Nathaniel Whittemore

And importantly, the harness evolves.

This is that idea that when one person figures out some skill, by which in this case we are referring to agent skills, markdown files that teach your agent how to perform a specific task, those skills can find their way into an internal marketplace that RAMP calls Dojo.

An example they give is a CX engineer building a Zendesk investigation workflow that pulls ticket history, checks account health, and suggests resolution path, which now, through this Dojo marketplace, gives the entire support team the ability to have access to that skill,

as soon as the originator of the skill makes it available.

Now, with 350 skills already shared, that's a lot to wade through.

And so, of course, they used AI once again, building an in-AI guide, which they, keeping with the theme of Dojo, call the Sensei, that looks at the tools that people have already connected, what role they're in, and what they've been working on to recommend skills that are most likely to be useful to that particular person.

A new account manager, Seb writes, doesn't need to browse a catalog of 350 skills.

The Sensei surfaces the five that matter most on day one.

What about memory?

We talked about context and context engineering in terms of the organization as a whole, but what about on an individual level?

Seb writes, when users first open Glass, we build a full memory system based on the connections they've authenticated.

This gives every chat session context on the people they work with and their active projects, along with references to relevant Slack channels, Notion documents, linear tickets, and more.

As a result, the agent spends less time searching, entering each conversation with the context the user expects.

Now, this is one of those areas where, especially if you're thinking about imitating this system, I think there's the most hidden technical complexity.

Seb continues, under the hood, we also run a synthesis and cleanup pipeline every 24 hours, mining users' previous sessions and connecting tools like Slack, Notion, and Calendar for updates.

This means Glass can adapt to their world without them having to re-explain things every session.

This is one of those things that's easier to write about than to build, even with agentic coding.

Managing memory and context is kind of the whole game right now, and there's a reason why it's a problem that so many people are still working on.

Now, one other interesting piece about this system that Ramp has built is that it takes a bunch of the features that people have looked to from OpenClaw and brings them directly into the company's agentic operating system.

For example, Seb writes that employees can schedule automations to run daily, weekly, or on a custom cron that can then take actions like posting directly to Slack.