AUGUST 5, 2026  |  Virtual Summit

The Best of AI Software Delivery.
Curated for 2026

Six standout talks. Practical insights from thought leaders. Proven strategies for the AI era of software delivery.

AI Software Delivery

Platform Engineering

Developer Experience

Governance

security

Release & Experimentation

Featured Speakers

Liz Toh

Head of Experimentation

Juan Pablo Soriano

Product Manager - Investments

Andrew Greenough

CI/CD Engineering Lead

Tony Phillips

Engineering Lead - DevOps Services, Engineering Platform

Natalia Sawicka

Head of Engineering

James Ford

Developer Experience Lead

Rahul Bondalapati

Engineering Manager, DevSecOps

Matthew Skeleton

CEO/CTO at Conflux | Co-author of Team Topologies

Mark-David McLaughlin, Ph.D.

Head of Security Architecture and Engineering

Gene Kim

Author, Researcher, and Multiple Award-Winning CTO

Jyoti Bansal

CEO

Why Attend

AI for Everything After Code

Learn how leading engineering organisations are applying AI across the entire software delivery lifecycle. From planning and development to testing, deployment, and operations.

Improve Developer Productivity

Explore proven strategies for reducing developer friction, streamlining workflows, and creating an engineering environment where teams can deliver more value with less effort.

Scale Without Sacrificing Control

Discover how high-performing teams are increasing delivery velocity while maintaining the security, governance, and reliability required by modern enterprises.

Avoid Costly Mistakes

Learn from real-world successes and failures, including the common pitfalls organisations encounter when adopting AI across the software delivery lifecycle.

Agenda

Sessions

Time (CEST)

What Engineering Excellence Looks Like Now

After AI adoption, what defines a truly high-performing engineering organization? This closing keynote synthesizes the day’s insights into a clear framework for improving DevEx, aligning AI with platform discipline, and building sustainable performance beyond code generation.

Gene Kim
Jyoti Bansal
Harness
10:00 am - 10:25 am

From Complexity to Clarity: Lloyds’ Journey to a Unified Developer Platform

Discover how Lloyds Banking Group is simplifying software delivery with an Internal Developer Platform, using Golden Paths, self-service onboarding, and standardized pipelines to improve developer experience while balancing innovation with enterprise stability.

Andrew Greenough
Lloyds Banking Group
Tony Phillips
Lloyds Banking Group
10:25 am - 10:55 am

The Human Bottleneck: Cognitive Load in the Age of AI

AI is accelerating software delivery but it can also create cognitive overload. Join Team Topologies co-author Matthew Skelton as he explores how to redesign teams, workflows, and AI adoption to boost productivity without burning out developers.

Matthew Skeleton
Conflux
Martin Reynolds
Harness
10:55 am - 11:30 am

Experimentation at Scale: How Leaders Increase Velocity Without Losing Control

Discover how leading financial institutions are moving beyond traditional A/B testing to accelerate experimentation, reduce delivery bottlenecks, and build repeatable processes for testing and releasing with confidence.

Juan Pablo Soriano
N26
Liz Toh
JPMC
Alex Bock
Harness
11:30 am - 12:05 pm

From Roadblocks to Results: Rethinking the Security–Engineering Relationship

Security and engineering don't have to be at odds. Hear how technology leaders from Intersystems and Citizens Bank are building trust, embedding security earlier, and balancing speed with governance to make security an enabler—not a blocker—of software delivery.

Rahul Bondalapati
Citizens
Mark-David McLaughlin, Ph.D.
Intersystems
Adam Arellano
Harness
12:05 pm - 12:30 pm

Are Developers Faster or Just Busier?

AI can increase output while quietly expanding review time, rework, and cognitive load. Discover how to separate real productivity gains from activity inflation and ensure AI adoption strengthens, rather than strains, your teams.

Natalia Sawicka
Bol
James Ford
Comparethemarket
Hardeep Bath
Harness
12:30 pm - 12:50 pm