Avoiding ‘team debt’ by building small and smart (w/ Matt Cook)

**Matt Cook** (0:00)
You are going to have problems, if you just cut a team, or if you just slice a team in half, there are going to be problems that arise from that. But I think if you hire smart people, they are now not problems to look at and be scared of.

**Yaniv Bernstein** (0:13)
If you have problems, then you get to solve them, and now you have the opportunity to solve them the right way.

**Matt Cook** (0:17)
You're going to have competitors who are way cheaper than you, way more nimble than you, perhaps have a better product than you, certainly can deliver more value for customers quicker. All of these things, like you're gonna have to adapt, you're gonna have to change, the bigger your team is, the harder that is to do.

**Yaniv Bernstein** (0:31)
If you have the same size engineering team now as you did a year ago, and you feel like you need them all, then there's probably something wrong with the team.

**Matt Cook** (0:37)
I think the best engineers are going to become incredibly valuable and very, very well paid.

**Yaniv Bernstein** (0:42)
Cutthroat capitalists are not doing this out of the goodness of their hearts. They're doing it because they see the value of doing it.
You're listening to The Startup Podcast. This is an educational episode. Hi, I'm Yaniv Bernstein.

**Matt Cook** (1:00)
And I'm Matt Cook.

**Yaniv Bernstein** (1:01)
Very excited to have friend of the pod, Matt Cook, back on today to discuss the state of engineering, teams, hiring, salaries, equity, and what the modern software factory builder is, and why they're so, so valuable to companies. Can't wait to get into it right after this break. AI means founders can build faster and attract enterprise buyers sooner. That's great news, but don't let compliance requirements like SOC 2, ISO 27001, HIPAA and other frameworks derail you. That's where Vanta comes in. Vanta makes it easy to get ready for enterprise deals in days, continuously monitors your compliance so future deals are never blocked, and is backed by support that's there where you need it every step of the way. With AI changing regulations and buyers' expectations, Vanta have the fastest, easiest way to keep up. That's why fast growing companies like Ramp and Writer get secure early with Vanta. TSP listeners can get $1,000 off at vanta.com/tsp.
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Matt, great to have you on again. It has been a few months and already so much has changed. So I'm really keen to talk to you about what you are seeing out there on the market. So Matt, I've always thought that you have this really great bird's-eye view of the engineering market that you view through the talent side, and so much is changing so quickly for engineers, engineering teams, how engineering gets done. And I feel you've always had this great ability to spot the trends and the upcoming issues and synthesize them. So you just sent me this great list of things that you're seeing and themes. And the first one of those that I thought we could jump into is team debt. What do you mean by that?

**Matt Cook** (2:42)
Team debt is obviously a spin on the idea of tech debt. I think tech debt is becoming less of a concern for companies more generally with AI and how engineering teams can attack tech debt and deal with it. The way I've heard it described is the interest rates are just very low on tech debt. And so it's much easier to take out and deal with.
Team debt, I don't know if it's a direct replacement for it, but it's basically the same idea. And I think it's becoming more of a common issue in startups now where ultimately they're faced with problems that they need to solve or they're faced with jobs that need to get done or tasks that need to get done. And they're immediately jumping to, oh, we'll hire a human to do that job or do that task, or we'll build out a team to do that job, do that task, achieve that outcome. And as the models evolve, as teams or companies get better at working with AI, as they build out their own AI infrastructure internally and try and become more AI native, they ultimately, and sometimes in the literal sense, but they ultimately make these hires or these teams redundant or semi-redundant, because the tech that comes in in three months or six months, or even the tech that's here now, that they haven't quite been able to leverage to its full potential yet, starts to almost replace or solve the problems that they're hiring the teams to solve. And I think a lot of startups are either about to be left with or are already left with teams that have been put together to solve problems that really just won't exist in the near future.