Context is the bedrock on which meaningful interactions are built. We’re at the brink of a major shift in AI. What began as simple, task-specific models is now evolving into something far more ...

As large language models (LLMs) become increasingly sophisticated, a new discipline is emerging that goes far beyond traditional prompt engineering: context engineering. This evolving practice ...

What if the key to unlocking the full potential of artificial intelligence lies not in the models themselves, but in how we frame the information they process? Imagine trying to summarize a dense, 500 ...

In the early days of generative AI, the technology industry’s primary focus was “prompt engineering,” the art of mastering how to ask questions to precisely generate hoped-for results. But as AI ...

While prompt engineering will remain vital, getting consistent, situationally aware results from AI models will require IT teams to build context ingestion processes for agentic AI. Organizations ...

Agentic AI systems need a deep understanding of where they are, what they know, and the constraints that apply. Context engineering provides the foundation. Enterprises have spent the past two years ...

Four big lessons, seven practical tips, three useful patterns, and five common antipatterns we learned from building an AI CRM. Context engineering has emerged as one of the most critical skills in ...

CARE-ACE supports autonomy through bounded agentic reasoning, in which diagnostic, prognostic, planning, and risk-assessment ...