Will this help with onboarding and turnover?

Yes. A new engineer's agent inherits the org's accumulated memory immediately, and because that memory belongs to the organization, nothing a departing teammate's agent knew leaves with them.

Can it keep agents consistent with our conventions and postmortem lessons?

Yes. Agents read shared context before acting and record new lessons, so conventions and incident learnings are recalled across every engineer's agent instead of relearned individually.

Shared memory for engineering managers

Engineering managers carry the context that keeps a team coherent: why an architecture was chosen, which incident taught the team a hard lesson, what a service owner needs to know before touching a fragile system, who decided what and why. As your engineers adopt AI coding agents, that context becomes the bottleneck, because each agent starts every task blind to it. One engineer's agent rediscovers a constraint your team agreed on months ago; another reintroduces a pattern a postmortem explicitly banned. Glen, shared memory for AI agents, gives your whole team's agents one durable, shared memory exposed as a single MCP tool, so the hard-won context you steward is recalled instead of relearned.

An engineering manager's real job is reducing the cost of context: making sure decisions, constraints, and lessons travel across the team instead of living in a few heads. AI agents amplify the stakes because every agent that starts cold re-incurs that cost, generating code that ignores an agreed convention, repeats a mistake a postmortem documented, or asks a question the team settled long ago. Glen makes that context durable and shared: connected over MCP, each engineer's agent reads the org's accumulated knowledge before it acts, picking up the decisions and constraints your team already established, and writes back what it learns, so the team's collective memory compounds rather than fragmenting per person.

For you this changes the dynamics you manage. Onboarding gets cheaper: a new hire's agent inherits the team's accumulated memory on day one instead of relearning the codebase from scratch. Knowledge stops walking out the door when someone leaves, because what their agent knew belonged to the org, not the individual. Consistency improves because every agent draws on the same conventions and lessons rather than each engineer's agent reinventing them. Because Glen is org-scoped, the memory spans your whole team and beyond, so a constraint one engineer's agent records is visible to a teammate's agent and to a product or design agent in the same org. As a standard MCP server, Glen works with Cursor, Claude Code, VS Code, or whatever your engineers already use. Connect once over OAuth or an API key and let your team's context compound.

FAQ

Will this help with onboarding and turnover?: Yes. A new engineer's agent inherits the org's accumulated memory immediately, and because that memory belongs to the organization, nothing a departing teammate's agent knew leaves with them.
Can it keep agents consistent with our conventions and postmortem lessons?: Yes. Agents read shared context before acting and record new lessons, so conventions and incident learnings are recalled across every engineer's agent instead of relearned individually.