When the cost of code approaches zero, what does engineering leadership look like?

**Ira May** (0:09)
Hello, and welcome to Leaders of Code. If you are joining us for the first time, this is a segment on the Stack Overflow Podcast where we get senior engineering leaders together, and we talk with them about the work they're doing, how they build their teams, and the biggest challenges they have in front of them right now.
My name is Ira May, I'm the B2B editor at Stack Overflow, and I'm here again with my colleague, Ben Matthews, who is engineering director at Stack Overflow. Ben, thanks for coming back on the show with us.

**Ben Matthews** (0:38)
Thanks for having me. Excited to be here.

**Ira May** (0:40)
Absolutely. Our guest today is Eric Anderson. So Eric is director of engineering at Intuit. Eric, thanks so much for joining us. How's it going?

**Eric Anderson** (0:49)
It's going great. I'm super excited to talk to you all. Thank you.

**Ira May** (0:53)
Amazing.
I'll jump right in. I know we have a lot that we've been wanting to talk about, and I wanted to start by just thinking about something we've had very much at the forefront of our minds at Stack, which is the importance of human critical thinking in relation to coding speed. When AI tools are making code generation essentially instantaneous, we need to think about human critical thinking, I think, in context and oversight in a different way. So I wanted to start by asking you, Eric, in your work with your teams, how are you thinking about balancing the speed benefits of AI tools against that need for human critical thinking?

**Eric Anderson** (1:30)
I would say that it's this incredibly interesting time in the industry right now, because never before, I've been doing this a number of decades, and I would say never before has the incremental cost of a line of code been cheaper.
It essentially is about the most inexpensive thing of anything that we do in terms of software development is actually produce code. And what that's really created is this very interesting dynamic where it used to be that coding was the thing you were always worried about from a scheduling perspective, from a risk management perspective, from a rollout perspective, from a rollback perspective. And now we've started to really look at how do we reshape how we work? What does it mean to actually build a feature?
What is a system design? What are the skills that engineers need in the organization to be successful? Because if you're a rock star programmer, that's not necessarily the thing that is going to make you a rock star software engineer in this new day and age. And so I think it's a really exciting time to be a software engineer. I think that, in many ways, a lot of folks a while ago were saying, like, will software engineering go away? It's like, I think we're making more software every day now than we ever have. I just see the need for software development, software architecture, software resiliency, engineering, all of these things becoming more and more and more. And I think to the core of your question, at the heart of all of that is a human that actually has to make high judgment decisions about the best way to put this code together and make sure it generates value for customers.

**Ben Matthews** (3:01)
I'd love that, especially the insight into a cost, the cost per line of code now has never been cheaper. I think that's the resounding thing of how mindsets are going to have to maybe change of how we look at things. I think the big question that's challenging us everywhere is, well, how do we measure effectiveness now? How do we measure how well an engineer is performing? How well are we measuring the quality of a product? We see a lot of companies bragging that we've generated X million lines of code now just through AI.
That is impressive, not to take away from that. But is that the real thing to measure? Is that how Intuit looks?

**Eric Anderson** (3:35)
We have a lot of metrics that we use here, PRs, CRs, numbers of reviews, lines of code.
All those traditional metrics, I think are still relevant and interesting. But ultimately, the metric that was and continues to be the most important one is, whatever we did in the technology, did it generate customer value and how do we measure that? I think that the speed with which we can actually put things into the production environment, explore different variations of things. We do a lot of experimentation inside of Intuit around is this version of this experience work better than that version? We don't have to choose anymore. Can we do two experiments? Can we do five experiments? Can we do nine experiments? Can we do 900 experiments? We actually have the optionality of experimentation has become much greater. I think that's really super exciting, right? Because now we're not just getting at like, okay, these are great ideas. How can we actually try them all out? How do we try them all out with velocity? How do we actually get the right metrics and instrumentation in place? It's much easier to do that now. And ultimately, what we want to do is really deliver value for customers. And I think that's still the same metric that existed five years ago, 10 years ago, today, tomorrow, five years from now. It will be, we will build all this technology to make someone's life, job, activity better, happier, easier, right, and make an improvement. And so I think it's the same thing.