context-engineering-advisor

Diagnose whether your AI workflows are context stuffing or context engineering, then implement structured practices to improve output quality. Guide product managers through diagnosing whether they're doing context stuffing (jamming volume without intent) or context engineering (shaping structure for attention). Use this to identify context boundaries, fix "Context Hoarding Disorder," and implement tactical practices like bounded domains, episodic retrieval, and the Research→Plan→Reset→Implement cycle. Key Distinction: Context stuffing assumes volume = quality ("paste the entire PRD"). Context engineering treats AI attention as a scarce resource and allocates it deliberately. This is not about prompt writing—it's about designing the information architecture that grounds AI in reality without overwhelming it with noise. The Fundamental Problem: PM's Role Shift: From feature builder → architect of informational ecosystems that ground AI in reality Critical Metaphor: Context stuffing is like bringing your entire file cabinet to a meeting. Context engineering is bringing only the 3 documents relevant to today's decision.