A mental model for Nous Research's open-source (MIT) Hermes agent: one agent, one memory, every surface. We'll walk its six capabilities — Connect, Remember, Schedule, Delegate, Search, Experiment — then trace a single request end to end, through persistent skill-learning memory, isolated subagents, the scheduling gateway, and five hardened execution backends.
Hermes is "the agent that grows with you." Its founding idea is that you shouldn't have a different assistant in every app. Instead it lives everywhere — Telegram, Discord, Slack, WhatsApp, Signal, Email, the CLI, and a growing list of platforms — but every one of those surfaces is just a doorway into a single agent with one shared memory.
So a project you set up from the CLI is known when you message it on Slack; a fact it learned over email is available on WhatsApp. The surface changes; the agent and its memory don't.
Hermes is organized around six capabilities. Together they're the building blocks of everything it does — think of them as the agent's components. The rest of this page zooms into the four that explain how it works: Remember, Delegate, Schedule, and the Search/Experiment pairing.
Memory is what makes Hermes "grow with you." It does three things: learns your projects, auto-generates skills, and never forgets how it solved a problem. The key move is that auto-generated skill: the first time it works out how to do something, it saves that recipe — so the next time, it reuses the skill instead of reasoning from scratch.
Big jobs blow up an agent's context window. Hermes' answer is to delegate: it hands a chunk of work to an isolated subagent that has its own conversation, its own terminal, and its own Python RPC scripts. The subagent does the messy, token-heavy work in isolation and hands back only the result.
That's what "zero-context-cost pipelines" means — the main agent's context stays lean because all the intermediate thinking happened somewhere else, out of view.
You don't write cron syntax for Hermes — you describe what you want in natural language: "every morning, email me a sales briefing." Hermes turns that into a schedule and runs it unattended through the gateway — a process that keeps firing your reports, backups, and briefings even when you're offline, "focused every time."
The last two capabilities are where work actually gets done. Search is the toolset the agent reaches for; Experiment is the set of places that work can run. Switch between them, then play the full flow to see how every component from this page snaps together.
Search gives the agent hands and senses. Backed by access to 300+ models via the Nous Portal, it can pick the right model for the job — that's the "multi-model reasoning."
Experiment is where code and tools execute — five interchangeable backends, all with container hardening and namespace isolation so a task can't reach beyond its sandbox.
Hover any component for its job, then hit Play full flow to trace a real request through the whole system.
One agent, one memory, every surface → six capabilities → memory that auto-saves skills → isolated zero-context-cost subagents → a gateway that runs work unattended → tools (Search) executing across five hardened backends (Experiment). An agent that grows with you.
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