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Hello everyone. Welcome to the 5 Minutes Podcast. This week I decided to talk about the use of AI in Agile, and why I want to talk about that because most of the time when we see papers and articles, including the article I wrote with Antonio about the use of AI, we use a more, I would say generic delivery approach. So in a set of statements, that are, I would say, most of the time for most of the delivery approaches. But right now, I want to talk specifically about Agile, and I want to share with you three ideas that you can use and adopt AI to improve your Agile, and I want to start by saying one thing. Most of the time, when people are using Agile, they truly believe, okay, we are already maximizing our capability of delivery because we are doing iterative planning, we are releasing minimal viable products, and we are accelerating benefits. And I agree with all of that. But what I want to say is that if you add on top of this the capabilities, the incredible capabilities of AI, then you can bring to a whole new level of performance for your Agile approach. So let me share with you the three topics I would suggest you think about on Agile and AI. The first one is the focus on iterative delivery. The first thing we need to understand is Agile development relies on iterative delivery. It's not incremental like I would say traditional project management, but what do you do? You develop a release, then you improve; then you release again, then you improve.
And each sprint is built on the previous one. And what is the use of AI? Ai can help the teams to plan and prioritize sprints based on historical data, and they can predict delivery dates with much greater accuracy. They can help you to plan your sprint and to understand is the sprint capable of delivering what I'm planning to deliver? Should I reduce the size of this sprint in terms of work, or should I increase? The second one is adaptability because this is one pillar of Agile development. Agile teams are expected to be adaptable and respond to change quickly. This is the reason why we use iterative development, and I can help this by providing insights into project risks, identifying potential roadblocks, optimize resource allocation. Just to remember, in 2018, I released the first version of the PMO tool, and that chatbot was, I would say, the first essay far before GTP. And the key aspect of that tool was resource allocation and optimization. Instead of using John, Mike, or Anna to do the work what you did, you just use generic resources, and they do all the capacity planning, and most of the time, they will say, on this sprint with this team, it's just impossible to do this work. You have two options. You increase your team or you reduce the amount of work for the next sprint.
And this is a perfect example of the use of AI. And if you use it more and more, you will have more and more accuracy, and it will provide you with recommendations to adapt to changing circumstances. For example, if you lose a resource, it can quickly reshuffle all the work. For example, there is a tool called Tadpole that does that for you. For example, if automatically you were unable to do one task, it will rescale all your sprints on that week. Exactly. To make sure that you focus on high-priority tasks. The third one is continuous improvement, Agile development, which emphasis on continuous improvement all the time. We want to improve, and this is the reason of the concept of Agile. So teams constantly seek for ways of improving the process and deliver the best possible quality. For example, if it's a new software or if it's a new tool and I can help teams to identify areas of improvement is like the A, B, C cost curve. It's something like what is the key improvements I need to do that will add the highest benefit for my product in the next sprint. And also I will help to analyze the effectiveness of this changes. For example, let's suppose you decide to make a change in the next sprint based on the retrospective you had on the previous one. So I will help you to understand will this be really effective or not, or should I make a different approach? And also it identifies patterns in code quality.
It will help you to predict defects and provide recommendations. Asians on that. And one example I love to use, of course, I'm not a software developer, but if you are developing software, there is a tool based on AI called Testify that does exactly that. That helps you to test at lightning speed with basically pretty much no human interaction to identify mistakes in the code quality of the code, identify problems, do regression tests, and provide real-time feedback on your code. So imagine this instead of you having 20 people to test something. For example, if you are a Spotify before you deliver, you can use AI to do basically an unlimited non-human test that is extremely cheap and extremely effective. So these are, for me, these three use that it will really leverage your Agile process and your agile development to a whole new level. And honestly, I'm already using this a lot. I'm already using a scalpel. I use Testify despite not being a software developer just to test it because these tools bring your productivity to a whole new level. So just to wrap up, focus on iterative delivery, adaptability, and continuous improvement in Agile, combined with the power of AI, it will be not an evolution but a revolution in the use of AI in Agile. I hope you enjoyed this podcast, and see you next week with another 5 Minutes Podcast.
