar.dev.
Three layers behind production agents: shaping the ask, assembling the window, and building the runtime loop. Where each discipline stops and what to invest in next.
How to structure what your AI coding agent knows — the docs directory, context boundaries, ownership, versioning, and the difference between a knowledge system that stays useful and one that silently rots.
From code completion to production actions; Context Lake, catalog, governance, and Agentic Assistant/MCP for safe automation.