Practical use of AI/LLM

Shipping with AI Without Shipping Regret

Chris Ayers

Chris Ayers

Chris Ayers is a Principal Software Engineer at Microsoft, where he builds AI-driven tooling to analyze outages and incidents across Azure. His work focuses on improving the way engineers understand failures, uncover risks, and strengthen reliability at cloud scale. With a background spanning DevOps, cloud architecture, and modern application design, Chris brings both engineering depth and practical experience to the challenge of making large systems more resilient.

He’s also a frequent international speaker who loves sharing real-world lessons about developer productivity, reliability, containers, and automation. Outside of work, Chris is a proud dad, lifelong gamer, avid reader, and unapologetic nerd.

1 / 2

AI can speed up your work, or it can help you confidently ship the wrong thing faster. The difference is not the tool. It is the workflow around it.

This session is a practical guide to using AI in everyday engineering without sacrificing reliability, security, or quality. We will cover where AI is useful across design, debugging, refactoring, documentation, testing, and incident follow ups, and where it tends to fail. You will learn how to spot common failure modes like hallucinated APIs, stale assumptions, context overload, weak test coverage, and outputs that look plausible but do not hold up under review.

Instead of one-off prompt tricks, this talk focuses on repeatable practices teams can actually use: plan-first prompting, better context management, evidence-based verification, test-driven review, and human gates that keep accountability with the engineer. You will leave with practical techniques for getting the speed benefits of AI while still shipping work you would bet your pager on.