90: Using AI at Work to Create an AI Quality Assurance System with Hernan Lardiez

**Hernan Lardiez** (0:00)
You look at me in the eye, I said, Ernard, I'm not going to implement AI because I'm afraid of the outcome. We are in a regulated market. If something happens, we cannot control risk.

**Chris Daigle** (0:09)
So who is the person in the organization on the client side or the internal stakeholder that is most likely the person that will understand the concept, understand the requirements of it, and be able to fulfill on the client side?

**Hernan Lardiez** (0:22)
There are two audiences, the business owner and the group that develops and implements AI solutions.

**Chris Daigle** (0:31)
Any closing thoughts or considerations for everybody as they go and chew on this?

**Hernan Lardiez** (0:35)
Don't feel shy about AI. Don't feel shy about the output of AI because it's good for everyone. It helps in a lot of ways, but ensure that you have the correct control points and the correct boundaries to understand what's going on with the AI output.

**Chris Daigle** (0:52)
Hernan Lardiez is a seasoned tech leader with 25 years in global sales and operations, a COO of Ragmetrics. He helps companies reduce risk and boost trust in generative AI systems. Welcome to Using AI at Work. I'm your host, Chris Daigle. Each week we'll be learning how today's business owners, entrepreneurs, and ambitious professionals are getting more done with smart use of tomorrow's tech. Let's get started. Right now every business leader is asking the same question, what are we going to do about AI? If this is you, chiefaiofficer.com has the answer. We'll give you a simple path forward where we provide executive and team training so your people know exactly how to safely use Generative AI in their day to day. We also manage the deployment and implementation to make sure tools actually get adopted and deliver results. And we'll also guide company-wide transformation so AI becomes part of your operating system, not just another shiny object. The companies that act now will increase productivity, cut costs, and grow faster than their competitors. Those that wait will get left behind. So if you want to make AI work in your business, visit chiefaiofficer.com and see how we're helping companies of all sizes finally get results from AI. All right. Greetings, esteemed listeners. This is Chris. I'm the host of Using AI at Work, where we explore Generative AI's application and participation in the work day through a non-technical lens. Now, the topic that we'll be covering today, we could get very technical in the weeds, but I'm going to make sure that the conversation sticks to how can I, as an executive, first of understand the application of and get benefit from model evaluations, the testing of the results that we're getting from AI that we're putting into production. And our guest today is a fantastic thought leader on that topic. Ernan is a, he's been working with AI since 1991, was his first exposure as a software development engineer. Has worked with a lot of the known brands, multinational brands that you know of. But we were recently introduced through a post that he and his partner had put in Rachel Woods group called the AI Exchange. If you're not familiar with that, definitely worth checking out. And I know Rachel's a friend, but she comes from kind of a geekier background when it comes to AI.
And in all of the training that she does, she always stresses evals, evals, evals. Well, as somebody who didn't come from a technical background or a development background where that was important, that was kind of a step maybe that I skipped or didn't pay a lot of attention to until recently. Now, we find ourselves at Chief AI Officer doing a lot of work with clients now where it's not if there's a mistake, it's not internal to our company. If there's a mistake, it has impact. It has gravitas on a client company, which we definitely don't want to do. So when I had the opportunity to connect with Hernan and his business partner on this topic so that I could understand it, I was excited to share that information with you. And this interview will be a continuation of a basic conversation that Hernan and I had maybe a couple of weeks ago. So with that, Hernan, welcome to the show. And anything that I left out maybe that you want, that you think people should understand.

**Hernan Lardiez** (4:09)
No, first of all, thank you for having me, Chris. A pleasure talking to you today. You defined a little bit what I've been doing. So my first interaction with AI was in 1991 At the time, it was purely academic because there was no processing power. The main difference between now and then is the processing power that we have today. So for sure, in the middle of my career, I've been doing other things, but in the last few years came back to the AI world.