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 ...

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.

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 ...

What if the key to unlocking truly intelligent AI isn’t just about asking the right questions, but about building the perfect environment for those questions to thrive? While much of the conversation ...

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 ...

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