Context-Driven AI Engineering: A Techno-Functional Guide for Product Managers of Agentic AI Systems
The world is leaping towards building products with agentic architecture; those powered by autonomous, goal-driven AI agents. These systems won’t just respond; they will reason, plan, and act independently. But with such autonomy comes complexity. Traditional engineering and product management models are no longer sufficient. Enter Context-Driven AI Engineering, an approach that embeds the surrounding situational, user, and system-level context into every stage of AI product development. For product managers (PMs) working at the intersection of data, design, and delivery, this isn't just a methodology, it's a necessity. Why Context is Critical in AI Engineering Autonomous agents interact with complex environments: users, APIs, documents, dynamic tasks, and even other agents. Without context-awareness, they risk becoming brittle, hallucinating, or acting inappropriately. Context isn't just data, it's relevance . It includes: User context : Who is interacting, with wha...