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 ...

The AI conversation in marketing has been dominated by two things: which tools to buy and how to write better prompts. Both are real skills. Neither one determines whether a marketing team gets ...

Developers are discovering that Model Context Protocol shines at providing AI coding agents with highly relevant software engineering context, on demand, at run time.

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 ...

The hottest discussion in AI right now, at least the one not about Agentic AI, is about how "context engineering" is more important than prompt engineering, how you give AI the data and information it ...

Effective AI results will increasingly depend less on crafting ever-more-detailed prompts and more on giving systems the relevant, current, and well-structured context they need to understand intent.

What if the AI tools you rely on could become not just smarter, but exponentially more effective? Imagine an AI assistant that doesn’t just follow instructions but intuitively understands your needs, ...

Every organization is facing the same problem: engineering teams don’t lack data. They lack context for that data.