How Agile Will Finally Achieve its Promise with AI Transcript

Ross Martin:

So in the context of a project manager now having an AI project assistant, one of the other things that is going to really open up here is the ability to, as I say, get Agile right. We've found for quite a while now that the promise of agile development, I remember when I first heard about it, it's kind of like, oh, this makes so much sense, the flexibility and all the other good things that come with it, right? But in practice, I've never really seen it work in the purest sense of how it was originally defined. And we think that AI is going to open up that possibility.

Idris Manley:

Yeah, absolutely. I can't tell you the number of times that my team was asked to manage a scrum or to manage some initiative and not being able to offer a predictable sort of schedule based on the product. The executives don't like that very much. Yeah, that doesn't really work very well. And so I think very early on with the introduction of Agile, it was very clear to me that, you know, my teams needed to be able to sort of offer some hybrid approach where they could still sort of plan at a high level conceptually that sort of the longer arc, if you will, in a waterfall manner, while still allowing the teams to function on a day-to-day, iterative basis in an agile manner.

Ross Martin:

Yeah, absolutely. And that's the same thing that happened in my companies as well. We converted the engineering and product teams over to Scrum. And I remember that there was a lot of resistance on that from even some of the engineering folks. You'd think that there would be more embracing of that, but there was some serious skepticism at the time. that this Silicon Valley big tech concept was coming into the next level of companies. And so there's this sense of, okay, now we're agile, but the reality is we also, the same thing within the PMO, and we figured out that outside of the product and engineering teams, everyone else really expected waterfall.

Idris Manley:

You know, I mean, because I mean, it's PMO, we're in the middle, right? So we are in the middle. So you have you have engineers on one side that really have begun to love agility and the freedom and the flexibility gives them because it allows them to be more adaptive to a fast changing, you know, environment and competitive two or three week sprint. they love those. They love being able to not think further ahead than that, which I completely understand. But then on the other hand, as project managers, we have business leaders, we have executive sponsors, you have C-level leaders that really are expecting a certain amount of output, velocity output. They're expecting a certain amount of deliverables to actually be released, product features, et cetera, to be released. And we're having to sort of answer along with maybe the engineering leadership as well as to why teams aren't delivering enough or when they can expect certain things to happen. So sales and marketing can have clarity on when they can set customer expectations on some feature set, et cetera. And so, you know, again, we're in the middle of these two audiences that have very different interests. Nobody was happy. Nobody was happy. And we're here, we're having to sort of bridge the gap here. We're trying to negotiate with engineering leadership to at least give us enough clarity and commit.

Ross Martin:

How many sprints ahead do you think this might be?

Idris Manley:

And can you commit to it? And can you at least... well, you know, confidence levels and et cetera. So I think we were really on the front line of having to force the conversation, or at least to begin thinking about these hybrid sort of designs that have become pretty ubiquitous now, I believe, in a lot of companies in PMO, in having to embrace a hybrid approach to being able to move forward and deliver.

Ross Martin:

Right. But the hard part with the hybrid approach is, as the project manager, again, you're trying to juggle both sides, the structured, predictable side and the flexible, adaptive side. And the way that you take all this information together is, in my case, our team, we were using things like Excel and stuff to try and...

Idris Manley:

Try and pull and then and then you're saying a date to someone and you're like, please please be right It's an interesting point So if you look at all of the you know leading agile tools that are out there today and like in my day You know rally and version one where I think some of the leaders in the industry early on but now you know you have you have you know, you have like Asana, and you have Monday, and you have the JIRA suite. So you have a lot of options. But if you look at that, these tools are really still set up as squarely Agile tools. So when you're scoring, and your story points, and how you're measuring commitments, it's still within the Agile framework. And so this notion of hybrid sort of waterfall-esque ways of being able to track and monitor still really haven't been built fully into a lot of these tools. And so as project managers, you're still left to having your own sort of hybrid sort of hodgepodge way of taking the information that you're getting from your Agile tools, translating it into a Gantt chart of some sort that is not Agile.

Ross Martin:

show that to engineering because they don't want to see that.

Idris Manley:

That's your tool and your data and you're then you're trying to translate that to executives and sponsors and other things that they can understand. So you're really sort of creating this mismatch of using a mismatch of tools and data to try and ultimately to appease all of these different audiences and I think that That leads us to AI and the opportunity that AI actually provides.

Ross Martin:

I think so, yeah. I don't know about you, Idris, but you create something like that Gantt chart and then an executive sees it. It's done. Like now that's the commitment, right? They saw it. It is now the date. And now suddenly you find this date is like everywhere. No, you show it, you own it.

Idris Manley:

Exactly.

Ross Martin:

And what sucks is that you as the PMO leader or the project manager are now Just, like I said, sort of hoping that it all works out.

Idris Manley:

The worst thing is to be asked to share a deck that contains timelines that are still in draft form via email. I go, you know, Idris, can you send me that that that deck that you showed over screen, you know, screen or zoom or and it gets forwarded. And then, you know, yeah, then it gets forwarded. It becomes like, you know, it's too late then. Yeah.

Ross Martin:

But yeah, it's like, oh, great. It's coming out in November. Yeah.

Idris Manley:

Idris is committed. He showed it in a slide.

Ross Martin:

Oh, my. Yeah. So so like you're you're teeing up, I think, is is the interesting thing is We believe that with AI, there's an opportunity here now to finally get hybrid right. The true promise of Agile with the need for a certain amount of predictability and structure for other parts of the organization who don't operate in an Agile manner.

Idris Manley:

Yeah, I think what AI will be able to do sooner than later is to consume all of this different data related to agile and really structure it in a way that it can also understand the constraints or the needs of the executives and really begin to frame naturally how to organize all of these sort of data sources and to ultimately to provide an optimized understanding of what's possible, what's likely, without you as a project manager having to really think a lot about that. And so it will naturally be able to give you data that is organized in a Gantt chart or just gives you new data that's structured in a way that can give you more predictability without necessarily having to crunch the numbers yourself and drop it into an Excel sheet and do all of these sort of creative ways to be able to try and identify and anticipate what's possible. And then in addition to that is going to be able to assess the risk as well. and to be able to offer you greater visibility more proactively with your Scrum teams, your Agile teams, in terms of risks that are possible in ways that would be much more difficult for you to do if you were just trying to read some of these reports and try and assess what the likely outcome is or how teams are actually tracking.

Ross Martin:

Yeah, absolutely. And what AI is incredibly good at, as we all know, is data. And you have lots of it. And there's a lot of data coming out. And even in tools like, say, Asana or Monday, you could take your Agile data and you could try and figure out what your team's velocity of, or maybe if you're doing safe, the multiple Scrum teams or how their velocities are going. But at a certain point, it gets a bit overwhelming, right? Because you're trying to figure out, you know, you're looking at the backlog, you're trying to figure out the velocities, you're trying to figure out how they interact with each other, the various Agile teams, and where that all leads towards the delivery of a significant feature or release of a product. And then there's the ones that aren't even in that tool, like I said, like product marketing, or sales enablement, or any of those other things, customer interactions, all those types of stuff, gets to a point where it's just overwhelming. And that's what AI is gonna really make a difference at here, is that AI will be able to consume all of these things, the people who are working in Agile, the people who aren't working in Agile, the different functions, the constraints, and really be able to bring it together so that, essentially, that the different parts of the organization get to work in their most efficient manner, and it's okay that they're all different, or that they could be different, and it still can work together.

Idris Manley:

AI becomes the glue that allows all of these teams to operate with the project methodology of their choice, and it really sort of links them all together in a way that you as a project manager can maintain visibility and insight into all of the things that matter most. to performing your job, which is, can we deliver as committed or as expected? What are the risks that need to be proactively dealt with? And what is the how? And how are we performing against baselines? And how can we perform even more efficiently and more effectively, increase velocity, and all of those things that's necessary?

Ross Martin:

Absolutely. And to make something that was actually impossible to get your arms around relatively easy to get your arms around, frees you up to focus again on how the team's operating, why are we delivering this, and how are we doing on our metrics and KPIs towards the business outcome that this entire project is here for in the first place. And figuring out how to make tweaks and changes and adjustments along the way, driving through the risks, that's what your job's gonna be.