Does AI still need Convex guidelines?

The discussion revolves around the necessity of including Convex guidelines in AI model prompts, initiated when npm create convex@latest began shipping these guidelines to fill Convex's knowledge gaps compared to larger databases like Postgres or Express. The text details the "evals project," a series of rigorous tests that evaluate models' understanding of Convex, highlighting categories like fundamentals, data modeling, and actions. Despite advancements in models and increased availability of Convex data online, the need for guidelines remains debatable, as recent experiments showed mixed results regarding their impact on model performance. Particularly, guidelines seem to aid older or smaller models significantly, whereas top models perform well with or without them, albeit with slight performance differences. The text explores alternatives to the current guideline setup, such as shrinking the guidelines or adopting a retrieval-based index system that allows models to access documentation dynamically rather than relying on pre-loaded prompts. The author remains undecided on the best approach, emphasizing the importance of further experimentation and inviting community input.

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