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 ...

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 ...

Four big lessons, seven practical tips, three useful patterns, and five common antipatterns we learned from building an AI CRM. Context engineering has emerged as one of the most critical skills in ...

What if the key to unlocking the full potential of artificial intelligence lies not in the models themselves, but in how we frame the information they process? Imagine trying to summarize a dense, 500 ...

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 ...

“As AI makes code generation easier, the real challenge shifts to reasoning across massive, interconnected systems. Potpie is ...

As cloud project tracking software monday.com’s engineering organization scaled past 500 developers, the team began to feel the strain of its own success. Product lines were multiplying, microservices ...

When everyone has access to the same AI models, the same AI-enabled tools, and the same vendor ecosystem, organizational context becomes the differentiator. Context is demonstrated execution: the ...

Software engineering is among the many fields being changed with the fast progress in large language models (LLMs). In a few years, LLMs have evolved from advanced code autocomplete tools to AI agents ...

Model-Driven Software Engineering (MDSE) represents a paradigm shift in software development whereby models serve as the principal artefacts throughout the lifecycle of an application. By elevating ...