Workshops & team sessions

Bring AI into your agile workflow

AI agents can accelerate delivery, but only when stories, responsibilities, and quality controls are designed for them. We build that workflow and evolve Product Ownership around outcomes rather than task administration.

AI agents change how teams implement work. Making them part of a useful workflow requires suitable tasks, sufficient context, and clear responsibility for decisions and quality.

I help you integrate AI agents into your agile practice. We work with your backlog, shape collaboration between people and agents, and develop the Product Owner’s role—with greater emphasis on understanding problems, setting priorities, and validating value.

  1. The goal

    Create a reliable agentic delivery workflow from problem definition to a reviewed, usable result. We define how stories carry sufficient context, boundaries, and acceptance criteria, where AI agents contribute, where human judgement is mandatory, and how Product Ownership evolves as implementation becomes faster.

  2. How you benefit

    You gain a reusable pattern for agent-ready stories, explicit handovers, decision gates, and human quality checks. The team can use AI without losing accountability or product intent, reduce avoidable rework, and learn from a real backlog item. Product Owners strengthen their focus on outcomes, context, prioritisation, and validation.

  3. Who is it for?

    For Product Owners, developers, Scrum Masters, technical leads, and delivery leaders who want to integrate AI agents into a real product workflow. The strongest results come when the people who define, implement, review, and accept work participate as one team.

  4. What to bring

    You should already work with a Product Backlog and understand your current path from idea to delivered result. Bring a real use case and examples of existing stories. AI expertise is not required, but the team needs access to an approved AI tool and must be able to make decisions about workflow and quality controls.

Preparation

Bring real stories and a suitable use case. Hands-on exercises require access to an approved AI tool and an appropriate working environment. We agree on these during preparation.

What we work on together

  • Identify suitable tasks for AI agents.
  • Add context, boundaries, and testable acceptance criteria to user stories.
  • Clarify team structure, responsibilities, handovers, and human reviews.
  • Design the workflow from backlog item to verified result.
  • Test the workflow with a practical example and reflect on the Product Owner’s role.

What you take away

Worked examples of agent-ready stories, a trialled workflow for collaborating with AI agents, and clear team responsibilities.

What’s challenging your team?

Let’s discuss where you are today and what support would help. Together, we’ll agree on the right scope and format.

Book an introductory call