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 ...

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 ...

Artificial intelligence entered the crypto ecosystem primarily as a reactive tool rather than a reasoning agent—responding to queries instead of maintaining situational awareness. Early forms of ...

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 ...

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.

While some consider prompting is a manual hack, context Engineering is a scalable discipline. Learn how to build AI systems that manage their own information flow using MCP and context caching.

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 ...