Nufar Gaspar

So you should deliberately get the agent to remember that.

And these are the things that you should make into a habit or even create a dedicated skill to help your agent remember the way you like it to remember.

And there is a lot of variance between the tool.

That's something that you need to know.

So it's a layer that you can probably deepen over time.

You don't need to solve it on day one, but the better the memory works and the better the overall experience becomes because memory is what makes every other layer stick across sessions.

If we're going with our chief of staff, beyond the general memory, you might want to create dedicated memory for decision logs.

For example, what was decided, why, what's the alternatives that we were contemplating and so on.

We might want to also include a dedicated memory for learning about the working processes.

because you want the chief of staff to also own an ongoing improvement.

And perhaps you want to remember relationship context, how a conversation with a specific stakeholder went, what they reacted well to, and so on.

And this is more structured than the generic memory that any tool that you use will provide and will really help your chief of staff agent to be a much better companion and helper for you.

So everything so far has made your AI smarter about you.

We move to the next layer, which is connections, and that makes it capable of acting in the real world.

And connections are how your agent reaches real systems, whether it's email or calendar, Slack, Jira, Salesforce, your databases, there are various ways to get there.

We have the MCPs or model context protocols.

This is the open standard that many tools support.

Recently, we're seeing CLI tools that give your agent more judgment to decide how to interact with the external system on its own.

And there's always the option of direct API or scripting to get connected.

You don't have to go deep on that to be able to connect your agent.