Enterprise platforms can cost less than rebuilding with AI

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

1. 19:21

   well for one i agree with you that a lot of people are frightened of change to begin with the era of ai has disrupted every industry every business every person and everybody needs to really rethink everything and it seems to be coming all at once so my approach to that was to lean into it and one of the ways we did that here is put together a white paper on the blueprint for agentic business which I'll happily give you a copy of today and train them on, you know, what is the difference between a language and model and an enterprise platform? Not saying better or worse, they're both important. They're both extremely important. And one actually makes the other stronger. But if you don't know where one begins and one ends, it really is kind of confusing for people. And that was a big unlock.

2. 20:24

   I literally had CEOs tell me that that white paper actually let them see the world totally different, that there were many things in it that they didn't know or didn't realize. One such example would be, you know, let's take an example that's real. Every company today has a compensation issue. So, OK, we have a compensation issue on aisle seven in XYZ Corporation. The language model will do a great job of telling you, in a compensation situation like this, please consider step one, two, and three.

3. 21:04

   Excellent. Does it in milliseconds. Fantastic. Only problem is, it doesn't actually close the case. So now in aisle seven, we got to have the data, the context, and we'll have to go in and out of several different iterations of departments because let's assume it's a salesperson in aisle seven. And oh, by the way, that's connected to the HR department. And because it might be a problem, probably finance is involved in it or legal or compliance or risk.

4. 21:39

   And now we have data and a workflow that's gone through many different iterations, databases, and functions to come back and remediate the issue and close the case. That's what a workflow platform like ServiceNow does. And it was also important to have AI think, but workflow acts. That's an unlock for a lot of people. Another case example would be, hey, you know, I'm a bank. I've got 15,000 of my own engineers. My CEO is under pressure from the board to come up with AI use cases. The board meeting is coming up in 60 days. And I got to look like I got all my story straight on what we're doing to infuse AI. You agree that that's a common thing, right?

5. 22:31

   Very common. Yes. Very common thing. OK, so one thing would be AI and some of the AI code out there is fantastic and it can write new code very beautifully and set up the engineer for success and get things done at a speed never before done in the world. It's also true that that net new code comes at a cost because the cost to replace an enterprise platform in this SaaS-pocalypse that people talk about is an extraordinary expense to try to match what some of these really important enterprise platforms do.

6. 23:15

   because you'd have to rebuild it. You're getting a model. I'm going to write code now. So I'm rebuilding your model. Let's take that cost. And then let's take the cost associated with the human capital doing that instead of something else because the platform was doing the work for you. And then let's add up the cost of the GPU factory, the business model associated with the language model company, and the tokens that will materially affect their business model we've actually done the math on this and so for a simple application on our platform it would be 10 times greater in cost to try to replicate it with a language model. Now, the other thing about that is, if I give you the language model and it makes a mistake, you call me up and you say, hey, Bill, the language model made a mistake. And I say to

7. 24:11

   you, the language model works. And you say, yeah, it works, but it made a mistake. Well, it's probably right, but it's not deterministic. And incidentally, it doesn't have the context of all the data that has materialized in the company in our relationship for a couple of decades now and so what we're learning too is people that run businesses understand that people make mistakes they never will forgive software for making a mistake so we're kind of in a situation where at a very small fraction of an IT budget, a premier platform, is a bargain. And to combine that with AI and the things that AI can do, you get the best of both worlds. You get more innovation, better integration, and a better outcome. Try to build it yourself at a 10x higher price, and then you have a problem.

8. 25:10

   And I just tell you that the model works, because I just give you the model. You don't have someone to call to fix things.