There’s a quiet but profound transformation underway in how businesses interact with backend systems. It’s not a flashy app or piece of consumer technology - it’s happening at the infrastructure level ...

Companies are realizing that higher AI productivity does not come from using bigger models, but rather from using AIs that understand the context they operate in. Context helps AI interpret ...

2025 has seen a significant shift in the use of AI in software engineering— a loose, vibes-based approach has given way to a systematic approach to managing how AI systems process context. Provided ...

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 ...

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 ...

As AI becomes embedded in more enterprise processes—from customer interaction to decision support—leaders are confronting a subtle but consistent issue: hallucinations. These are not random glitches.

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 ...

Have you ever wondered why even the most advanced language models sometimes produce irrelevant or confusing responses? The answer often lies in how their context windows—the temporary memory they use ...