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 ...

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 ...

Every great leap in computing has reshaped not just technology but also the industries built around it. When microprocessors became the heart of enterprise computing, services firms flourished by ...

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 powerful: multi-turn, reasoning-driven agents that can plan, act and adapt ...

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 ...

元Hugging Faceのテクニカルリードで、Google DeepMindのシニアAIリレーションエンジニアであるフィリップ・シュミット氏が、AIを使う上で「コンテキストエンジニアリング」が必須であると、自身のブログで主張しています。 一般的に、AIのレスポンスを最適化 ...

What if the secret to unlocking the full potential of AI coding agents isn’t in the algorithms themselves, but in the way we communicate with them? Imagine an AI tasked with refactoring a sprawling, ...

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 ...