Maebh Booth

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.

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.