Engineering the Developer Experience

Every engineering organization is being asked the same question right now: how do we adopt AI? But the teams getting real results aren't starting with the AI tooling. They're starting with developer experience — because it turns out that the same investments that make developers productive are exactly the ones that determine whether agentic development actually works or just creates a new category of mess.

Engineering the Developer Experience at QCon San Francisco 2026 treats DevEx not as a feel-good initiative or a platform team's side project, but as a discipline you build deliberately — with measurable impact on how engineers, and increasingly the agents working alongside them, get software shipped.

We'll hear from practitioners who are building and evolving the systems that shape how engineers work every day, and from researchers studying what's happening to developer productivity, cognition, and satisfaction as AI reshapes the craft — both navigating the very real tension between accelerating with AI and keeping humans effective, engaged, and in control.

This track explores:

• Measuring what matters: How teams are defining and instrumenting developer productivity beyond vanity metrics? Connecting developer experience signals to engineering outcomes that leadership cares about.
• DevEx as architecture: The system design decisions that make or break how engineers work — from build systems and CI/CD pipelines to internal APIs and local development environments — and how those choices compound over time.
• The agentic shift: What's changing when teams integrate AI coding assistants, autonomous agents, and code review tooling into the workflow — including what's working, what's not, and what experienced engineers wish they'd known earlier. As more code gets generated, the bottleneck moves to reviewing, verifying, and landing it safely.
• Designing for humans and agents alike: Autonomous agents are now consumers of your internal platform too — reading your docs, calling your APIs, running in your environments. The interfaces, feedback loops, and reproducible setups that make developers effective turn out to make agents effective as well. What does developer experience mean when your "developers" are a mix of people and machines?
• The human side of the transformation: What happens to engineering culture, skill development, code ownership, and team trust when AI reshapes how work gets done — and how leaders are managing that transition without losing what makes their teams effective.

This track is designed for engineering leaders, senior engineers, and architects who are responsible for how their organizations build software. You'll hear from peers who are deep in the work: people running developer productivity programs, building internal tooling, rolling out AI-assisted workflows, and making the hard calls about what to automate and what to protect. You'll leave with practical patterns for engineering developer experience deliberately, and a clearer picture of how to adopt AI in a way that actually makes your engineers better, not just faster.