Product managers and product owners are drowning in documentation, vision statements, roadmaps, and backlogs. But what if AI could handle the heavy lifting, freeing you up to actually talk to customers?

In this episode, Dave and Peter explore how large language models are changing product management. They go beyond the obvious use cases (like generating user stories) to discuss upstream opportunities: building product strategy, validating market positioning, and testing ideas against competitors.

You'll learn:

• Why documenting your product strategy matters (and why most PMs skip it)
• How to prompt AI to be critical, not just complimentary
• The danger of accepting AI outputs without evaluation
• Temperature settings, context windows, and other practical techniques
• What to do with the time you get back (hint: talk to real customers)

Dave and Peter also share a key practice: write down what you expect before you prompt. This simple step helps you critically evaluate AI responses instead of accepting them at face value.

If you're a product manager, product owner, or anyone building digital products, this conversation will help you use AI as a tool for better thinking, not just faster output.

In this episode, Peter Maddison and Dave Sharrock welcome Justin Trombold, President and Founder of Antison Advisors, to discuss the parallels between agile transformation and generative AI adoption in organizations.

Justin shares insights from his work helping companies navigate generative AI readiness, revealing that the biggest challenges aren't technical; they're organizational. From end-user proficiency to cross-functional collaboration, the conversation explores why companies struggle to move beyond "toy apps" to create real business value with AI.

Key topics covered:
• Why organizations need an AI strategy before investing in tools
• The critical importance of end-user proficiency with LLMs
• How cross-functional collaboration enables AI success
• Why annual planning cycles may be holding your AI initiatives back
• The parallels between agile adoption and AI transformation
• Moving from efficiency gains to true value creation

Whether you're leading AI initiatives, managing agile transformations, or wondering why your organization's AI investments aren't paying off, this conversation offers practical frameworks for thinking about organizational readiness in the age of generative AI.

THREE KEY TAKEAWAYS:

1. End-user proficiency is everything. 
2. Define the sandbox before choosing the toys.
3. Innovation in planning matters as much as innovation in products. 

Contact us: [email protected]

#GenerativeAI #AgileTransformation #OrganizationalChange #AIReadiness #DigitalTransformation #LLM #CrossFunctionalTeams #Innovation

In this episode, Peter Maddison and Dave Sharrock welcome Rick Delisi, Lead Research Analyst at Glia and co-author of "The Effortless Experience" and "Digital Customer Service," to discuss how AI is transforming customer service in banking and credit unions.

Rick reveals why the future of contact centers isn't about eliminating human interaction; it's about automating the routine so humans can focus on building real relationships. Learn how banks are breaking the age-old trade-off between efficiency and customer experience, and why starting with internal-facing AI tools is the safest path to transformation.

Discover the surprising truth about which customer satisfaction metric actually predicts loyalty (hint: it's not what most companies are measuring), and why customer expectations for AI are shaped more by bad experiences with other companies than by anything your organization does.


THREE KEY TAKEAWAYS:

1. AI for Everyone, Not Just Customers: AI can transform your entire organization, from helping frontline agents with real-time guidance, to giving managers instant analysis capabilities, to enabling executives to make data-driven strategic decisions. The most successful implementations use AI across all levels: customers, agents, managers, and executives.

2. Start Internal, Then Scale Outward: Begin with internal tools that help agents, managers, and executives first. This builds confidence, allows teams to experience the technology firsthand, and creates incremental improvements that build organizational trust. By the time you roll out customer-facing AI, your entire team understands and trusts the system.

3. The best predictor of customer loyalty isn't satisfaction scores or Net Promoter Score, it's the Customer Effort Score. Ask customers, "How much effort was required for you to get what you needed?" after each interaction. Low-effort experiences drive loyalty, and this metric gives you actionable insights into where to improve your service processes.

CONTACT US:
Email: [email protected]

Definitely Maybe Agile explores the complexities of adopting new ways of working at scale, covering digital transformation, agile practices, and DevOps in enterprise environments.

#AI #CustomerService #Banking #DigitalTransformation #ContactCenter #CreditUnions #CustomerExperience #Glia #FinancialServices #AgileTransformation

Welcome to Definitely Maybe Agile! In this episode, Peter Maddison and Dave Sharrock sit down with Barbara Whittmann, founder of the Digital Wisdom Collective, to explore how real organizational change happens from the middle out.

Barbara shares her 25 years of experience fixing broken digital transformation projects and reveals why the "juicy middle" of organizations holds the key to sustainable change. We dive deep into mindset training, building internal ecosystems, and why most organizations have forgotten the purpose of half their tools and processes.

From navigating the "permafrost layer" of middle management to understanding why AI initiatives often miss the mark, this conversation offers practical insights for anyone working to transform how organizations operate.

Three Key Takeaways:

1. Meet Organizations Where They Are - Don't force rigid methodologies or terminology. Use the organization's own language and focus on solving their actual problems rather than trying to "fix" them with prescribed frameworks.
2. The Power of Cohorts - Change isn't an individual effort. Building a cohort of four people creates redundancy, moral support, and a self-reinforcing dynamic that can create ripples throughout the organization.
3. Communication is Critical - We don't invest enough in helping leaders develop communication skills. Leaders need ongoing support, coaching, and safe spaces to develop their ability to listen, speak up, and collaborate effectively.

Featured Guest: Barbara Whittmann - Founder, Digital Wisdom Collective

Contact: [email protected]

When Hanna Bauer's publishing business faced a perfect storm of budget cuts, industry disruption, and the ebook revolution, she learned that Six Sigma processes weren't enough. The real transformation required leading with heart.

In this raw conversation, Hanna shares the wake-up call that changed everything: a top employee resigning to take a pay cut elsewhere. This crisis revealed the truth about organizational change; you can have all the right processes, but without genuine human connection and psychological safety, your best people will walk.

Whether you're leading digital transformation or navigating organizational change, this episode delivers practical wisdom on building growth-oriented cultures where people actually want to stay.

This week´s Takeaways:

1. Hope Drives Change People with high hope find a way where there is no way. Leaders must tap into this to navigate uncertainty; it's not just positive thinking, it's the catalyst for transformation.

2. Psychological Safety Starts at the Top Growth-oriented cultures need leaders brave enough to say "maybe it's my team" instead of pointing fingers. Cross-functional honesty beats departmental defensiveness every time.

3. Influence > Position Leadership is influence, nothing more, nothing less. You don't need a title to create change; just the will to advocate for your team and drive positive impact.

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Hussein Hallak, serial entrepreneur and author of The Dark Art of Life Mastery, joins Peter Maddison and Dave Sharrock to talk about what really keeps entrepreneurs in the game. It's not resilience or grit, it's clarity about why you're doing this in the first place.

The conversation covers the shift from pre-COVID to post-COVID startup communities, why watching customers do their work beats asking them what they want, and the critical difference between handing off your product and handing off your purpose. Hussein also challenges the wall-poster approach to company values and explains why living your principles matters more than declaring them.

Three Key Takeaways:

• Strategy is becoming - Choose who you want to become as a founder and company, then let your thoughts, words, and actions flow from there. It's about the experience you want to have, not just the exit you want to achieve.
• Hand off the product, never the why - Founders can delegate product development once the team understands the purpose behind it. But stay close to customers. That connection informs everything and keeps you from drifting.
• Live your values, don't announce them - Stop putting principles on posters. Instead, have honest conversations with your team about what matters to them, what's missing, and how you'll work together. Build culture through behavior, not declarations.

Topics Covered:

• Why entrepreneurship is really about your relationship with uncertainty
• The founder's role: stay with the customer, hand off the product
• How 80% of features go unused (and what to do about it)
• Why watching customers work reveals more than asking questions
• Building culture through honest conversations, not corporate values posters

💬 Got feedback? Email us at [email protected]🌐 Visit definitelymaybeagile.com

🚨 Struggling to implement Agile because you can't get dedicated cross-functional teams? You're not alone.

In this episode, Dave Sharrock and Peter Maddison tackle one of the BIGGEST challenges facing late-adopter organizations: how to increase productivity and deliver value when dedicated teams just aren't in the cards.

In this episode, we explore:

• Why the "dedicated team first" approach often crashes in traditional organizations
• The hidden dysfunctions and perverse incentives that keep teams fragmented (spoiler: it's about promotions and funding)
• The famous "Sock Factory Parable" explains cross-functional alignment perfectly
• How context switching kills productivity with scarce specialists like DBAs
• Three essential steps to make real progress WITHOUT restructuring your entire organization

The Three Critical Steps:

1. Understand WHY dedicated teams work before forcing the structure
2. Get leadership aligned on real prioritization and trade-offs (not everything can be Priority 1)
3. Create genuine work transparency without status report theater

Whether you're an Agile Coach, Scrum Master, Product Manager, or Engineering Leader dealing with organizational resistance, this episode gives you practical strategies to move forward when structural change isn't an option.

Resources Mentioned:

• Peter's LinkedIn Learning Course on Value Stream Management

About Definitely Maybe Agile: Join Peter Maddison (XodiacInc) and Dave Sharrock (IncrementOne) as they discuss the complexities of adopting new ways of working at scale. Real conversations about digital transformation, agile, and DevOps challenges, no sugar-coating, just practical insights.

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Got a question or topic you'd like us to cover? Reach out to us!

In this episode, hosts Peter Maddison and Dave Sharrock sit down with Nick Cawthon to explore how generative AI is revolutionizing the relationship between UX, design, and agile development.

Key Topics:

• Embedding UX research into agile sprints, balancing short-term feedback loops with long-term strategic insights
• The "electric bicycle" analogy: How AI gives teams superpowers but can also accelerate you in the wrong direction
• Why Nick believes he'll never use Figma again, shifting from design tools to code-native prototyping
• Building functional prototypes using company design systems and generative AI tools
• The evolution of team size: From 6-8 person cross-functional teams to powerful 2-3 person teams leveraging AI
• The architect's mindset: Understanding the technical foundation before designing the interface

Three Key Takeaways:

1. What an incredible opportunity we have; it feels like the year 2000 again, with the excitement and disruption ahead
2. Small teams (2-3 people) with diverse perspectives can now move incredibly fast using modern tools
3.  Speed is powerful, but you still need feedback loops to ensure you're building the right thing and not racing in the wrong direction

Connect with us: Website: https://definitelymaybeagile.com/ LinkedIn: https://www.linkedin.com/company/definitely-maybe-agile-podcast Email: [email protected]

Customer journey maps have been the standard for years. But what if they're built for a world that no longer exists?

Dave and Peter challenge the linear, step-by-step approach to understanding customer experience. From showers on Emirates flights to adaptive payment systems, they explore why our traditional mapping tools might be keeping us from seeing breakthrough opportunities.

What We Cover:

• Why traditional journey maps focus on the "critical path" and miss everything else
• The shift from cohorts and personas to individualized experiences
• The privacy paradox of hyper-personalization
• How decreasing costs make adaptive systems possible

Key Takeaways: 

✅ Traditional customer journey mapping optimizes a narrow, linear experience when customers want many different paths 

✅ Privacy and ethics matter more as experiences become hyper-personalized 

✅ What was too costly before is now feasible, changing the game for customer experience

Perfect for product managers, CX professionals, and digital transformation leaders.

Connect: definitelymaybeagile.com | [email protected]

Can AI really shrink your development teams from two pizzas to one? Peter and Dave explore the promise and reality of smaller teams in the age of AI agents. While AI can handle documentation, test automation, and other "hygiene" tasks teams often skip, the real question isn't whether you can reduce team size, it's whether you should. They dig into when one-person teams make sense (startups and greenfield projects), when they don't (complex legacy systems), and why the biggest gains might come from augmenting existing teams rather than downsizing them. Plus: why most AI initiatives fail and how to find the real business problems worth solving.

This week´s Takeaways

1. AI as Capacity Booster, Not Team Replacer: AI agents excel at handling the "hygiene" work that teams often skip: documentation, test automation, release notes. Rather than shrinking teams, this gives existing teams ephemeral capacity to tackle work that improves long-term system quality and maintainability.
2. Context Determines Team Size: One-person teams work brilliantly for startups and greenfield projects where you can build from scratch. But complex legacy systems in large organizations still need the diverse knowledge and experience that comes with larger teams to navigate technical debt and organizational complexity.
3. Solve Real Business Problems First: The biggest AI failures happen when teams focus on cool technology instead of actual business needs. Before experimenting with smaller teams or AI agents, identify genuine business problems that need solving; that's where you'll see real returns and organizational support.