Applying a Systems Engineering Framework to Agentic Coding: Why Prompts Fail and Structure Wins (opens in new tab)

Agentic AI coding tools are transforming how we build software. But they share a fundamental constraint: context windows are finite, and as chat sessions grow, AI performance degrades, a phenomenon Anthropic calls context rot. The model loses its grip on early instructions, leading to a frustrating "fix-it loop" where the agent fixes one thing but breaks another. Most of us prompt an agent, let it write code, review it, and repeat. This works beautifully for prototypes. But when you need to b...