Snowflake Inc.

And this is a really important trend because the companies that have... really advantaged positions in this space are really starting to see their share prices soar.

So Snowflake is a recommendation that we've had in the AI Investor Podcast.

They recently reported earnings.

I believe that they were up almost 25% the next day.

So again, the leading companies in this space have seen excellent returns recently.

And this allows people to diversify from, if you're looking at AI, just hardware companies to actually software companies that are growing as well.

Snowflake's a recommendation we've had that's done exceptional.

Cloudflare's another company we recommend that continues to see basically an increasing future of how they can be a toll booth for the agentic era.

Yeah, yeah, yeah, definitely.

But there's also security risk, like, you know, that there is I've joked about the AI plumbing thing in the past, like, I would say that, you know, SQL has come like Snowflake has come a long way.

And we used to do all of this stuff where we would be extracting data from a Snowflake database, we'd be pulling it out, we'd be transforming it, and then we'd be shoving it back in.

Oh my gosh, what a process.

Well, it's a huge process and it's also fraught.

Every time you're moving data around in that respect, you could break stuff.

And the realization that prompting is built right into SQL now.

I mean, we don't have a lot of SQL dorks who are listening to this show, I don't think, but you could just basically inject a prompt right into Snowflake and transform data that way.

the more important thing is that the question they want to ask is that when will our data be ready for that and so on right it's not it's not so much on when the data will be ready i think the more important question that we need to answer is that how do we build a workflow that is able to operate on top of this imperfect and distributed data while we continue to maintain the governance and visibility when we use the ai i think that that's that's a key thing This is especially important when the enterprises are moving from an individual AI assistant towards a more autonomous cross-department and cross-function multi-step workflow where data, the underlying data, how is it being accessed and how it connects to existing systems and processes.

And the main thing is also, we also know that for average enterprises, it runs about 367 applications across the employee experience, right? And the main thing is that it's not duplicating the data, right? I think it's basically capabilities to orchestrate and being able to co-relate data across the enterprises, whether it's via API, agent-to-agent, MCP or zero copy to even technology like Databricks and Snowflake and so on.

So I think that's extremely important.

Just to give an example, we have a case study at this Griffith University in Australia.

Josh Brown, what do you have for us?

Snowflake rally is not over.

Green stock and a red tech tape.

Okay.

What else do you have for us today?

Wanna take a look at Snowflake, Hinge, and Taiwan Semiconductor.

Okay, we'll check out those stocks.

But first, a closer look at those major indexes.

And then there's always this alternative, like, well, what if we just did a simple thing? You know, if we could just make it not so complicated, would it still be work? And if it did, how amazing would that be? So when you say cost, are we talking, like, operational costs, licensing costs? Do I need a large cluster of machines so there's always a quorum to vote on different things for durability? What do you mean by costs?

I mean, cost is actually, let's say, the service cost that, for example, platforms like Databricks or Snowflake charge you to use infrastructure that they run, right? Because obviously Snowflake and Databricks, they run on AWS or Google Cloud, you can even choose your deployment type.

But obviously, because they provide a service, but they still have to pay for the infrastructure, the service is basically something on top of that infrastructure.

And they decide how much it is, basically.

And lo and behold, we know that Microsoft has already advertised that they are doing agentic or AI generated patching.

And the very same thing happened with Snowflake just recently.

It was reported by the Wiz research team where they found a vulnerability in Snowflake that had been generated with GitHub Copilot.

to actually auto-fix the vulnerability, and then that led to a new vulnerability.

So it's more common, I think, today than ever before that people are now turning to AI, and perhaps they haven't seen our research yet, or they want to believe, as they say.

I mean, I'm definitely seeing some successes and definitely hearing some horror stories from people who are doing exactly what you described.

Like the CEO says, oh, I'll just hook up Cloud Code to Snowflake.

That's easy.

And then the data team has to go back and kind of correct the results he's been getting because, you know, that's just kind of how it goes.