# MIDS Principles of Effective LLM Use

1. Always validate.  
2. Remain skeptical.  
3. **Practice reflective experimentation.** These tools are constantly changing, and our understanding of “best practices” is evolving. So experiment\! But do so thoughtfully.  
4. **The LLM is not your friend; the LLM is a hostage that will tell you anything to make you happy**. Beware AI sycophancy.  
5. **Context is king.** Managing an LLM’s context window — what it is aware of when answering questions — is paramount. For example, using an LLM to help write code without letting it see your full project is like asking it to work with one hand tied behind its back.  
   1. But more is not necessarily better — bad context (like when your conversation has gone off the rails, or there’s so much in the context window that what matters may be lost in the noise) is often worse than no context at all.
6. **LLMs are at their best when they do things you *can* do yourself (or are a small enough extrapolation beyond what you could do that you can really follow**) but which would take a lot of time. If you can’t follow what the AI is doing, you can’t supervise, verify, or redirect what it’s doing. Moreover, if you can’t follow what the AI is doing, you can’t answer questions or think critically about the strengths and limitations of its output.  
7. **LLMS are at their most dangerous when you ask them to do something you can’t do (or follow easily) yourself.**  
8. **LLMs are at their very best at tasks that are hard to do but easy to verify.**