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Every technical system harbors its share of quick fixes and band-aids – those temporary solutions we implement with the best intentions of returning to fix properly "someday." But what happens when that day never comes?

Peter Madison and David Sharrock dive deep into what they call "longstanding risks" – the accumulated technical debt that results from prioritizing expediency over completeness. Through a relatable example of a memory-leaking service that gets automatically restarted rather than properly fixed, they unpack the hidden costs of these decisions. The conversation reveals how seemingly minor shortcuts can gradually transform robust systems into fragile, unmaintainable messes.

The hosts share a compelling analogy about a utility company that saved money by skipping tree trimming around power lines for just one year – only to face significantly higher costs from the resulting infrastructure damage. This perfectly illustrates how short-term thinking about technical maintenance creates expensive long-term consequences. They offer practical recommendations including proper documentation of temporary fixes, avoiding team overload, and maintaining good system hygiene.

What makes this episode particularly valuable is the mindset shift it advocates: moving from attempting to prevent all possible failures to building systems that remain resilient when inevitable problems occur. As Sharrock references from safety expert Sidney Decker's work, sometimes the best approach is focusing on what makes your system work well rather than obsessively eliminating every risk. Whether you're managing complex technical systems or leading transformation efforts, these insights will help you balance pragmatic solutions with long-term system health.

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In this episode of Definitely Maybe Agile, Peter Maddison and David Sharrock explore the critical question: "How do we know when work is ready to start developing?" They discuss the challenges of translating business requirements into technical implementation, the importance of having the right people in collaborative discussions, and practical approaches to defining "ready" work. Peter shares recent experiences with organizations struggling with this exact problem, while Dave highlights how trust between business and technology teams impacts the handoff process. They explore visual collaboration techniques, the concept of "full kit," and practical ways to determine if work is truly ready to begin.

This week´s takeaways:

1. Revisit and reinforce your work definition process regularly, as changing roles and organizational shifts can erode even the most robust systems over time.
2. Use the "full kit" concept as part of your definition of ready, and be willing to say no to work that doesn't meet these criteria.
3. Work is ready to start when it's the team's top priority, has a clearly defined problem to solve, and the team can confidently estimate it within their typical delivery range.

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In this insightful conversation with Suzanne El-Moursi, co-founder and CEO of BrightHive, Peter and Dave explore how organizations are addressing the growing gap between data volume and analytical capacity. Suzanne reveals that while 90% of the world's data was created in just the last two years, only about 3% of enterprise employees are data professionals, creating a massive bottleneck where business teams must wait in line for insights from central data teams.

BrightHive's solution is an "agentic data team in a box" – seven AI agents that work in unison to handle the entire data lifecycle from ingestion to governance to analytics. Unlike typical AI solutions, these agents operate at the metadata layer to ensure quality, compliance, and meaningful insights without replacing human expertise.

The conversation covers compelling use cases across industries – from helping resource-constrained organizations extend their analytical capacity to unifying fragmented data landscapes resulting from mergers and acquisitions. Perhaps most striking is Suzanne's vision for measuring AI's impact through what she calls the "delight KPI" – are employees finding their work more fulfilling when augmented by these tools?

Key Takeaways:

• Data fragmentation persists - Organizations struggle with siloed data across systems, especially after mergers, blocking comprehensive analysis.
• AI augments human intelligence - "A doctor with AI will displace a doctor without AI" - the goal is removing grunt work so humans tackle higher-value analysis.
• Measure the "delight KPI" - Track how AI improves job satisfaction by enabling more data-informed work without technical bottlenecks.
• Cultural shift needs technical solutions AND organizational buy-in to overcome skepticism about AI in the workplace.

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In this episode of Definitely Maybe Agile, Peter Maddison and David Sharrock explore how increasing technological capabilities—particularly AI and modern development tools—are changing the landscape of organizational change management. They discuss the implications of newly created capacity, the value of team autonomy, and the importance of balancing efficiency with innovation.

This week´s takeaways:

• Creating capacity through new technologies doesn't mean downsizing teams—it means enabling organizations to address previously neglected but valuable work while maintaining knowledge pipelines.
• Team autonomy is crucial for effective change management—when teams have both direction and freedom to make decisions about their workspace, they can respond more effectively to urgent needs in the system.
• Organizations must recognize and protect "slack time" as a valuable resource rather than inefficiency—this time for maintenance, innovation, and thinking is essential for sustainable systems.

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In this episode of Definitely Maybe Agile, hosts Peter Maddison and David Sharrock tackle an often overlooked but critical topic: career progression for Scrum Masters and Product Owners. They explore how organizations initiate these crucial Agile roles but frequently fail to consider their long-term evolution within the company structure.

The discussion contrasts the divergent career trajectories of these two roles. For Product Owners, a clearer path exists from managing individual products to becoming Chief Product Owners and potentially Line of Business managers, though challenges arise when the role lacks proper autonomy or is treated as a part-time responsibility. Meanwhile, Scrum Masters face a more ambiguous journey, with traditional progression into Agile coaching roles becoming increasingly limited in many organizations despite the valuable skills they develop.

Peter and Dave highlight the critical importance of demonstrating value and making contributions visible, particularly for Scrum Masters whose impact often remains behind the scenes. They also discuss how understanding financial aspects of the business becomes increasingly crucial as professionals advance in either career path.

Key Takeaways:

• Product Owners have clearer progression paths toward leadership positions, but organizations must properly position and empower the role from the beginning to enable this growth.
• Scrum Masters develop highly valuable skills in facilitating delivery and optimizing organizational flow, but need to actively demonstrate their impact to create career advancement opportunities.
• Both roles require increasingly strategic thinking about business value and financial outcomes to progress into higher leadership positions within organizations.

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In this episode of Definitely Maybe Agile, hosts Peter Maddison and David Sharrock dive into the world of Objectives and Key Results (OKRs). They explore how this increasingly popular framework helps organizations create alignment, measure progress, and foster autonomy while moving away from traditional KPIs. From the origins at Intel in the 70s to widespread adoption by tech giants like Google, Peter and David discuss the nuances of implementing OKRs effectively and why they're particularly well-suited for organizations operating in rapidly changing environments.

This week´s takeaways:

• Unlike KPIs which measure performance, OKRs measure progress and alignment to strategy. They should never be tied to individual performance metrics as this undermines their exploratory nature.
• Successful OKR implementation requires ongoing conversations, regular reviews, and a cultural shift. Many organizations underestimate the effort needed to maintain OKRs effectively.
• Effective OKRs should be limited in number (3-5 objectives with 3-5 key results each), represent stretch goals beyond business-as-usual, and serve as a prioritization mechanism for the organization.

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When was the last time raising risk in your organization led to anything other than slowing down? Join hosts Peter Maddison and David Sharrock as they challenge conventional thinking about risk management in the age of rapid technological change. This episode reveals why traditional approaches might be putting your organization in greater danger.

Drawing from their battle-tested experience working with financial and technology organizations, Peter and David crack open the uncomfortable truth: many companies still treat risk management as a checkbox exercise rather than a competitive advantage. They reveal how the explosion of data analytics capabilities has rendered old "rule of thumb" approaches obsolete while simultaneously creating entirely new risk landscapes that most organizations are woefully unprepared to navigate.

This week's takeaways :

1. Risk management begins with identifying vulnerabilities, understanding potential impacts, and making informed decisions about how to handle them—whether through acceptance, avoidance, transfer, or reduction.
2. Effective risk management isn't just about frameworks and committees—it requires a cultural environment of psychological safety where risks can be openly discussed without fear.
3. The most effective approaches position oversight functions like architecture as service providers rather than gatekeepers, helping teams move forward safely rather than simply blocking progress.

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In this insightful episode of "Definitely Maybe Agile," hosts Peter Maddison and Dave Sharrock welcome David Hirschfeld, founder and CEO of Tekyz Inc, to discuss the complexities of effective product management. A 35-year software development veteran and former physics student from UCLA, David brings a unique perspective shaped by leadership roles at tech giants like Computer Associates, Texas Instruments, Intel, and Motorola.

The conversation explores the critical balance between product market fit and product solution fit, with David emphasizing why focusing on customer problems rather than product features leads to greater success. Whether you're a startup founder, product manager, or development team leader, this episode with the host of the Scaling Smarter Podcast provides actionable insights for creating products that truly solve customer problems and generate sustainable revenue.

This week´s takeaways:

• The most valuable customer conversations happen when you ask about their problems, not your product features.
• Successful product management requires understanding both the perceived impact of a problem and its actual cost to customers.
• Successful founders and product managers are those who love understanding customer problems and spend their time learning about customer challenges.