Why the AI stack for modern engineering teams requires both coding and context

What this post added

This post introduces a two-layer model for AI tooling in engineering, emphasizing the need for a foundational context layer alongside coding surfaces. It details how enterprise context platforms, AIOps/observability tools, and general-purpose AI platforms work together. The post highlights the evolution of AI from experiments to infrastructure, the importance of blending tools rather than vendors, and the critical role of security, governance, and explainability in building a scalable and trustworthy AI stack for engineering teams.