AI, Refined: Moving Beyond Prompts with Context Engineering
Unlock smarter, more reliable AI by moving beyond prompts and building intelligent systems.
This webinar is over.
Presented by:
Marc Hamel
Sponsored by
ERE Pro is the world’s largest library of talent acquisition media. ERE Pro features deep dives into the recruiting challenges that real talent acquisition professionals face daily, from practitioners that have already tackled them.
About the speakers
Marc Hamel
Senior Sourcer
Waymo
Marc is a tech-sourcing veteran with 16+ years of experience across agencies, startups, and giants like Amazon, Meta, and now Waymo. At Waymo, he continues his work at the intersection of sourcing and Generative AI, building tools, leading education efforts, and driving thoughtful adoption. He spent seven years at Amazon, where he helped shape their AI recruiting strategy. Actively involved in sourcing communities, Marc enjoys sharing insights and supporting fellow TA professionals. Outside of work, you’ll find him exploring Austin, sampling IPAs, and cheering on the Chicago Cubs.
As large language models become more deeply integrated into products, workflows, and decision-making, it’s clear that effective AI doesn’t start and end with a well-crafted prompt. Instead, the most powerful applications rely on a thoughtfully engineered context—one that includes the right tools, data, history, and memory to guide the AI toward useful, reliable outcomes.
In this session, Marc Hamel will break down the shift from prompt engineering to context engineering, offering a practical framework to understand when each applies and how they work together. He’ll share actionable techniques, walk through an end-to-end example, and showcase tools that support more dynamic, context-aware AI systems. If you’re building or scaling AI capabilities, this session will equip you to drive smarter, more consistent results.
Attendees will gain insights around:
AI Effectiveness through Better Design – How context engineering improves accuracy, adaptability, and relevance in LLM outputs.
Prompting Tactics vs. System Thinking – Understanding when prompt engineering is enough—and when it limits your AI’s potential.
Tools that Extend AI Context – Solutions that inject external knowledge, memory, and functionality into AI workflows.
End-to-End Example – A detailed walkthrough of how prompt and context engineering come together in a real-world use case.
Don’t miss this opportunity to deepen your understanding of how to architect AI systems that are not just responsive—but truly intelligent.
