Context is All You Need: The Art and Science of Information Design
Context engineering, LLMOps, Models
AI systems today have unprecedented capabilities, yet they consistently fail at tasks that should be simple. The bottleneck isn't model intelligence, it's information design. While everyone focuses on better models and fancier frameworks, the real breakthrough lies in understanding context as a design discipline.
In this session, you'll discover the patterns that separate high-performing AI systems from those that struggle. We'll explore the "art" - intuitive principles of information hierarchy and attention flow, alongside the "science" = measurable patterns for structuring and managing information that consistently improve AI results.
You'll learn practical design patterns that work across any AI application: how to architect information flows that scale, when to compress vs. expand context, and why sequence often matters more than content. Walk away with a systematic approach to context engineering that transforms unreliable AI interactions into more predictable, powerful tools.
Lena Hall is an expert in practical AI adoption, data engineering, cloud and pragmatic architecture, with extensive experience leading large, high-performing technical teams.
Lena is a Senior Director of Developer Relations at Akamai Technologies. She has 15+ years of deeply technical background as a solution architect, technical leader in large-scale data, analytics, machine learning, and cloud computing. Prior to Akamai, Lena worked as Head of Developer Experience, North America at Amazon Web Services and led Big Data Developer Relations at Microsoft. She is also a co-founder of Droid AI, helping people get real results from AI.
She frequently shares practical knowledge on her YouTube channel (youtube.com/@lena-hall) and LinkedIn (linkedin.com/in/lena-hall) and at industry conferences as an international keynote speaker.