Lessons from Building an AI App Builder on Convex

Over the past months, the team behind Chef, an AI app builder, has leveraged the Convex platform to create a robust system that excels in both backend knowledge and ease of use. Chef utilizes an opinionated template that integrates Vite + React for the frontend and Convex for the backend, ensuring simplicity and clarity for large language models (LLMs). This architecture allows for programmatic prevention of errors, ensuring that LLMs cannot make irrecoverable changes, and supports queries as code for enhanced type safety. The use of modularized components simplifies complex tasks and empowers LLMs to focus on higher-level problems. Key principles learned from this development include the importance of good abstractions, limiting incorrect decisions by LLMs, providing great examples, and utilizing evaluations (evals) to quantify the success of LLM outputs. These strategies have been central to building an efficient and effective AI application framework that allows for rapid development and scalability.

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