Transformation of the Week
Tyler Laughlin

Transcript

Lusk: Hey Tyler, thanks for joining me today, congrats on winning the Transformation of The Week. Tell me a little bit more about your background.

Tyler: It is a pleasure to be here. I have been working at Adobe as an information systems engineer, working in our backend systems for almost seven years now. And I have been a fanatic of seeing how we can improve the systems that most people work with in a corporate setting. So focus on developing tools for internal customers to make sure that businesses can run more efficiently, rather than just developing flashy AI for end users.

Lusk: So what first got you interested in Gen AI specifically?

Tyler: Honestly, my start of my Gen AI journey started way back as a very young eight year old. I saw Alan Tudyk as Sonny in the movie “I Robot” and I have been enraptured with the idea of AI companions, and AI help in the workforce ever since. Robots talk about dreaming and trying to help out people and putting themselves in harm’s way to protect us and our time, was very influential on a young Tyler.

Lusk: Now, you graduated from our LLM Ops course a little over a year ago, and you’ve been a peer supporter in our AI Engineering Bootcamp; have you been able to put anything that you’ve learned into practice at work or on personal projects?

Tyler: Oh, absolutely. I’ll say, while the class is largely been focused historically towards prototyping and being in the entrepreneurial space, almost everything we’ve learned in the course has been directly applicable to my work as an enterprise engineer, both from being able to demo appropriately to executives that may or may not have the detailed knowledge needed to go all the way down the tech stack.

But one still has to be able to talk to those stakeholders about what is being developed, as well as actually applying AI engineering principles to corporate tech stack, has been extremely helpful. As well my background really helps with a lot of the data plumbing and the creation of enterprise level data sets. The practices we have in AI engineering are fundamental towards building towards those enterprise applications that need constant uptime and a full tech stack awareness. So this has been wildly helpful as a jumping off point to leverage my personal skills.

Lusk: So what are some big challenges that you see Gen AI tackling, or what are some things that excite you, specifically, in Gen AI?

Tyler: Great question. So the biggest areas of improvement, and that excite me going forward, are the development of agentic teams, AI LLMs that are able to leverage tools that engineers from all different disciplines are able to contribute to and leverage, so that the engineers knowledge of a tech stack and the classic machine learning enabled tools, are able to be put in the hands of a system that can scale ten x what a normal human could output and start actually working in fully AI powered scrum teams. Having agents talk to each other allows a single human engineer to have ten times the output of a non AI empowered engineer, while still protecting our engineering autonomy to deal with the truly complex issues that need to be properly tooled to, you know, allow for tracing, integration with corporate tech stacks, to scale securely to, you know, thousands of customers. And having the ability for a single well-trained engineer to spin up an entire scrum team with around them as human in the loop or as an autonomous process, allows us to scale our engineering knowledge far beyond what could ever be done without AI assistants.

Lusk: So what words of wisdom do you have for people out there watching this right now who are considering a move into Gen AI?

Tyler: So the biggest wisdom I can give is to not be afraid of the trends that media are trying to tell us of AI is coming to take our engineering job. It’s just simply not the case any more than the the, you know, automated plow is coming to take farmer jobs. It’s not about replacing us, it’s about enhancing us.

And now more than ever as an engineer, one’s knowledge of non-AI related topics only makes them a stronger AI engineer because it allows us to scale our knowledge of our specific areas, whether that’s in dashboarding, reporting, in data architecture, or even in good application design, we give tools for the AI to use the way that we tell them to use it, so that we can scale our knowledge far beyond what we could do on our own without undermining our autonomy as engineers to build best in class systems that aren’t racist, that aren’t biased, that can scale without going rogue on us, and really leverage AI to be a partner in the overall work structure of the company, rather than some scary entity here to oppress or take our lives away from us. It is our duty as engineers to put our nose to the grind wheel and actually build the automated future we want to see, rather than let the future we fear come to pass.

Lusk: Tyler, congrats again on winning the Transformation of The Week, where can people connect with you and see the great things that you’re building, shipping, and sharing?

Tyler: First of all, thank you for Transformation of The Week, it’s an honor to be here. The best places to find me are on LinkedIn. And as well as coming to see me in the AI Engineering classes and on the AIM discord. Join our community to better yourself and better your knowledge of how to build, ship, and share.