Datastacks is known for its expertise in scalable data solutions, particularly for Apache

Cassandra, a leading NoSQL database.

Recently, the company has focused on enhancing platform support for AI-driven applications,

including vector search capabilities.

Jonathan Ellis is the co-founder of Datastacks.

He maintains a technical role at the company and has recently

worked on developing their vector search product. Jonathan joins the show to talk about his

passion for being in a technical role, where AI fits into the Datastacks platform, developing

vector search, and he also reflects on his gradual adoption of AI in his workflows and where he thinks AI development is headed in the coming years.

This episode is hosted by Sean Falconer. Check the show notes for more information on Sean's work and where to the show.

Thanks, John. Glad to join you.

Yeah, absolutely. Thanks for being here.

So you've been working on data stacks for nearly 15 years.

Like, what's kept you engaged all that time? What's kept you

excited? Writing code. So my career arc transversed across going in the executive direction and then

realizing that did not spark joy for me and then coming back to writing code pretty much full-time, most recently

on our vector search products. So that's what makes me happy to get up in the morning is

looking forward to taking code. And then at the end of the day, it does something that it

couldn't do before. Yeah, I think it's good that you're able to recognize that because I think

it's like a typical path that a lot of people, especially if you, you know, you're an entrepreneur or you start a company, but like you're in technical positions.

And then if you're successful, a lot of times you end up getting promoted away from doing a lot of the technical work and end up doing a lot of, you know, more people management. And there might be technical aspects, but it's definitely a different skill set. And you have to find joy in different ways than actually,

like, you know, day-to-day building something. Yeah, I tried, and I think I might have said this on a

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