Pod Insights The Agile Daily Standup - AgileDad AgileDad & AI For Product Managers, Project Managers, and Leadership About this episode AgileDad & AI For Product Managers, Project Managers, and Leadership
The real value of AI is not just that it helps us move faster. It is that it helps us slow down in the right places so we can move better in the places that matter most.
That is the shift.
AI should not just help us produce more. It should help us think more clearly before we produce anything at all.
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Transcript 0:15 Speaker 00 Everybody wants to talk about AI like it's all about speed. Faster analysis, faster content, faster decisions, faster everything. But in Agile, I think the real story might hit a little different. In this continued saga, AgileDad is going to talk to you about how AI impacts project managers, Agile project managers, how it's going to impact product managers, and how it's going to impact Agile leaders who embrace AI. The real value of AI is not just that it helps us move faster. It's that it helps us to slow down in the right places so we can move better in a place that matters the most, and that is the shift.
1:00 Speaker 00 AI should not just help us produce more. It should help us think more clearly before we produce anything at all. And that matters for Agile project managers, product managers, and Agile leaders because the quality of delivery is often determined long before the delivery actually begins. So today, I want to stop and talk to you about how AI is changing the game by improving discovery, sharpening decisions, and helping us optimize delivery in a way that creates more value and less waste. So here's the problem with speed. For a long time, a lot of teams have been rewarded for being busy. More output, more stories completed, more items in the backlog, more work progress, more movement, more churn.
1:43 Speaker 00 But movement is not the same as progress. Speed is not the same as success. If we rush into delivery before we understand the problem, we often end up building the wrong thing faster. And that's where AI starts to really matter because AI gives us a chance to pause, analyze, and sharpen our thinking before we commit to time, budget, and energy to do the wrong thing. This is especially important in agile environments where teams are often under pressure to keep moving. The danger is that we can confuse movement, churn, and activity with value. We can optimize for output and still miss the desired outcome. We achieve no impact. We can deliver more and still satisfy a lot less.
2:29 Speaker 00 That is why the role of AI becomes so quintessential to what we're doing. It gives us support in the messy, uncertain human part of the work and helps us make better choices earlier. And in agile, making decisions early is everything. Let's talk for a second about AI and discovery. Many moons ago, in 2015, we created a diagram that goes through the four phases and it talks about initiate, or ideation, discovery, delivery, and release. And I think that's incredibly important because I want to, I want to dig in a little deeper on AI and discovery. Discovery is where we learn what the problem is and is it worth solving? It's where we test our assumptions.
3:14 Speaker 00 It's where we gather context. It's where we decide whether an idea has real value or just sounded good in a meeting. And this is exactly where AI can be the most powerful.
3:25 Speaker 00 AI can help product managers synthesize input faster. It can help teams analyze patterns across customer feedback, internal data, support tickets, and market signals. It can help service themes that would take a human much longer to identify manually. But most importantly, it can help slow down discovery in a good way. And that might sound strange. Why would you want to slow down discovery even a little bit? Because if you slow down long enough to ask better questions, you reduce the chance of wasting lots of effort later. AI can help us explore options before we make the commitment. It can help us compare scenarios. It can help us challenge assumptions that we might otherwise go unnoticed.
4:06 Speaker 00 It can help us move from what do we think is happening to what evidence do we actually have that something is happening? And for me, that's a major upgrade. For product managers, that means better product decisions. For agile leaders, that means better strategic alignment. For agile project managers, that means fewer surprises down the road. Discovery should never be rushed. It should just be sharpened, and AI will and can help sharpen it. So product managers, you're probably asking a question now that sounds good, but what do we have to gain? Product managers live in a space between vision and value. They're constantly trying to understand what to build, why it matters, how to prioritize
4:49 Speaker 00 limited time and resources and come up with something that is brilliant. AI can help you in a few important ways. First, it can help identify patterns in customer behavior and feedback way more quickly. Second, it can help to compare ideas against likely impact instead of just what my gut is telling me, my gut feeling. Third, it can help frame better questions before moving into solution mode. And that last one matters a lot because one of the biggest risks in product work is solving the wrong problem very quickly. AI can help product managers slow down just enough to make sure the problem is real, the opportunity is meaningful, and the solution path is actually worth pursuing.
5:33 Speaker 00 That creates better prioritization, it creates better focus, and it creates better value delivered to the customer. At the end of the day, a product manager does not win by having more ideas. A product manager wins by making better decisions about which ideas deserve the most attention. AI can support that decision-making process if we use it well. All right, project managers, this one's for you. Let's talk about the project managers. This role often sits in the middle of complexity. Dealing with dependencies, risks, timing, coordination, communication, delivery pressure, budgetary constraints. There's a lot to manage for an agile project manager.
6:16 Speaker 00 And AI can be incredibly useful here as it is used to improve visibility and decision quality. AI can help service project risks earlier. It can help identify trends in delivery performance. It can help reveal bottlenecks that may not be obvious from a service level look at the actual work. It can help teams see where handoffs are slowing things down. It can help highlight where work is getting stuck before the delay becomes a much bigger issue. But again, the real Value is not just speed, the value is in the clarity. If AI helps agile project managers see the system more clearly, then the team can make better decisions about how to optimize their delivery. That may mean adjusting a scope, that might mean changing sequencing,
7:00 Speaker 00 that might mean resolving dependency sooner, that might mean reducing unnecessary work. All of that matters because delivery is not just about getting things done, it's about getting the right things done with less friction and more impact. AI helps bring those friction points into view earlier, and that makes delivery stronger. What about agile leaders? Agile leaders need AI for a slightly different reason. They need it because leadership decisions depend on signal. What is actually happening in the current system? Where is value being created? Where is energy being wasted? Where are the teams overloaded? Where are decisions getting stuck? Where is the customer experience improving? And where is it not improving?
7:42 Speaker 00 AI can help leaders see patterns across teams and initiatives faster than they could manually. And I want to be clear, that does not replace leadership judgment. It is designed to enhance it. It gives leaders more information so they can make more grounded decisions. That is especially important because agile leadership should not be about managing more activity. It should be about improving organizational effectiveness. AI can help leaders ask better questions about value, flow, and impact. It can help them stop rewarding motion and start rewarding meaningful progress. And that is much better leadership conversation. So, I mentioned discovery should slow down to improve delivery.
8:27 Speaker 00 And I'll go as far to say that that's the heart of this message. AI is valuable in agile, not because it makes everything faster all the time. It's valuable because it helps us slow down discovery just enough to optimize delivery. And that is the real change management shift. If discovery is weak, delivery gets messy. If discovery is shallow, the backlog fills with assumptions. But if AI helps us explore to problem space more. Early, validate ideas more intelligently and clarify the right direction earlier. Then delivery becomes smoother, more focused and more valuable. That means fewer rewrites, fewer false starts, fewer wasted cycles and more confidence in the work that gets released.
9:11 Speaker 00 So when we talk about AI and agile, we shouldn't just ask, how can it make us faster? We should ask, how can it help us discover better so that we can deliver better? That is the real question. We need to focus on a way to move from output to impact and outcome. There's another major mind shift that that needs to occur in order to be successful. We need to figure out the way to measure success and move away from how much got done and move towards measuring success by what changed because we got minimal done. That means less obsession with output, less obsession with velocity and standalone measures.
9:53 Speaker 00 Less obsession with how busy the team actually looks at their churning and more focus on value delivered. More focus on consumer impact, more focus on whether the work actually improves something real. AI is there to help support that shift by making it easier to analyze what's working, what's not, and where investment should go next. This gives teams and leaders a much better foundation for decision making. Cause the goal shouldn't be to fill a system with work. The goal should be to create outcomes that matter. That's where agile and AI really belong together, not in hype, but in results.
10:31 Speaker 00 AI is definitely changing agile work, but not in a shallow way people sometimes imagine. It's not about doing more faster. It's about thinking better before we build. It's about slowing down discovery just enough to improve delivery. It's about helping product managers prioritize smarter. It's about helping agile project managers seek risk and flow more clearly.
10:53 Speaker 00 It's about helping agile leaders make better decisions based on value and not noise. And ultimately, it's about creating better outcomes for customers and organizations.
11:14 Speaker 00 That is the future of AI in Agile. No more buzzwords, no more empty activity, better discovery, better delivery, better impact, better real work. That is the opportunity and that's where this conversation needs to go. If you are looking for a proper AI class, we have several. We have AI application in Agile, a full eight-hour class. We have AI for project managers, for Agile project managers. We have AI for product managers and for leaders. The reason we broke it up so much is because we want to make sure that each person who
11:54 Speaker 00 attends this class has an opportunity to really dig in and forget about slides, forget about that part of the instruction, but use a large language model to create and understand how they can do their job more effectively and how they can learn about focus on impact and focus on outcomes and how they can streamline their framework and their process to make them better at what they do best. That's going to do it for this episode. I hope that you enjoyed it. If you have a topic you want us to discuss, learnmoreatagiledad.com, we'd love to hear from you. And as always, we encourage you to stay healthy, stay well, and stay agile, my friends. Until next time, you take care. Bye now.
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