coaching

Agile & AI: From Genie-Level Hype to Practical Collaboration

AI has arrived in our workflows like an unpredictable genie — powerful, fascinating, and sometimes a little reckless. Kent Beck, one of the authors of the Agile Manifesto, recently described AI agents as “genies” that can grant wishes but rarely in the way you expect. His advice? Experiment boldly, but don’t forget the risk you’re taking.

That perspective resonates deeply with Agile practitioners. After all, agility is about embracing uncertainty, experimenting, and learning quickly. The challenge is figuring out how AI can serve our teams without letting the hype or fear distract from the real work: delivering value to people.

1. Build Safety Before Scale

Teams are often pressured to “adopt AI now.” But introducing AI without psychological safety creates resistance or misuse. Coaches and Scrum Masters can help by framing AI as an experiment, not a mandate. Encourage teams to:

  • Start with small, low-risk use cases.
  • Share what works — and what doesn’t — openly.
  • Normalize that AI will sometimes fail spectacularly (and that’s okay).

2. Use AI to Augment, Not Replace

Agile thrives on collaboration, creativity, and problem-solving — qualities AI can’t replicate. But it can amplify them. For example:

  • Product Owners can use AI to analyze customer feedback at scale.
  • Scrum Masters can generate retrospective prompts tailored to their team’s patterns.
  • Developers can get “draft” code snippets or test cases that spark discussion.

The key is treating AI as a sparring partner, not a decision-maker. Humans remain accountable for judgment, ethics, and empathy.

3. Focus on the “Why,” Not the Tool

It’s tempting to jump straight to prompts and plugins. But Agile leaders should remind teams: every tool is in service of a purpose. Before introducing AI into your workflow, ask:

  • What problem are we trying to solve?
  • How will this help us deliver faster feedback or higher value?
  • What will we measure to know it’s helping?

Without a clear “why,” AI risks becoming another shiny object that drains time instead of creating impact.

4. Coach for Resilience in Uncertainty

AI, like Agile, is about embracing the unknown. Coaches can use AI adoption as a teaching moment:

  • Practice adaptability when results aren’t perfect.
  • Encourage curiosity over judgment.
  • Help leaders resist the urge to over-control outcomes.

These mindsets don’t just make AI safer to adopt — they strengthen agility itself.

Closing Thought

AI will continue to evolve in ways we can’t predict — just like the genie that twists every wish. Our role as Agile leaders isn’t to tame the genie but to help teams use its power wisely, with intention and care. By grounding AI adoption in safety, purpose, and human collaboration, we keep agility at the center — and ensure that our teams remain the true source of innovation.