BONUS: The Hidden Dangers of AI at Work With Ari-Pekka Skarp

AI is usually sold as a productivity tool, but Ari-Pekka Skarp argues that the real story is what it does to the conversations, skills, and purpose that hold teams together. In this BONUS episode, Ari-Pekka explores why organizations are rushing to use AI “as efficiently as possible” without defining what efficiency means, and what that rush is REALLY costing us.

Organizations Are Conversations

“Organizations are actually conversations, conversational patterns between people.”

Ari-Pekka’s path from software engineering in 1999 to psychology, psychotherapy, and change leadership was driven by one thread: how the mind works, both individually and socially. Meeting Ralph Stacey, Esko Kilpi, and Douglas Griffin at Nokia changed how he saw organizations. Instead of a machine made of parts, an organization is a living pattern of conversations — people responding to each other’s gestures, again and again. George Mead added the idea that the human mind itself is not individual but relational. This matters for AI because a large language model is a new kind of player in those conversations, not just a tool that moves data between them.

The Efficiency Fetish

“It’s like how much people are pressing the acceleration pedal in the car. It doesn’t tell anything where the car is going.” Continue reading BONUS: The Hidden Dangers of AI at Work With Ari-Pekka Skarp

Deborah Colombari: Coordinating Global Agile Teams Around One MVP

“The scope is clear. How we are going to deliver it is not clear.” – Deborah Colombari

Deborah brings a live challenge from a new global project. Her team carries the deadline, but three other teams must contribute, and those teams do not share the same priority or urgency. The question becomes: how do you align teams when only one of them feels the pressure? Deborah has already tried management alignment meetings, but they have not worked as well as needed. Her next experiment is a one-week workshop inspired by Lean Inception, where managers and teams can write down what is needed, when it is needed, and what each team can realistically contribute.

Vasco and Deborah explore three practical moves: define the MVP as a real vertical slice, ask whether a person from each dependent team can join for a Sprint or a few days per week, and reduce dependencies by moving ownership closer to the team that holds the deadline. The coaching conversation ends with a useful image: even vertical slices contain thinner vertical slices. When the deadline is fixed, scope must become flexible.

In this episode, we refer to Lean Inception and Minimum Viable Product.

Self-reflection Question: When your team depends on others, are you managing the dependency or trying to reduce it?

Transform Your Agile Teams with Hard-Earned Lessons from Super-Experienced Scrum Masters

Do you wish you had decades of experience? Learn from the Best Scrum Masters In The World, Today! The Tips from the Trenches – Scrum Master edition audiobook includes hours of audio interviews with SM’s that have decades of experience: from Mike Cohn to Linda Rising, Christopher Avery, and many more. Super-experienced Scrum Masters share their hard-earned lessons with you. Learn those today, make your teams awesome!

About Deborah Colombari

Deborah ColombariDeborah is an Enterprise Agile Coach with a decade of experience championing Agile principles across organizations. Passionate about collaboration and continuous improvement, Deborah genuinely loves what she does—empowering others to work smarter, deliver value, and thrive in dynamic environments.

You can link with Deborah Colombari on LinkedIn.

Deborah Colombari: When Agile Principles Became a Fight With the System

“I was trying to go against the system, but you cannot go against the system.” – Deborah Colombari

Deborah Colombari’s Scrum Master journey started with a sense that Agile gave her permission to work differently. After early project management work, a year in Canada exposed her to Agile, and the Scrum Master role soon “felt like a glove.” But her failure story starts when a supportive leader left and a more command-driven manager arrived. Deborah pushed back hard, trying to protect the Agile practices she believed were right: dailies, burn-down and burn-up charts, transparency, and team focus.

The problem was that she was fighting the manager instead of first understanding the system around him. That conflict spilled into the team and damaged morale. Looking back, Deborah says she would now sit down with the manager first, understand the goals and pressures behind the change, and look for compromise before escalating into resistance. Her key learning was pragmatic: Scrum Masters need principles, but they also need diplomacy. The work is not only helping the team inside the Agile bubble, but also translating between that bubble and the wider organization.

In this episode, we refer to ITIL, the Dunning-Kruger effect, and Thinking in Systems by Donella Meadows.

Self-reflection Question: Where are you fighting the system before you have understood the pressure it is trying to respond to?

Transform Your Agile Teams with Hard-Earned Lessons from Super-Experienced Scrum Masters

Do you wish you had decades of experience? Learn from the Best Scrum Masters In The World, Today! The Tips from the Trenches – Scrum Master edition audiobook includes hours of audio interviews with SM’s that have decades of experience: from Mike Cohn to Linda Rising, Christopher Avery, and many more. Super-experienced Scrum Masters share their hard-earned lessons with you. Learn those today, make your teams awesome!

About Deborah Colombari

Deborah ColombariDeborah is an Enterprise Agile Coach with a decade of experience championing Agile principles across organizations. Passionate about collaboration and continuous improvement, Deborah genuinely loves what she does—empowering others to work smarter, deliver value, and thrive in dynamic environments.

You can link with Deborah Colombari on LinkedIn.

Sheik Meeajaun: Scrum Masters Must Learn by Experimenting When AI Joins the Agile Team

“Never be afraid to admit you don’t know something.” – Sheik Meeajaun

Sheik brings a current challenge that goes beyond one team: the gap between Scrum theory and real work when the context changes faster than the playbook. His example is AI. Scrum Masters are now asked to help teams where AI agents contribute to delivery, but no certification course can fully prepare us for that. Sheik’s starting point is humility: say “I don’t know,” learn the domain, run small experiments, and reflect quickly.

In one team, two human developers worked alongside several AI agents. They could not run a normal standup with Claude, so the team created a status report and reviewed it with the human team members. Sheik framed the agents as junior developers: useful, fast, and still requiring clear instructions, review, and guardrails. That framing helped experienced developers see AI collaboration as coaching and oversight, not as magic productivity. The key lesson is practical empiricism: try, inspect, adapt, and keep learning as the work changes.

In this episode, we refer to Scrumling’s AI Product Owner course and the need to adapt Scrum practice to AI-enabled work.

Self-reflection Question: What new reality is your team facing where the honest Scrum Master answer should start with “I don’t know yet”?

Transform Your Agile Teams with Hard-Earned Lessons from Super-Experienced Scrum Masters

Do you wish you had decades of experience? Learn from the Best Scrum Masters In The World, Today! The Tips from the Trenches – Scrum Master edition audiobook includes hours of audio interviews with SM’s that have decades of experience: from Mike Cohn to Linda Rising, Christopher Avery, and many more. Super-experienced Scrum Masters share their hard-earned lessons with you. Learn those today, make your teams awesome!

About Sheik Meeajaun

Sheik MeeajaunSheik is a seasoned product and Agile leader with over 20 years of experience scaling innovative, customer-centric digital solutions. A certified Scrum and Agile expert, he bridges strategy and execution, driving high-performance teams at enterprises like Rabobank and citizenM. As a hands-on builder, Sheik created Scrumling—a free, interactive Agile training platform—and ScrumJobs.net, a niche job board for Agile professionals. His passion lies in transforming theory into impactful, real-world results.

You can link with Sheik Meeajaun on LinkedIn.

You can also explore Scrumling, ScrumJobs.net, and Simatech.

BONUS: How Scrum Masters Can Use AI Without Becoming the Human API, With Fred Deichler

AI is already changing the practical, everyday work of Scrum Masters and Agile Coaches. In this BONUS episode, Vasco talks with Fred Deichler about moving from curiosity to real AI-supported workflows: finding team signals faster, preparing better conversations, keeping documentation in sync, and staying focused on outcomes instead of just producing more output.

From Automation to an AI Sparring Partner

“I have this partner I can work with to help me ideate things.”

Fred’s journey into AI started before the current AI wave, with automation in Jira and the practical need to surface bottlenecks without manually watching every board. The turning point came when ChatGPT stopped feeling like a search box and started acting like a thinking partner.

Faced with a team being pushed toward multiple sprint goals, Fred dumped the context into AI and asked for three to five options instead of one “right answer.” That shift helped him move from a deterministic mindset into a problem-solving mindset, using AI to explore options, challenge his own assumptions, and prepare a better conversation with the team.

The Monday Morning AI Context Builder

“It instantly sets that context for me. It sets that tone for the whole week.”

Fred describes his weekly workflow as a very practical use of AI: on Monday morning, he opens Cursor and works with his own AI harness, Atlas. Atlas is built from markdown files containing persona, skills, history, meeting transcripts, notes, and Jira data. When Fred says “good morning,” the system pulls the most relevant signals forward: aging work items, backlog health, sprint goals, and where the next team conversation should focus. Instead of starting the week by hunting for data, Fred starts with questions he can bring into the first stand-up: what is stuck, what needs refinement, and what risk is already visible?

Making Flow Metrics Visible Inside Jira

“If you’re on a page, what do you hope you could learn without asking?”

Beyond using AI as a thinking partner, Fred used AI to build a Chrome extension that surfaces useful Jira insights directly where the team already works. On the active sprint board, it shows work in progress, aging items, sprint goals, and sprint changes. In the backlog, it exposes backlog health and epic health. On the sprint report page, it adds cycle time per item so the retrospective can move from generic discussion to concrete learning. The point is not to shame the team with metrics. The point is to make the right conversation easier to start: what caused this item to take seven days, what blocked it, and what do we want to learn from that?

AI as Extra Eyes and Ears for Team Conversations

“It helps make sure that we don’t lose sight of these things I can bring back to the team.”

Fred also uses AI agents to review meeting transcripts and look for patterns that are easy to miss in the flow of daily work. The system can notice hesitation, unresolved topics, or a requirement problem that was mentioned once and never followed up. For retrospectives, Fred’s Atlas setup can review sprint transcripts around day nine of the sprint and suggest themes for the next retro. It can even generate prompts for a visual retrospective board in Copilot or a Miro board from a prompt. This helps Fred avoid relying only on recency bias and creates a better starting point for the conversation the team actually needs.

Keep the Human in the Loop, Especially for Outcomes

“It’s not about building a faster hammer. It’s about identifying the outcome you’re going for.”

A major warning in the episode is that AI can make Scrum Masters faster at producing more of the same: more notes, more summaries, more documents, more reports. Fred argues that the useful question is not “can we automate this exact process?” but “what outcome are we trying to achieve?” In a Jira-to-Azure DevOps migration, for example, the goal was not to reproduce the current time-tracking process perfectly. The goal was to provide the information accounting needed. That outcome focus keeps the human accountable for direction, judgment, and value, while AI helps explore better ways to get there.

The SPOT Framework for Finding AI Opportunities

“If it meets three or four of those, this is a great opportunity for an automation to free me up to do that more human-centric work.”

Fred uses a simple filter, the SPOT framework, to decide what AI should help with and what should remain human-led. A task is a good candidate when it is simple, predictable, observable, and tedious. Simple means it requires low human judgment and could be explained on an index card. Predictable means it happens repeatedly, either on a schedule or triggered by an event. Observable means the needed data is available to the agent and not locked away in someone’s head or behind policy. Tedious means it consumes energy without adding much human value. When a task matches most of those criteria, Fred looks for ways AI can handle the toil while he stays focused on facilitation, coaching, and decision-making.

A Small Experiment Scrum Masters Can Try Tomorrow

“If a Scrum Master finds himself operating as, like, I’m moving data from point A to point B, that is a great opportunity to say, how might we do this?”

Fred’s concrete advice is to start by noticing where you have become the “human API”: moving data between tools, updating spreadsheets, copying information into reports, or keeping documents manually aligned with reality. Write down one tedious workflow and ask your approved work AI, “How might we automatically populate this, while keeping me in the loop?” Vasco adds a useful ideation tip: if the first five ideas are not good enough, ask for five more without repetition, then five more again. The goal is not to hand over accountability. The goal is to discover what might be possible and choose one safe, small experiment.

Resources for Scrum Masters Exploring AI

“It’s all about building up your own idea of what’s possible to start those how-might-we conversations.”

For listeners who want to keep learning, Fred recommends The AI Daily Brief as a way to stay current with what is happening in AI, and Jack Roberts’ YouTube channel for practical ideas around personal AI and agent-based workflows.

About Fred Deichler

Fred Deichler

For over two decades, Fred has been a technology leader, who has been intuitively following the Scrum values and Agile principles even before discovering them. He has successfully led multiple teams on their Agile journeys, emphasizing the importance of a harmonious balance between people, processes, and tools, and continuously striving for improvement. For Fred, personal growth is as crucial as professional development.

You can link with Fred Deichler on LinkedIn and connect with Fred Deichler at Triforce Agility.

 

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