Memento

In the movie Memento, the protagonist is unable to form new memories, and has to resort to an elaborate system of notes to remember what he has done in the past to uncover who killed his wife.

Like in Memento, the LLM you are working with has no memory. Whenever you ask it to perform a task, it must reconstruct enough context to do what it needs to do. This will be the prompt (e.g., the Cursor rules for your project), context that is explicitly/implicitly attached, and anything the model decides to ask for in agentic mode. That’s it! Your model is speed running understanding your codebase from scratch every time you start a new chat.

“The marvel is not that the bear dances well, but that the bear dances at all.” It is incredible that LLMs have this capacity to reunderstand your codebase from scratch every request. But it is a fragile thing; if the model fails to get the right files into its context, it can quickly start ripping up the floors, having gotten into its head the wrong idea of what you are trying to do.

Help the model do the right thing: make sure there documentation it can reference, and make sure the model can find it (e.g., via prompting, or just putting it where the model expects it to be). Avoid asking for major changes (where misalignment on the actual goal is more likely to be harmful) without contextualizing how it should fit together with the project as a whole.

Examples

• I asked Sonnet 3.7 to come up with a project plan to come up with a way of doing end-to-end testing of an already existing project. Sonnet interpreted this to mean that the raison d’etre of the entire repository was testing, and proceeded to rewrite the README to talk exclusively about testing.