JUNE 15–18|SAN FRANCISCO
Join us at the world’s largest data, apps and AI event.
Validate the skills needed to design, manage, and govern AI context effectively
by Rachel Canetta, James Kantor and Trang Le
As AI systems move from experimentation to real-world deployment, one truth is becoming clear: the quality of an AI system depends not just on the model, but on the context it receives. Context engineering—the discipline of designing, curating, and delivering the right information to AI systems at the right time—has quickly emerged as a critical capability in today’s AI landscape. Without it, even the most advanced models can produce incomplete, inaccurate, or inconsistent results. With it, organizations can build AI agents that are reliable, grounded in enterprise knowledge, and capable of handling complex, multi-step tasks.
