{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Contextually Aware","title":"Context Engineering: What Every PM Building AI Needs to Know","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/07a139e1\"></iframe>","width":"100%","height":180,"duration":571,"description":"The best prompt engineer I know told me he stopped writing prompts.He said: \"Prompts are maybe 5% of what makes AI actually useful. The other 95%? It's everything the model sees before you even ask a question.\"If you're building AI features and still obsessing over prompt wording, you're optimizing the wrong thing.In this episode, I break down context engineering—what it is, where the term comes from, and how product managers can own the context window without writing code.**What you'll learn:**- Why \"know your user\" is the foundation of context engineering- The 3 types of retrieval: keyword, semantic, and graph RAG- Why more context actually hurts performance (context rot)- How to build evals that learn from future outcomes- 5 actionable homework items you can start today**People mentioned:**- Simon Willison (AI Engineer, Creator of Datasette)- Kevin Weil (CPO at OpenAI)**Key terms:**- Context window- RAG (Retrieval Augmented Generation)- Semantic search / Vector databases- Graph RAG / Knowledge graphs- Context rot- Evals / Data flywheelContext engineering is where product strategy meets model behavior. The best AI products aren't using better models—they're using better context.","thumbnail_url":"https://img.transistorcdn.com/PfqMDTkostuShnybuhV6nlGAxYo3V7hPlonxdle3dic/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS8yN2I2/YjEzMDRhYjY0YmZj/OGJjYmJmNmRlODk0/OGQzZi5wbmc.webp","thumbnail_width":300,"thumbnail_height":300}