Podcast Summary

Scrum Master Toolbox Podcast

Episode: How AI Is Changing the Way Agile Teams Deliver Value
Host: Vasco Duarte
Guest: Prabhleen Kaur
Date: February 11, 2026

Episode Overview

In this episode, host Vasco Duarte invites Prabhleen Kaur, Agile Coach and Scrum Master, to discuss a pressing and timely challenge: how AI is reshaping the way Agile teams deliver value. The conversation focuses particularly on AI’s impact at the team level — from the uncertainty and adaptation phases to practical, emerging uses and the essential cautions for integrating AI smoothly into everyday team practices.

Key Discussion Points & Insights

1. Framing the Challenge: AI as Disruption and Opportunity

• [01:50] Prabhleen introduces AI as both a challenge and an opportunity, noting growing expectations and the paradox of delivering faster than consumers can keep up.
  • Quote: “We are delivering faster than the consumer can also consume. We have so many tools… the expectations are also increasing…” [01:55]
• Emphasizes that AI’s influence extends beyond tech — every team across domains now uses AI in some way.

2. Focus Area: AI’s Impact on Teams

• [03:18] Prabhleen chooses to explore how AI affects team dynamics, daily work, and morale, rather than only the Scrum Master role.
  • Quote: “The important part is to understand how the team is impacted because it is going to change all the conversations we’ll have.” [03:22]

3. Evolving Team Reactions to AI

• Teams’ journey described as moving from uncertainty to experimentation, growing into confidence and integration.
  • Quote: “It started with being uncertain about what's happening… and then steadily building confidence… to a point that we are trying to utilize it to make our lives easy.” [03:53]

4. Practical Examples of AI in Agile Teams

A. For Developers

• AI is used for code writing and cleaning, especially for smaller code snippets.
• Significant improvement in onboarding new team members: AI assists in understanding legacy code.
  • Quote: “They have started to utilize AI to help them... write the code... or it also helps them understand the code which is already written.” [05:34]

B. For QA/Testers

• Test case creation becomes much easier, with AI pulling from user stories and epics.
• Regression testing for legacy products is streamlined and edge cases better identified, making quality assurance more robust.
  • Quote: “It is really easy to write the test cases now... AI can help you think beyond what you’re thinking if you’re using it correctly.” [10:59]

5. Emerging Experiments & Next Steps with AI

• Teams are starting to experiment with agentic AI: Multiple AI tools working together or AI systems collaborating for smarter outputs.
  • Quote (Prabhleen): “Now what teams have started to explore is agentic AI. We want the AI to be little more smarter, to talk to the other AI and give me the better output… that’s a huge graduation.” [07:53]
• Host Vasco draws a parallel between this and how teams of people collaborate, suggesting coordination among multiple AIs mirrors human collaboration. [08:33]

6. Broader Reflections on AI in Testing

• AI enables greater test coverage, especially for unit and UI-driven tests.
• Human expertise is now focused more on exploratory testing and risk assessment.
  • Quote (Vasco): “With the help of AI, it would be a waste not to have a very large set of unit tests to cover the functional aspects of the code.” [09:52]

7. Advice for Teams: Proceed with Caution

• AI is a tool, not a replacement for human judgment.
• Both host and guest underscore the importance of critical thinking and double-checking AI outputs.
  • Quote (Prabhleen): “The AI’s output is not the final output. It is us and our mind working… a little bit of caution can bring us great results.” [12:16]

Notable Quotes & Memorable Moments

• On the transformation in team attitudes:

  • “It started with being uncertain… to building confidence… to utilizing it to make our lives easy.” – Prabhleen Kaur [03:53]

• On AI’s support for testers:

  • “AI can help you think beyond what you're thinking if you're using it correctly… regression becomes very easy if you have a legacy product.” – Prabhleen Kaur [10:59]

• On being careful with AI outputs:

  • “The AI’s output is not the final output. It is us and our mind working… a little bit of caution can bring us great results.” – Prabhleen Kaur [12:16]
  • “Absolutely, well said.” – Vasco Duarte [12:51]

• On the analogy between agentic AI and teams:

  • “The team itself is a collection of people with their agency… Just like we are now asking different agentic AIs to interact…” – Vasco Duarte [08:33]

Important Timestamps

• 01:50 – Challenge framing: “AI is both a challenge and an opportunity”
• 03:18 – Scope set: Impact on teams, not just Scrum Masters
• 03:53 – Team journey from uncertainty to AI integration
• 05:29 – Practical uses for developers and QA
• 07:53 – Teams moving toward agentic AI
• 10:57 – Conversations with QA: Edge cases & regression
• 12:16 – Importance of human validation of AI outputs

Final Thoughts

This episode offers a practical, nuanced look at how AI is starting to transform the work of Agile teams—easing code management, test creation, and accelerating experimentation. The discussion emphasizes both the opportunity and the risks: while AI can dramatically enhance efficiency and team learning, its integration requires careful guidance, ethical awareness, and—crucially—a human touch. The episode encourages Scrum Masters and Agile teams to start conversations about AI in their contexts, to experiment bravely, but to stay vigilant, thoughtful, and rigorous in reviewing AI’s outputs.