Martin Casado

We've seen the flood start to come.

And I think you'll see the quality and reliability of Fivetran take yet another leap this year because of that.

Awesome.

No, their use cases are very typical.

They use Fivetran to replicate data from lots of different systems of record into a centralized data lake.

And they do analytics with that.

They feed that as context into their own internal AI workflows.

So they have built data foundations that look very much like...

the data foundations of many other companies.

The systems at Anthropic, one of the people who helped set them up was a consultant who had set up Fivetran and DBT and many other companies.

So their data platforms look very typical.

And I think this is a very important message.

If you are thinking about data foundations for AI, do not make the mistake of thinking you need to build some exotic new system.

as a data foundation for AI.

The right data foundation for AI is probably the one you already have.

If you have a reasonably modern data platform, something like Snowflake, Databricks, or BigQuery, or maybe even you have transitioned to an iceberg data lake with those compute systems running on top, that is a great foundation for your context for AI as well.

No one knows how powerful it will get over time.

I mean, the nice thing about that is that if it gets sufficiently powerful, all these questions become sort of moot because we'll just be living in a post-scarcity world.

But...

I think if we look at the present day, I think it is mostly true that AIs are just creating more demand for infrastructure and not commoditizing it at all.