Max Junestrand

A year from now, two years from now, it's going to be a really sad conversation.

So we invest a ton of upfront manual labor, time and effort in doing the implementation and activation right.

So I do think that's necessary for enterprises where you're changing the way they work.

If you just think about a process, right?

Like let's say you're working in, if we're just staying in legal, if you're working with AI contracting,

You basically have a contract lifecycle management system.

You just send a document somewhere, generate some red lines, and then you put it back.

That's pretty easy.

You don't need a forward deployed engineering or legal engineering model for that.

You just deploy the stuff and then you're done.

But in our case, I actually like to think of it synonymous to the way that accountants had to learn Excel or architects having to learn CAD, right?

Like before you would actually go out to the site, you would draw

the building, and then you would go back to your office, you would do all the math, but now you just get a picture of the site, you throw it up in CAD, you put in the blueprints for the building that you want, and the system AI generates it, or generates it, and then you look at the math behind it, and then you bring taste and you bring design.

When architects were learning CAD, I think it was an enormous change management.

And all the old architects would go, Harry, we're going to use that computer system to do the hard work for you.

And you would go, yeah, I'm super savvy and I'm going to get to spend more time doing the design or have creative ideas about how to solve my client's architectural problems.

And I think that's kind of synonymous to what's happening today.

Some of the things that we observed were spending a lot of effort on fine tuning models.

That always seemed to me, at least back in 2023, like a waste of time because the general models were improving at such a fast rate.

It felt like we should be building boats.