context-engineering-advisor

## Purpose 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. ## Key Concepts ### The Paradigm Shift: Parametric → Contextual Intelligence **The Fundamental Problem:** - LLMs have **parametric knowledge** (encoded during training) = static, outdated, non-attributable - When asked about proprietary data, real-time info, or user preferences → forced to hallucinate or admit ignorance - **Context engineering** bridges the gap between static training and dynamic reality **PM's Role Shift:** From feature builder → **architect of informational ecosystems** that ground AI in reality --- ### Context Stuffing vs. Context Engineering | Dimension | Context Stuffing | Context Engineering | |-----------|------------------|---------------------| | **Mindset** | Volume = quality | Structure = quality | | **Approach** | "Add everything just i...