CONFERENCE DAY ONE - Wednesday 22nd October

Join Julien Roynette and Thomas Rumas, developer experience leaders at ADEO, as they outline their organisation’s developer experience evolution - from understanding tech stacks and streamlining onboarding to leveraging a unified internal DevHub and fostering a collaborative engineering culture. This session will feature a demonstration and explore how they’re able to deliver a more seamless and empowering developer journey though:

• Mapping the DX maturity journey by deeply understanding developer needs, stacks, and behaviours.
• Centralising tool visibility and onboarding through platforms like DevHub to streamline the developer experience.
• Building internal communities that foster collaboration, observability ownership, and shared problem-solving.
• Gathering continuous feedback through structured campaigns to guide ongoing improvements.

Julien Roynette

Head of Developer Experience
ADEO

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Thomas Rumas

Developer Advocate
ADEO

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Session Available For Sponsorship

As AI shifts from experimentation to embedded functionality, engineering leaders face a new paradigm in how developer tools and platforms are built, deployed, and measured. This panel brings together experts building AI-powered developer applications to explore the operational, architectural, and cultural shifts required to make AI work in practice.

• Why AI represents a new paradigm in platform and software engineering.
• Troubleshooting AI applications without access to real-world data.
• Balancing rapid experimentation with cost, latency, and error reduction.
• Managing data decay and abstracting telemetry for long-term AI performance.
• The impact of AI systems on Developer Experience metrics.
• Where AI is already delivering measurable value - and where it’s not.

Jacob Castello

Lead Site Reliability Engineer
N26

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Dan Suleiman

Director, Solutions Engineering, Europe
Checkmarx

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Maebh Booth

Senior Head of Engineering
Former Marks & Spencers / Yell

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Martin Wheatley, Technology & Development Director at Envision Pharma will join us to unpack the broader implications and impact of AI-assisted development on engineering teams. An exploration of what’s now possible, what’s changing for developers, and what’s coming next.

• What do your team requirements look like in the age of AI?
• Demonstrating how AI can help solve tasks for developers and UX designers.
• Where AI coding tools truly add value - and where they fall short.
• The evolving role of the developer in an AI-assisted world.
• Balancing creativity, speed, and reliability with AI.
• What this means for your teams, your workflows, and your future.

Martin Wheatley

Technical & Development Director
Envision Pharma Group

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Start-ups move fast, experiment freely, and build with urgency—enterprises, by contrast, operate under scale, structure, and regulation. What happens when the two worlds collide, and what lessons can leaders take from each extreme? This session unpacks how to bring the agility of start-ups into even the most complex environments.

• What high-velocity start-ups do differently, and why it works.
• How large enterprises can adopt start-up practices without losing stability.
• Building engineering excellence in highly regulated industries.
• Balancing speed, compliance, and innovation to create lasting impact.

Harveer Tiwana

Engineering Excellence Manager
Ford Credit

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Introducing Engineering Productivity measurement and analysis to Lloyds Banking Group - the UK's largest bank, with ambition to become the UK's largest FinTech. To enable the aspiration - focus is needed on both Qualitative and Quantitative data points to inform our products and service to our Engineering community.

• Bank History - multiple takeovers/mergers causing disparate engineering practices - causing immeasurable friction for Engineers coupled with pressure to go faster to keep up with competition.

• Assessment of frameworks; identifying data sources; understanding the Productivity 'product' and 'customers'.

• Quantitative data measurement and analysis - what measured - so what? Qualitative data measurement and analysis - what measured and how - so what?

• Considerations from product focus - adoption, prototype feedback loops, customer influence, stakeholder influence, consumerability.

• Impact of data insights on Productivity.

Hilary Lanham

Head of Engineering Productivity Services
Lloyds Banking Group

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Tom Kelk

Senior Product Owner – Productivity Intelligence
Lloyds Banking Group

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As AI continues reshaping the software development lifecycle, engineering leaders are under pressure to identify real outcomes. From co-pilots to agentic systems, AI promises major productivity gains - but only when applied to the right problems with the right tools. David Graca is the Principal Developer Experience Engineer at AXA, he joins us here to explore how we are looking to adopt AI in software development, balancing cost, efficiency, and developer joy.

• Unlocking and measuring the real-world productivity impact of AI tooling.
• Understanding the difference between agentic AI and co-pilots - and when to use each.
• Avoiding misuse: AI is a tool, not a solution - how to align AI capabilities to developer pain points.
• Cost considerations and operational trade-offs of integrating AI into daily development workflows.

David Graca

Developer Experience Lead Expert
AXA

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True developer experience transformation isn’t just about tools or processes—it’s a cultural movement. Leaders must shift mindsets, inspire engineers, and communicate value in a way that resonates. This session explores how to build momentum that drives real, lasting change.

• Using storytelling to demonstrate and sell the value of developer experience.
• Shifting mindsets toward continuous improvement and growth.
• Empowering engineers to think bigger, take ownership, and innovate.
• Embedding culture as the foundation for lasting DX transformation.

Treating the platform as a product is more than a mindset shift - it’s a practical approach to making platforms genuinely useful for developers. Standardising tooling alone isn’t enough. Adoption comes from solving real pain points, simplifying workflows, and treating internal teams like customers. This session explores how product thinking at DKB transforms internal platforms into high-impact tools that developers actively want to use.

• How to define and deliver a “Thinnest Viable Platform” that meets core developer needs fast.
• Embedding feedback loops, usage analytics, and roadmaps to evolve the platform iteratively.
• Why self-service, good UX, and platform branding matter for developer adoption.
• Balancing standardisation with flexible usage to reduce cognitive load and increase satisfaction.
• Key metrics to track: adoption, satisfaction, time-to-value, and engineering efficiency.

Stephane Di Cesare

Senior Platform Engineer, Platform Experience
DKB

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Session Available For Sponsorship

Developer adoption isn’t automatic-no matter how powerful your platform is. The most successful platform engineering teams treat developers as customers, designing clear, intuitive “paved roads” that streamline common workflows while supporting broader innovation. This session focuses on how to define, build, and continuously evolve those pathways to drive real adoption and trust.

• Identifying and mapping developer journeys to eliminate friction and redundant decision-making.
• Tactics for aligning paved roads with both infrastructure and application team needs.
• Enabling self-service without sacrificing quality, reliability, or observability.
• Establishing feedback mechanisms to refine and expand paved road offerings over time.

Hasith Kalpage

Director, Platform Engineering & CISO
Cisco

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Louis Bailleul

Director of Architecture and Platform Engineering
TGS

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Engineering excellence doesn’t happen in isolation - it thrives in environments where learning is continuous, knowledge is shared, and teams are empowered to evolve. This session, Daniel Gittins, Developer Experience & Strategy Leader, explores how Ford is seeking to foster a culture of excellence by connecting engineering communities, enabling peer learning, and embracing dynamic re-teaming.

• Leveraging experimental peer learning and cross-team knowledge sharing to accelerate growth.
• Creating scalable frameworks that unite siloed teams and foster shared training and ownership of engineering standards.
• Linking DORA Metrics to Capability Building: How to use performance insights to set aspirations and guide team development.
• Dynamic Re-Teaming for Continuous Learning: Rotating engineers across teams to promote adaptability, innovation, and cultural cohesion.
• Building small, focused capabilities that collectively drive a new culture of engineering excellence.

Daniel Gittins

Developer Experience & Strategy Manager - Connected Vehicle Software
Ford

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