Thoughtfully leading an AI transformation

Theme: Engineering at scale

AI and agentic coding practices continue to disrupt and transform our industry. Whether it’s engineers designing and writing code with help from agentic coding tools, or Product Managers building agentic workflows that help to shape and document ideas. The possibilities seem endless and the hype cycle is at its peak.

At times like these it’s hard to know what’s real. What is the truth behind the claims that we read in blog articles and hear about on LinkedIn? Is everyone really seeing the improvements that they claim and are all those AI transformations really going as well as it appears? And if they aren’t, then what should we do when helping to transform our own organisations and teams?

We started our AI transformation in Bloom & Wild in 2025. Like any transformation activity we’ve seen steps forward and steps backwards, made some mistakes along the way and learnt a lot from the experience. This talk is about that experience gained and where we see the future of AI heading for us.

Participant Takeaways:

• Real world examples of how to transform a Product Engineering team to a more AI and agentically driven way of working. 
• Hints and tips on leading an AI transformation thoughtfully, ethically and with care; it’s how people work that is being transformed after all!
• Why a one size fits all AI transformation does not work, and how you can ensure that your approach is tailored to the different groups of people, their different motivations and needs. 
• How systems thinking and theory of constraints have become more important than ever as AI continues to disrupt established ways of working.
• Why your company's AI transformation impacts the Product Engineering team's ways of working, and how you can, and should, support the needs of that new group of vibe coders.
• A view of the future and what teams and ways of working may well look like in the years to come. 
• The confidence that we’re still all finding our way in this new world and we’re all making mistakes along the way that we can learn from.