AWS details four context engineering layers for production AI agents

The article explains that standard 200K-token windows are often insufficient for complex tasks like data analysis, which can consume over 150K tokens in 15 minutes. To address this, Deep Insight uses a hierarchy of specialized agents (Coordinator, Planner, Coder, etc.) that share only compressed summaries via a shared state dictionary. This isolation keeps individual agent contexts under 25K tokens.

Key implementation details include a 'write-and-execute' tool that reduces token usage by about 95 percent by keeping code in files rather than the context window. Additionally, a skills system loads detailed instructions on demand, shrinking the system prompt by about 97 percent compared to loading all guides at startup. The guide emphasizes that these techniques, drawn from Anthropic’s engineering posts and the Strands Agents SDK, are necessary to prevent context rot and maintain accuracy in long-horizon tasks.