If AI is speeding up how fast we can ship, what’s slowing teams down now? Brian and returning guest Cort Sharp dig into the emerging friction between AI-assisted development and the still-slow art of product decision-making.

Overview

With AI accelerating software delivery, it’s no longer the developers dragging their feet. It’s the backlog that’s backing everything up. In this episode, Brian and Cort tackle the big shift: as coding becomes faster and easier, the real challenge becomes knowing what to build, why, and whether it’s worth it.

They talk about feature bloat, the myth of productivity, the “good enough” curve, and why product owners are quietly becoming the most critical role on agile teams. Plus: short sprints, fake one-day sprints, and a healthy dose of “what even is a Sprint, anyway?”

If you're feeling the tension between building faster and deciding smarter, this convo’s got your name on it.

References and resources mentioned in the show:

Cort Sharp

#104: Mastering Product Ownership with Mike Cohn

#3: What Makes a Great Product Owner? With Lance Dacy

#164: Why Innovation Efforts Fall Flat with Tendayi Viki

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This episode’s presenters are:

Brian Milner is a Certified Scrum Trainer®, Certified Scrum Professional®, Certified ScrumMaster®, and Certified Scrum Product Owner®, and host of the Agile Mentors Podcast training at Mountain Goat Software. He's passionate about making a difference in people's day-to-day work, influenced by his own experience of transitioning to Scrum and seeing improvements in work/life balance, honesty, respect, and the quality of work.

Cort Sharp is the Scrum Master of the producing team and the Agile Mentors Community Manager. In addition to his love for Agile, Cort is also a serious swimmer and has been coaching swimmers for five years.

Auto-generated Transcript:

Brian Milner (00:00 )

Welcome back Agile Mentors. We're here for another episode of the Agile Mentors Podcast. I'm with you here as always, Brian Milner. And today I have back the one and only Cort Sharp with us. Welcome back Cort.

Cort Sharp (00:11 )

Hey Brian, thanks for having me.

Brian Milner (00:13 )

Yeah. Cort and I were chatting just in between engagements and things we were talking about going on. Cort's coaching a lot recently, and I've been coaching a lot recently as well. And so we've been kind of sharing stories and talking about kind of some of the things we've been experiencing. And you came across something really interesting recently that I thought we talked about might make a good topic. help us out. What was that that you came across?

Cort Sharp (00:42 )

Yeah, so I've seen this idea pop up a few times actually on LinkedIn specifically, but I've seen it trickle out into other areas within the coaching that I've been doing recently, but also just in other pieces or parts of the internet as well. And it's this idea of like with AI being brought into organizations, brought into companies, helping out developers so much that AI has actually lowered that barrier. for the programming side of stuff, programming side of the development side of things, that the new blocker that is currently emerging, so the new piece that's been slowing everyone down now is actually the product management side of stuff itself, which I thought was just so fascinating because I've done a little programming, definitely more in the product management side of things now, but I kept seeing this pop up and I was like, man. I would love to just hear, you know, Brian's thoughts about this and the community as a whole, everyone's thoughts about this a little bit here too, but I have my own thoughts, but just quick little immediate reaction to that idea there, Brian. How does that make you feel? What do you think of that?

Brian Milner (01:51 )

Yeah, I actually have been thinking this was coming for a while. I don't have this prepared, so please don't get me wrong in this. I know I always say data didn't happen. But there are three studies that I found at one point that were trying to determine the number of features in just your average software project that were rarely or never used. And it was three separate studies spread out over years. And one of them was like 48%. That was the low one, was like 48%. Then there was a middle one that was 64. And then there was another one that was more recent that said like 80%. And I mean, think about that, know, like I, even if you take the low end, And so, you know, 48, let's just round it up to 50 just to make it easier to have the conversation. But let's just say out of those three studies, we say it's 50 % of features that people are building are things that people rarely or never use. Now I get it that there are some rarely used features that are essential, right? Like admin functions and things. You may not use those all the time or it may not be a huge swath of users. that uses that, but you have to have them. So set those aside because that's not 50 % of what's being developed, right? And I think if that's true, if we even like go on the low end of that and say that it's closer to 50%, then that's an awful lot of productivity that's being lost. Not to mention just money and energy and effort. of developers to build stuff that no one cares about. Those studies were all prior to AI. So let that sink in, right? If those are prior to AI and we were seeing at the low end, 50%, you know, across those surveys of things that no one was using. Well, that's where I've been kind of forecasting this to say, if, if AI is speeding up our process to build things. the actual development of things, then what's going to become painfully obvious very quickly is that the bottleneck isn't developers. And it, you know, my point from saying that in classes is to say it's never been right. It's not been developers that have been the bottleneck to us being more successful. That's where the focus has been. But I don't think that was correct. And I think that the correct area to put it on is the product side. And if that's true, right, I know I'm doing a lot of leaps here, but if that's true, if it is the product side, well, I think that what that really translates to is the discipline of product management, of being able to recognize what's valuable.

Cort Sharp (04:50 )

Mm-hmm.

Brian Milner (04:54 )

to your customers to deliver that, to close the loop and verify that that's actually what was needed and to measure the impact of those things, that discipline, I think, becomes just all the more essential because that stat tells me there's a lot of bad product management going on. So that's my initial thought. That's a lot of thoughts, but that's my initial thought when you said that. What about you? What do you think about that?

Cort Sharp (05:19 )

right there. I'll share my thoughts, but I do want to harp on or just go back to your first initial one of the callback to those studies there. When you first threw out those, because I've seen similar studies where it was about 50 % was kind of it. I haven't seen those studies that say like, know, what was the last one you threw out there on the high end, like 80 something percent. ⁓

Brian Milner (05:39 )

Yeah, actually I remember, so I remember two of them. The 64 % one was from a group called the Standish group. There's been some question about their methodology in that one. I haven't seen the methodology of the 80 % one, but it was a group called Pindo that did that one. And I don't remember the 48 % one. that's just off top of my head.

Cort Sharp (06:01 )

Sure. But that 80 % one though, that one sticks out to me because as you were going through it, I was like, okay, well, I have Google Docs open right here just for some show notes or something. Just make sure I ask the questions that I'm supposed to ask or I want to ask. And I thought, wow, I'm looking at the menu bar right here. I use maybe, two or three of these consistently. And there's like 15 options up here. yeah, I could absolutely see a large majority of features that a product has that go widely unused by the vast majority of its users. And I think that poses the question then is, do we wanna go down the path of having one product be really good for, or like, really good at one thing and then kind of OK at everything else. The thing that always comes to my mind in this, and I've been going down this rabbit hole of kind of digital minimali