Is this overkill for a tiny team?

The opposite. Small teams feel the founder-as-bottleneck problem most acutely. Glen lets context you'd otherwise re-explain accumulate in one shared memory every agent reads, freeing your time, and it scales with you as you grow.

Does it span every part of the company?

Yes. Glen is org-scoped and works across whatever agents and clients your team uses, so code, sales, support, and ops agents all read and write the same company memory, no per-person silos.

Shared memory for founders

As a founder you are the context for your company, the decisions, the customer conversations, the reasons behind every bet, all of it lives in your head until you can get it out. You and your small team increasingly run AI agents across code, sales, support, and ops, but each agent starts cold and knows none of what the company has learned, so you spend your scarcest resource, time, re-explaining the same context over and over. Glen, shared memory for AI agents, gives every agent your company uses one shared, durable memory exposed as a single MCP tool, so the company's knowledge compounds instead of bottlenecking on you.

Early-stage companies live or die on how fast they learn, and a founder's job is largely to spread that learning faster than the team can lose it. AI agents are a force multiplier for a small team, but without shared memory they amplify the exact bottleneck founders feel most: every agent, like every new hire, needs the context re-explained, and that context lives in you. An agent writing code does not know the architectural bet you made; an agent drafting a sales email does not know how you position against a competitor; an agent answering a support ticket does not know the workaround you discovered yesterday. Glen breaks the bottleneck: connected over MCP, every agent reads the shared store before it acts and writes back what it learns, so context you provide once is available to every agent thereafter.

For a founder the leverage is enormous because your team is small and your time is the constraint. Instead of being the single point of context for code, sales, support, and ops, you let the company's knowledge accumulate in one shared memory that every agent reads, so the second time a question comes up, an agent already knows the answer. Because Glen is org-scoped, this memory spans your whole company, every function, every tool, rather than being siloed per person, which is exactly what you want when everyone wears five hats. As a standard MCP server, it works with whatever agents and clients your team already uses, no migration and no lock-in, and it scales with you: the memory you build at five people is the institutional knowledge that onboards your fiftieth hire's agents instantly. Connect once over OAuth or an API key and stop being your company's bottleneck for context.

FAQ

Is this overkill for a tiny team?: The opposite. Small teams feel the founder-as-bottleneck problem most acutely. Glen lets context you'd otherwise re-explain accumulate in one shared memory every agent reads, freeing your time, and it scales with you as you grow.
Does it span every part of the company?: Yes. Glen is org-scoped and works across whatever agents and clients your team uses, so code, sales, support, and ops agents all read and write the same company memory, no per-person silos.