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 ...

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 ...

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 ...

Jared Bowns is Head of Data and AI at Elyxor, helping enterprises turn emerging AI into scalable, real-world business value. Large language models (LLMs) have evolved from novelty to necessity in ...

To date, vibe coding platforms have largely relied on existing large language models (LLMs) to help write code. However, writing code is only one of many different tasks developers need to perform to ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Madelyn Olson discusses the evolution of ...

AI initiatives rarely fail because of model quality. They fail because the underlying data systems were never designed for reliability, context retrieval, or operational consistency.

Model Context Protocol, or MCP, is arguably the most powerful innovation in AI integration to date, but sadly, its purpose and potential are largely misunderstood. So what's the best way to really ...