Context Engineering: Inside Google's Architecture for Production AI Agents
· 22 min read
The progression of Generative AI from novelty to enterprise cornerstone has necessitated a fundamental shift in system construction methodology. Early LLM adoption emphasized "prompt engineering"—ad-hoc string concatenation, trial-and-error phrasing, and minimal state management. While sufficient for simple chatbots, this approach collapses under production demands: reliability, observability, latency, and cost-efficiency.
The Google Gen AI Agent Development Kit (ADK) signals the arrival of Context Engineering—a discipline that treats context not as a mutable string buffer but as a compiled view over rich stateful systems.
