Sunday, May 17, 2026

The AI Engagement Lifecycle with Endava, Dava.X.AI, and Miro


Endava set out to reinvent how IT services get delivered in an AI-native world. Dava.X.AI is the group inside Endava driving that shift. Miro is the workspace they're building it on. Together they've shipped Davaflow — an AI engagement lifecycle that runs from signal to explore to govern to evolve, with humans and agents working alongside each other the whole way.


Takeaways

Reframe from value capture to value creation — don't use AI to make existing processes 10–15% better, reimagine the work entirely from an AI-first perspective.

IT services hit its "ChatGPT moment" two years ago when clients and analysts started asking Endava why they were needed if AI could just write the code.

AI is becoming a method, not a tool — just as Agile organized humans to do work, this new method organizes agents and the people working alongside them.

The technology question is largely settled; the change management question isn't — quality has hit the inflection point, and what remains is the human shift, much like Waterfall-to-Agile.

DavaFlow runs in four phases — Signal, Explore, Govern, and Evolve — moving from identifying the right problem, through virtual personas and prototypes, to governing agent output, to evolving in production.

Chat is the wrong interface for most of this work — humans are visual creatures, and tools like Miro give LLMs context that a chat box never could.

AI-driven work can produce better traceability than humans ever did — every decision and prototype connects back through the chain of thought, what Joe called "traceability on steroids."

Anyone can buy the tools — what separates enterprise work from vibe-coding chaos is policy-as-code, defined skills, and human-in-the-loop checkpoints.

Adoption happens in baby steps, not the full vision — showing people the end of the journey overwhelms them, so start at signal and layer in each next step.

The hardest part is the identity question — engineers liked writing code and designers liked crafting prototypes, and the shift is a growth-mindset problem, not a skills problem.


Links from the Podcast


Upcoming Miro Canvas Events


Contacting the Guests



Chapters

00:00 Introduction to Endava and AI Transformation

08:54 Navigating the AI Landscape: Challenges and Opportunities

17:52 The Evolution of Miro and AI Integration

24:00 Dava Flow: The AI Engagement Lifecycle

25:49 The Power of Visual Context in AI

27:03 Enhancing Contextual Understanding with AI

29:12 Temporal Dimensions in Decision Making

31:27 Navigating Change in Organizational Mindsets

35:40 Demonstrating Value to the C-Suite

38:13 Embracing the Future of Work

41:09 Amplifying Human Creativity with AI


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