Contextual memory in AI is a major challenge because current models struggle to retain and

recall relevant information over time.

While humans can build long-term semantic relationships, AI systems often rely on fixed

context windows, leading to loss of important past interactions.

Zep is a startup that's developing a memory layer for AI agents using temporal

knowledge graphs, enabling agents to retain long-term contextual information. It was founded in

2023 and was part of the Y Combinator batch of Winter 2024. Daniel Shalef is the founder of Zep.

He joins the show with Kevin Ball to talk about the challenge

of contextual memory and AI, temporal knowledge graphs, ambient AI agents, and more. Kevin Ball, or K. Ball, is the

vice president of engineering at Mento and an independent coach for engineers and engineering leaders.

He co-founded and served as CTO for two companies, founded the San Diego JavaScript meetup,

and organizes the AI inaction discussion group through latent space.

Check out the show notes to follow KBall on Twitter or LinkedIn, or visit his website,

kball.l. LLC.

Thank you. LLC. Daniel, welcome to the show. Thanks for having me, Kevin. Yeah, excited to get into this. So let's maybe start. Do you want to introduce yourself and Zep and what you all are all about?

Yeah, so I'm a software engineer and founder, and this is my second startup and my first AI startup. Like many, we're just under two years old.

And our focus is on enabling the agentic future. And the way we're going to do that,

well, the only way we can do that is to ensure that agents have the right information available to them at the right time. And so ZEP is a memory layer for agentic applications. And we focus on

mid-sized companies and the enterprise, and it's a very exciting space to be in.

So let's maybe define some terms here, because while some of our audience is familiar with all

of these different things, maybe not everyone is.

So when you say the agentic future, what do you mean by that?

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